TLDR: Reinforcement Learning (RL) teaches AI to improve through millions of trial and error attempts at warp speed, powering everything from back-flipping robots to smarter cities. Trust me, it’s going to be a very big deal.

Remember that rush when you finally beat that impossible video game boss after fifty attempts?

Or mastered a skateboard trick after face-planting and ripping up your knees?

That's your brain on reinforcement learning—trying, failing, adjusting, and eventually nailing it. Now imagine bottling that learning process, turbocharging it with a million virtual attempts per hour, and unleashing it on everything from robot dogs to traffic systems.

Welcome to reinforcement learning—where agents learn not by being told what to do, but by figuring it out themselves.

Learning by Doing it Millions of Times

Picture this: You're teaching your friend to ride a bike.

Option A: Spend hours explaining the physics of balance, tire friction, and momentum.

Option B: Put them on the bike, give a little push, and let them figure it out (with a helmet, obviously).

Reinforcement learning (let’s just say “RL”) is firmly in camp B—it's all about learning by doing, failing, and trying again.

But here's where computers have us beat: While you might try a skateboard trick 50 times before landing it, an AI can attempt the same task 50 million times before breakfast. And unlike humans, computers don't get tired, frustrated, or need ice packs for their bruised elbow.

"But wait, Nye" you ask, "isn't AI just about massive language models like ChatGPT spitting out essays and code?" That's just one flavor of the AI ice cream shop, friend. Reinforcement learning is the chocolate chip cookie dough that's about to take over the menu.

Here. --- Let's do the classic industry example: Imagine a digital mouse in a virtual maze.

At first, the mouse has no clue what to do—it's like you being dropped into a foreign city without Google Maps. It tries going left (smacks into a wall!), right (uh-oh, dead end!), backward (nothing useful there either!). Each time it makes a choice, it gets feedback:

• Find cheese: +10 points (woohoo!)

• Hit wall: -1 point (ouch)

• Wander in circles: -0.1 points (boring penalty)

No human tells the mouse which way to turn. Instead, after thousands of attempts, it builds a mental map: "Turn left at the first junction, right at the second, and—jackpot!—virtual cheese awaits." This is reinforcement learning in its purest form: try, get feedback, adjust, repeat.

In a virtual world, this mouse is called an “agent.” The series of actions or decisions is makes is called the “policy.” And the reason the agent makes the decisions it makes is called the “reward function.” It’s all crazy math that is far beyond our heads, but at it’s core, it allows the agent to learn how to do things through million and millions of attempts.

What makes this revolutionary is how it mirrors human learning but at warp speed. When you learned to walk, nobody downloaded "walking.exe" into your brain. You stood up, fell down, and kept trying until neural connections formed that helped you balance. RL works the same way—but can compress years of human learning into hours.

While programming each line of code is cumbersome. We can use reinforcement learning to train autonomous systems, like, (I’m guessing) personalized robots.

RL's Greatest Hits

Remember when IBM's Deep Blue beat chess champion Garry Kasparov in 1997? That WAS NOT reinforcement learning—it was brute-force calculation. Same with Watson defeating Ken Jennings on Jeopardy!

Fast forward to 2016, when Google DeepMind's AlphaGo defeated world champion Lee Sedol at Go—a game with more possible positions than atoms in the universe. AlphaGo couldn't just calculate every move; it had to develop intuition through reinforcement learning.

RL has only grown more powerful:

Boston Dynamics' Backflipping Robots: Those viral videos of robots doing parkour? They're powered by RL algorithms that learned through millions of simulated attempts before executing a single real-world flip.

OpenAI's Dota 2 Bots: In 2019, OpenAI Five defeated world champion e-sports players at Dota 2—a complex strategy game requiring teamwork and adaptability. The bots trained by playing 180 years' worth of games... daily.

Reinforcement Learning for Characters: Nvidia is working on using RL for Physics-Based Character Animation. With adversarial reinforcement learning, physically simulated characters can be developed that automatically learn responsive behaviors in decades of years of training that take only days of human time.

The common thread?

None of these systems were explicitly programmed with solutions. They discovered strategies through trial and error—often finding approaches humans never considered. AI can learn to cook, clean, drive, write, create by practicing tasks millions of times.

The secret sauce behind this revolution? Game engines as AI gymnasiums. The tools powering your favorite games—Unity, Unreal Engine, O3DE, Godot, and others—are becoming training grounds for tomorrow's AI. Nvidia is building their own virtual engine, Isaac Sim. We'll likely create everything we need AI to do virtually, letting it practice in physics-enabled 3D environments according to properly designed reward functions.

Why build expensive real-world testing facilities when you can create perfect digital twins? Want to train a delivery robot? Drop it into a virtual neighborhood with realistic weather, traffic patterns, and the occasional surprise squirrel crossing its path.

These tools are increasingly accessible. Five years ago, building an RL system required a PhD. Today, high schoolers with gaming laptops are beginning to experiment with reinforcement learning using free tools and YouTube tutorials.

Getting started with RL

If you are already familiar with RL, feel free to shoot me a line, I am eager to learn as much as I can. If you are interested in learning RL yourself, (like I am endeavoring to), below are my suggestions to start.

1. Learn a game engine. Preferably several. There are a number to choose from. You can go with one of the big dogs like Unity or Unreal, or find one of the open source versions like Godot, or the Linux Foundation’s O3DE. Moving things in the virtual world will increasingly be a valuable skill.

        Here’s a RL agent course that I’m playing with for Godot:

   https://huggingface.co/learn/deep-rl-course/en/unitbonus3/godotrl

2. Use Cases. Just because you can use RL, doesn’t mean you actually know what to do with it. We will need to figure out what to teach AI, as much as the how. That’s why I also recommend designers and creatives play with LLM driven agents. There are a number of open source platforms like Menlo.ai, that allow you to experiment with models like R1, Lllama3, or if you have the API key Claude and Open AI. You can also play with a variety of models and agents on the AI open source playground Hugging Face. You can connect with me here.

https://menlo.ai/products/robotics/simulation

Too hard? Keep your eyes open. Even if the above sounds too complicated, hang in there. I’ve noticed that tools for AI are only getting better and more accessible UX. When voice integration becomes common place, expect things to move even faster. If you can’t do something now, keep an eye out for the next software or open source model on the horizon.

Good luck. Let me know how you make out. Watch this space. I’ll be updating as I learn more!

Nye Warburton is an educator, game developer and creative technologist. This essay was written by recording improvisational sessions with Otter.ai, and using the output as data for a series of essay generations in Claude Sonnet 3.7. Images created with Leonardo.ai. Editing was done with human labor. For more information visit https://nyewarburton.com

"Cartooning is for people who can't quite draw and can't quite write. You combine the two half-talents and come up with a career." — Matt Groening

Using AI for art is an exploration, not an act of creation.

You do not create with AI, you search --- and zero-in on an idea. Hopefully, you do this, while leaving yourself open to the discovery of new ideas along the way. To use AI for art is to explore infinite possibility. To find your way, you must learn to map the latent space* you are searching.*

What is Latent Space?

Imagine a vast landscape where every possible idea exists somewhere as a point on a map. This is "latent space" – the linear algebraic territory that AI navigates when creating images, text, or other work. It's where new mixtures of established concepts live before someone brings them to life.

Today's AI tools force us to navigate this landscape using only text commands. This writing of what we wish to have AI generate, termed “prompting,” is the clumsiest the UX for using AI will ever be. It's like trying to find a location by shouting directions out the window. The evolution of these tools are inevitable.

What if artists could explore this latent space visually?

What if we could triangulate where we want to go, and calculate ever finer approaches to the ideas we wish to explore?

The Triangle: Mapping Artistic Judgment

Latent space might be billions of multi-vector possibilities, but in essence, it is just a massive space to explore. We could simplify the concept to three vectors and a small triangular area.

Bear_Rabbit_Robot is a demonstration of this approach for artists. Instead of relying on words alone, it uses a simple triangle to map creative possibilities – giving artists a visual way to explore the spaces between concepts.

The project places three character types at the corners of a triangle:

• Robot at the top

• Bear at the bottom left

• Rabbit at the bottom right

Each point inside this triangle represents a unique blend of these three concepts. By selecting 21 specific points in this triangle, we created a collection of characters that shows how these elements can combine in different ways.

What makes this approach powerful isn't just the mathematics of blending. It's that each point represents an artistic judgment about what combination "feels right." When we place a character halfway between Robot and Bear with minimal Rabbit influence, we're making a statement about what we consider a harmonious blend of those elements.

Each position in the triangle represents a creative decision.

It’s mapping the algorithmic blend of the AI model’s latent space, to the artistic instinct that dictates what we, as humans, would determine to be the blend between the elements. This is merely 21 images with three vectors of concepts. Imagine the control of this thinking blending 100’s of thousands of ideas together.

In navigating latent space, we can draw inspiration from the sextant—the tool sailors used to find their way by measuring the angles between stars. Our triangle method works the same way: by establishing three clear reference points (Robot, Bear, and Rabbit), we create a map that helps us navigate creative possibilities. We don't need complex math to understand that moving between these points creates new combinations, just as sailors didn't need to understand astronomy to find their position at sea.

While data science typically focuses on solving problems, artists can borrow these approaches for a different purpose: discovery. The tools mathematicians use to find patterns—like mapping distributions or finding relationships between variables—can help us explore creative territories beyond what we could imagine on our own.

Your Sensibility

You're a DJ with three turntables.

One plays pure "Surreal" beats, another drops "Minimalist" tracks, and the third spins "Baroque" melodies. Your magic happens when you blend these sounds – not by random mixing, but through your unique sense of what sounds amazing together.

That's the concept. Latent space can become your creative mixing board.

Let’s use Rabbit_Robot, with the slightest hint of Bear. This isn't some soulless formula – I chose the instance to use in that spot.

Is this a precision-engineered bunny with just enough bear-like sturdiness to give it presence? Or perhaps a lightning-quick mechanical being with a touch of wilderness in its circuitry? Does it feel right to you or a certain audience? Who makes the judgement about what a Robot-Rabbit looks like and how much is just a “dash of Bear?”

As AI becomes more integrated into creative workflows, your greatest advantage will be your unique artistic sensibility – your personal judgment about what combinations feel right. The triangle method doesn't replace this judgment; it gives it a map where it can be expressed and taught. I am sure there will be more of these kinds of frameworks nearing infinite complexity.

As AI tools evolve, the artists who thrive won't be those with the most technical knowledge – they'll be the ones who can most clearly map their creative instincts. Think of it like teaching a new assistant: You wouldn't just give random orders; you'd help them understand your taste and preferences.

User experience design has already given us powerful tools for creative exploration – scroll bars, toggles, bezier-curves, and eye droppers became the iconic controls of the previous generation of digital art.

But mapping latent space will usher in an entirely new breed of tools that let artists blend and morph through their AI-powered creations with the same intuitive ease. The triangle is just the beginning – a simple demonstration of what's possible.

Your Turn to Map Creative Space

Your artistic sensibility – the judgment that says "this combination works but that one doesn't" – is your superpower in the AI age. The mathematics doesn't replace this judgment; it amplifies it by giving you a playground where your creative instincts can run wild in organized ways. No matter how complex the system for searching might become, it will always be driven by your instinct to find the next great idea.

So grab your metaphorical sextant and start mapping. The technology industry is waiting for the artists to show them what’s possible.

Place your three favorite concepts at the corners of a triangle and just start. What undiscovered ideas live at the uncharted coordinates? And maybe ask, what happens when you blend concepts that nobody thought to combine before?

I am looking forward to seeing what you discover.

Nye Warburton is a creative technologist and educator from Savannah, Georgia. The Bear_Rabbit_Robot experiment was imagined through improvisational concepting with Deep-Seek R1 . Imagery was created using Leonardo.ai and Stable Diffusion. Writing was mainly human labor, with editing assistance from Claude Sonnet 4.5. For more information visit https://nyewarburton.com

TLDR: What if students viewed themselves as citizens rather than consumers of education?

The Age of the Consumer

Jeff Bezos built Amazon on an almost obsessive focus: give customers exactly what they want, when they want it.

This isn't just a business – it's a logistical empire built on precision. Every click, every purchase, every moment you spend on Amazon feeds into algorithms designed to predict and fulfill your desires with increasing accuracy. It's a testament to capitalism's relentless drive to optimize the customer experience.

But let's flip this "customer is always right" mindset to another modality.

Military training.

Picture a drill sergeant saying, "Private, I can see you are tired, so we'll skip the obstacle course today."

Training would be pointless. Some domains require challenge, discomfort, and growth that have nothing to do with customer satisfaction.

Education sits at this crossroads. Clearly we aren't army bootcamps, however, we have an obligation to outcomes none-the-less. Obligations, which increasingly might be at odds, with treating students as consumers.

My concern is that real learning often demands something very different from customer service.

The Science of Learning

There is a tax on knowledge. Learning must be earned.

Students who understand that learning is supposed to be a struggle actually develop greater resilience and take on bigger challenges. In the educational STEM world, this is termed "productive struggle." According to Angela Duckworth's book, this is called "Grit" – it's not about how many times you win, but how many times you fail and get back up. According to “Make It Stick: The Science of Successful Learning," when we simply reread material or passively consume information, we don't truly internalize it. It's in the struggle, in the testing, in the retrieval of information, that real learning happens. It's like trying to build muscle by lifting feather-weight dumbbells – the absence of challenge means absence of growth.

But this creates a paradox: How do you sell struggle?

When students can jump on RateMyProfessor to complain about challenging coursework, we risk creating an educational system that prioritizes comfort over effectiveness. Is our culture of instant gratification actually diminishing our ability to handle intellectual challenges – or worse, our emotional capacity to endure testing and failure?

The Citizenship Model

What if we frame education as a fundamental human right, but those rights come with responsibilities?

The things you put into your mind are like food for your brain. If you constantly opt for the mental equivalent of fast food – passively scrolling through TikTok, letting algorithms feed you "bite-sized content" – your intellectual life will head in one direction. But if you take the time to "prepare proper meals" – engaging with challenging material, wrestling with difficult concepts, contributing to your learning community – your mind develops in a fundamentally different way.

Creativity is painful.

It's overcoming the pain of failure that builds the ability to solve harder problems.

If any one person dealt with this pain alone, it would break them. That’s why when you are learning to be creative, your community becomes your support network. The more you put into that community, the more strength and support you get back. It’s not just about finding your voice, it’s about finding the community of people that your voice matters to.

True learning isn't just about engagement – it's about citizenship. It's about actively shaping your educational environment and showing solidarity with your learning community. When students view themselves as a proud citizen rather than consumer of education, something remarkable happens. The focus shifts from "What am I getting for my money?" to "I can’t wait to be a part of it."

• A consumer complains when service isn't perfect

• A citizen works to improve that service for everyone

• A consumer expects instant gratification

• A citizen invests in sustainable long-term development

• A consumer complains

• A citizen solves problems in their community

Education isn't about getting what you want – it's about becoming who you need to be.

And that transformation, like any worthwhile change, requires more than passive consumption. It requires active citizenship in your learning community, embracing the struggles that lead to growth, and contributing to something larger than yourself.

Nye Warburton is an educator and creative technologist from Savannah, Georgia. This essay was written with human labor and edited with Claude Sonnet 3.7. For more information visit https://nyewarburton.com.

Books

Grit: The Power of Passion and Perseverance by Angela Duckworth

https://angeladuckworth.com/grit-book/

Make it Stick: The Science of Successful Learning by Peter C. Brown, Henry L. Roediger III, and Mark A. McDaniel

https://www.makeitstick.com/

Articles

From Struggle to Success, New Research Provides Tips From Study on High-Achieving High School Students, Xiaodong Lin-Siegler and Ben Lovett

https://www.tc.columbia.edu/articles/2023/april/new-research-provides-tips-from-study-on-high-achieving-high-school-students/

How Students Benefit from Productive Struggle in STEAM Education

https://tinkrworks.com/blog/how-students-benefit-from-productive-struggle-in-education/

How to Explain Growth Mindset to Kids: Neuroplasticity Activities

https://biglifejournal.com/blogs/blog/teach-kids-growth-mindset-neuroplasticity-activities?srsltid=AfmBOorvMA3DB2cfGMsMD4KgBfFsbqrgBsLmWi_PanHRfFWwrn71dcXh

TLDR:* Your friendly neighborhood guide to becoming tomorrow's tech overlord!*

From AI-powered ego boosters to loyal robot minions and that pesky quest for digital immortality. (Ethics-Bypass Chip™ sold separately.)

Contents

• Introduction: The Antiheroes We Deserve

  • Chapter 1 / Fantastic Gadgets

  • Chapter 2 / Personalized Robots

  • Chapter 3 / Centralized Servers

• Conclusion : The Heroes We Need

Introduction: The Antiheroes We Deserve

If our cultural obsessions are any indication, humanity has officially entered its sympathetic super villain era. We’ve traded capes for hoodies, monologues for TED Talks, and secret lairs for Silicon Valley campuses. Walter White’s meticulous genius? Lex Luthor’s megalomaniacal philanthropy? Tony Stark’s “I-built-this-in-a-cave” swagger?

All have merged into a singular archetype: the tech bro with a messiah complex.

No need to hide it. You want to take over the world? Just do it - no regulation, no push back, paid off judges by the dozen - and the tools of the trade have never been easier!

The line between hero and villain has blurred into a gradient of charisma, wealth, and the relentless pursuit of legacy. But what happens when the tools of tomorrow***—AI, robots, blockchain—***are wielded not for the greater good, but to cement a new oligarchy of self-styled “visionaries”?

(Like a Stan Lee intro!)

Strap in, dear reader. The future is here, and it’s wearing a black turtleneck.

Chapter I. Fantastic Gadgets

Because Even Villains Need an App for That

Every super villain worth their salt needs a utility belt of dystopian toys. Today’s aspirational overlords skip the shark repellant and opt for AI-powered gadgets that promise convenience—and quietly harvest data to fuel their empires.

The Ego-Enhancer 9000™

Imagine AirPods, or wrap around stylish glasses, but instead of playing music, they whisper affirmations curated by your personal AI.

*“You’re not just disrupting industries—you’re redefining humanity’s destiny.”*

(Powered by ChatGPT-12)

This luxury item scans your calendar, emails, and biometrics to gaslight you into believing your 3 AM tweet-rants are visionary manifestos!

The NarcissiCam™

This facial-recognition glasses-cam livestreams your life to adoring subscribers (read: shareholders) while algorithmically editing out unflattering angles.

Why rule the world if you can’t monetize your morning smoothie routine?

The Ethics-Bypass Chip™

And are you tired of pesky moral quandaries slowing down your quest for market dominance? This neural implant generates airtight justifications for any decision.

Lay off 10,000 employees? “Streamlining for agility.”

Dump rocket waste in the ocean? “Sacrifices for interplanetary colonization.”

Buy now, and devices come preloaded with ESG buzzwords and a free subscription to Wired.

Chapter 02 Personalized Robots

Branded Smiles, Villainous Style

No super villain network is complete without an army of loyal minions. But forget henchmen in matching jumpsuits—today’s tycoons want robots that blend corporate cheer with personalized menace.

Enter VillainBots™: humanoid assistants clad in signature “Customer Obsession Smile,” but customizable with your logo (a biohazard symbol? A crypto token?). These bots are equal parts charm and threat. They’ll fetch your oat milk latte while discreetly scanning the café for antitrust regulators.

Customization options include:

• Voice Modulation: Choose between “Siri’s chill cousin” or “Skynet’s sassier sibling.”

• Loyalty Protocols: Programmed to laugh at your jokes, clap when you enter a room, and self-destruct if subpoenaed.

• Ethical Dampeners™: Guaranteed to never consider labor laws or ask why you need a fourth yacht.

But here’s the twist: These bots aren’t just servants—they’re spies. Each one feeds data back to your HQ, mapping vulnerabilities in competitors, governments, and even your inner circle.

The goal?

A world where loyalty is automated, dissent is algorithmically suppressed, and every interaction is a transaction.

Chapter 3. Centralized Servers

Immortality, One Bitcoin at a Time

Every super villain’s endgame is immortality—not through magic or gamma rays, but data. Enter the EgoCrypt™: a fortress of centralized servers running Bitcoin validators, AI models, and your digitized consciousness (patent pending).

Here’s the pitch: Why leave your legacy to chance when you can encode your brain into a blockchain? Your tweets, emails, and Zoom frowns are already stored in the cloud; now, for a mere $69 billion, an AI can simulate your voice, opinions, and hatred of taxes indefinitely. “You” will live forever as a CEO chatbot, haunting shareholder meetings long after your body is cryogenically frozen.

But the EgoCrypt’s real power is control. By monopolizing server farms, you can throttle competitors’ AI, manipulate crypto markets, and hold governments hostage with ransomware wrapped in a Terms of Service agreement. (“Your data will be restored if you acknowledge me as ‘Supreme Innovator’ in your national anthem.”)

But Wait … Where’s the catch? Doesn’t every super villain have a weakness?

Does this Death Star of happening have a single exhaust point to fire a torpedo into?

Centralization

Centralization is a single point of failure.

One hack, one power outage, one disgruntled intern with a USB drive, and your empire collapses into a meme.

Conclusion

The Hero We Need Is (Maybe) in the Comments Section

This is the part where a hopeful twist arrives—a reminder that heroes aren’t extinct, just decentralized. Imagine open-source gadgets that prioritize privacy over profit. Robots programmed to empower human creativity. Solar-powered server farms governed by sustainable community needs.

A world where “innovation” isn’t a euphemism for exploitation.

The tools of villainy are seductive, but they’re not inherently evil. What if we built networks that lifted instead of surveilled? What if instead of uploading our egos, we distributed human compassion?

Heroes won’t emerge from ivory towers or viral hype videos—they’ll come from collectives, cooperatives, and Gen Z anarchists making memes that actually mean something.

But perhaps— it’s just the Ethics-Bypass Chip™ Talking.

Sincerely yours,

—A recovering tech bro optimist

If you enjoy the work of myself and my robot minions. Please consider subscribing. Thanks for Reading. We’ll see you next time.

Nye Warburton is an educator who imagines a human-focused robot future. This essay was written over several improvisational sessions with Deep Seek and edited for #tone and #sarcasm with Claude Sonnet 3.5.

For more info visit : https://nyewarburton.com

The robots are coming.

Just like their cousin, the quad-copter drones before them, the robot dog movement is in full swing, and it’s only a matter of time before we all have them.

Now is the time for creatives to start playing with robotics.

Contents:

• The Everyday Roboticist

• Drones to RoboDogs

• RoboDogs to Androids

• What can we do with a Robot?

• Getting Started with Robotics

The Everyday Roboticist

Remember when creating a website meant wrestling with HTML and FTP? You may not, but I do.

Back then, embedding a QuickTime video on your GeoCities page could attract thousands of visitors simply because so few people had the technical skills to implement it. Today, anyone can create a super slick website in minutes using tools like WordPress or Squarespace.

A similar democratization is now happening in robotics, but it’s happening at 50 times the speed.

Robotics magic that was once the exclusive domain of PhD researchers at Stanford, is becoming accessible to creators, designers, and weekend hackers like me. The transformation mirrors the evolution of other technologies: from specialist tools to creative platforms that anyone can use.

Drones to RoboDogs

I first experienced this shift through quad-copter drones.

When I was in Los Angeles, I spent my days at a co-working space in Chinatown called "KleverDog Coworking." A few of us “entrepreneurial-artist types” starting flying drones for fun on Friday afternoons.

Starting with a $100 programmable drone, I learned about PID controllers (the mathematical magic that keeps drones stable), swapping plastic rotors and batteries, and the basics of flight control with a quad-copter.

And now, drones are everywhere. FPV drone racing is purely awesome – pilots becoming disembodied entities racing through the air at 90 mph, seeing through their drone's camera feed. Drone light shows paint the sky at major events, and aerial photography has become a mainstream creative medium. It’s hard to find a beach parking lot where a weekend enthusiast isn’t buzzing their quad-copter around.

We're seeing a similar revolution with robotic dogs.

Boston Dynamics' Spot, a yellow robot dog driven by industry-leading artificial intelligence, was a viral internet sensation. It and others like it have inspired a wave of more affordable alternatives. The Unitree GoPro2 is offering a programmable robot competitor at a fraction of the cost. Sony is offering a consumer robot dog called Aibo for around $3,000.

https://robostore.com/products/go2-pro-ai-quadruped-robot-dog?variant=41212102213702&country=US&currency=USD&utm_medium=product_sync&utm_source=google&utm_content=sag_organic&utm_campaign=sag_organic&gad_source=1&gclid=Cj0KCQiA7se8BhCAARIsAKnF3rxwNPucad3rkSN4zJgNJRcBQcj4RMXMzOTOhAb5paAliNmzqNE9A9caAp5MEALw_wcB

Jumping in myself, I recently bought a MechDog for $400! – less than the price of a gaming console. It's programmable using Scratch or Python, and while I'm a pretty “dog-crap coder,” AI assistants like Claude, or the IDE Windsurf with Codium, help me write what I need. It's amazingly cool, mind-blowing, and a sure fire vector of the future we are inventing.

The evolution from quad-copter drones to quadruped dogs represents a significant leap in complexity.

While drones master the challenge of stable flight through PID control, robotic dogs tackle the intricacies of walking using inverse kinematics – an “old” animation software trick of calculating joint angles to achieve natural movement. They learn different gaits (walking, trotting, galloping), maintain balance on uneven terrain, and interact with their environment in increasingly sophisticated ways.

The tools for developing these robots are becoming more accessible too. Using Gazebo, a virtual environment simulator from the Open Robotics foundation, I can download virtual models of robots like Boston Dynamics' Spot, and train them in virtual spaces.

https://mikelikesrobots.github.io/blog/spot-sdk-intro/

Spot might be millions of dollars of MIT quality research, but the SDK libraries and training of spot is free and open with anyone with access to github and a little bit of Claude-powered python knowledge. (aka, me)

RoboDogs to Androids

Dressed in a sparkling leather jacket, NVIDIA's CEO Jensen Huang recently announced their Cosmos platform, which aims to democratize physical AI development. Cosmos is designed to provide accessible digital tooling for developers to train and test a variety of robot models. It’s targeted at the industrial sector, providing all of the data and compute necessary for robot labor to understand the real world.

"The ChatGPT moment for general robotics is just around the corner."

Jensen Huang, Nvidia -- CES 2025.

https://www.nvidia.com/en-us/ai/cosmos/

This push from major tech companies is being matched by rapid evolution in the open-source community. Hugging Face, known as a hub for AI models, now hosts educational robotics projects. The Robot Operating System (ROS), a collection out-of-the-box frameworks that handles complex robotics underpinnings, allows developers to focus on building functional robotics rather than wrestling with low-level control systems.

This convergence of affordable hardware and accessible software tools marks the beginning of a personal robotics revolution, much like how affordable PCs and accessible programming tools sparked the personal computing revolution. The focus on quadruped robots isn't just about making cool pets – it's a crucial step toward humanoid robots.

As Huang points out, our world is built for “human-sized interaction.” Doorways, stairs, tools, and furniture are all designed for human bodies. Mastering four-legged movement provides the foundation for the even more complex challenge of bipedal (two-legged) robotics.

What can we do with a Robot?

The creative opportunities are already emerging.

Digital artist Beeple recently created an installation featuring Spot robots with 3D-printed heads of himself, blending robotics with contemporary art. Chinese drone shows have evolved into spectacular aerial ballets, with full sparkling dragons that undulate across the sky. These examples merely hint at the vast potential for artists, designers, and creators to shape the future of robotics.

As LLM powered agents take the digital world tasks from us, the cheap hardware robots will certainly take the real world ones. Cleaning, cooking, delivering, monitoring our day to day lives is a near certainty. More than likely … building, constructing, surgery, and massage therapy?!?!

Research now reveals that having robots in the house helps with loneliness and depression for older adults. (Though I might ask if we are actually fixing the problem by throwing robots at it, or should we just double down on more human connections?)

https://pmc.ncbi.nlm.nih.gov/articles/PMC9629053/

Anyway - My sum up is this:

Don't let technical constraints hold you back.

The tools are becoming more accessible every day, and your creative vision is exactly what the field needs. Start small – experiment with a programmable drone or an affordable robot dog. Join online communities sharing open-source robotics projects. The barriers to entry have never been lower, and the potential for creative innovation has never been higher.

The future of robotics belongs to those who can imagine it, not just those who can engineer it. The question isn't whether robotics will become democratized, but what we'll create when it does.

And if my experience with a $400 robot dog is any indication, we're in for an exciting ride.

Getting Started with Robotics

Keep in mind, I am a NooB myself, but so is most of the world!

Based on my experiments and research, here are some ways to get going building your own robot best friend.

1. Start Virtually

   Before buying any hardware, start with simulation.

   There are drone simulations all over the place, many are downloadable from Steam. If you are savvy with a game engine, maybe do some research on virtual robotics kits --- For Example, Cleverlike Studios has developed a virtual robot training course for the Unreal Engine.

   https://www.cleverlike.com/robotics

2. Quad-Copter Drones

   Small programmable drones are perfect for learning the basics. They're relatively cheap (under $100 for starter models), and you can program them using Python.

   You'll learn about PID controllers, pathfinding algorithms, and real-world physics – If you really get bitten by the bug, you can design and develop drone shows, go deeper into drones for survey work, or (gulp) the military.

   I’ve been really impressed with the work of Drone Blocks. They provide educational kits for classrooms, and simple starter drone packs for learning.

   https://droneblocks.io/

3. Robot Dogs

   I just purchased a MechDog ($400), but if you have the wallet and are ambitious, I might recommend the ROS Pug ($1300) as an entry points.

   The ROSPug come with the new Jetson Nano boards – NVIDIA's powerful AI computers which should undoubtedly make an obvious difference. Imagine creating an interactive art installation where the robot responds to your movement, or designing a game where virtual and physical robots interact.

https://www.hiwonder.com/products/mechdog?variant=41158973161559&srsltid=AfmBOoqYncHIHLRTdcg91Z-bADcMlO0sR09M5_z7M31ivZyqNpbtpivT

https://ozrobotics.com/shop/rospug-quadruped-bionic-robot-dog-powered-by-jetson-nano-ros-open-source-python-programming/?srsltid=AfmBOoo_eSDP_HLNDMXOAqz5nv7ECwf7rve6-fd9uOWUGDhu8nhfwfZM

4. Tap into Open Source!

Platforms like Hugging Face aren't just for AI models anymore – they're about to become the hub for open robotics projects too. Browse through the available models, fork a project that interests you, and start experimenting.

LeRobot is a brand new community dedicated to sharing robots for education.

https://huggingface.co/lerobot

If you liked this essay, please consider subscribing and sharing. Thanks for reading!

Nye Warburton is an educator and who likes to imagine a positive robot future. This essay with written with human passion in collaboration with Claude Sonnet 3.5. Visit https://nyewarburton.com

The gaming industry is undergoing a radical systemic transformation.

My hypothesis: Individual game creators armed with AI tools, open-source software, and access to decentralized networks will compete effectively with large traditional game studios.

Contents:

• Introduction

  • 1. The Traditional Game Business Model

  • 2. The Impact of Networks

  • 3. The Rise of User Generated Content

  • 4. Three Disruptive Forces

  • 5. Artificial Intelligence

  • 6. Advice for New Developers

• Conclusion

Introduction

I believe the video game industry is undergoing a profound transformation, reshaping how games are created, distributed, and experienced. This isn’t just a matter of layoffs and restructuring.

Computing is being upended by not just AI, but also the reimagining of networks and fractional ownership.

To my students - as aspiring game developers and enthusiasts, understanding these changes is crucial for navigating the future landscape of interactive entertainment. Those who adapt and predict where the industry goes will be at a distinct advantage while legacy players will need to adapt to catch up.

1. The Traditional Game Business Model

The video game industry has historically operated on a straightforward model:

Large companies invest substantial capital to produce games, which consumers purchase. This generates revenue that funds future projects.

Crucially, even after purchase, intellectual property rights remain with the game company—consumers buy a license to play, not ownership of the game's content or characters.

This model has enabled the growth of gaming giants and the creation of iconic franchises. The long-term value lies in the intellectual property itself, not just individual game sales.

However, technological advances and evolving consumer expectations are increasingly challenging this foundation.

2. The Impact of Networks

Internet connectivity has fundamentally altered the gaming landscape.

Network game systems have matured into new dynamics to both game development and player interaction. These networks, ranging from social platforms to interconnected gaming ecosystems, have enabled the rise of massive multiplayer online games and live service models.(1) Networked companies operate more like a SaaS.

Companies not only develop games but also maintain extensive server infrastructures to support online play. A game purchase often includes access to evolving multiplayer experiences, regular updates, and ongoing support.

However, this networked model has also increased the complexity and cost of game development and maintenance, requiring companies to factor in long-term server costs, continuous content creation, and community management.(2)

3. The Rise of User-Generated Content

User-generated content (UGC) represents one of the most significant shifts in recent years. Games like Minecraft and Roblox have demonstrated the immense potential of empowering players to become creators within game ecosystems. This trend has blurred the lines between developer and player, creating vibrant communities and extending the lifespan of games far beyond what was previously possible.(3)

The UGC model has proven particularly effective to drive growth for companies that have successfully implemented it. However, UGC has not demonstrated that it is an effective monetization strategy. (4)

Roblox, for instance, has built a significant portion of its business model around user-created content and experiences. By allowing “developers” (often no older that 13!) to create and monetize games within their ecosystem, Roblox has fostered a self-sustaining content creation engine while taking a percentage of the revenue generated through their Robux virtual currency system.

Despite Roblox's massive scale with over 380 million monthly users and nearly $4 billion in annual revenue, the platform struggles with profitability due to its high cost structure. The company faces a fundamental challenge where growth often leads to higher costs - As game industry expert Matthew Ball has succinctly put in his writing - Roblox generates significant cash flow due to stock-based compensation practices, its core business model currently spends about $138 for every $100 in revenue.(5)

These challenges are also evident in Fortnite, (6) and other massive live service models. Essentially this means, the game industry is without a capitalist-centric business model. Most large technology firms are looking to similar revenue shares, as opposed to charging for monthly SaaS based models.

The meteoric rise of gaming during the COVID Pandemic era may have shown fantastical revenue, but returning to normal consumption has revealed structural issues with the business models in general. (7)

Couple this with three major technical trends, and the democratization of the development pipeline, we are on the cusp of something incredibly huge.

4. Three Disruptive Forces

Before we get to Artificial Intelligence specifically, I wish to cover three emerging trends that promise radical disruption to the gaming landscape:

Disruption 1 - Open Source

The rise of high-quality, free, and open-source tools like Blender for 3D modeling and the Godot game engine is democratizing game development by reducing barriers to entry for aspiring developers. (8) But open source is effecting elements of the gaming industry beyond software.

Industry innovator Valve exemplifies this trend with the Steam Deck, which demonstrates the potential of open-source technology in gaming hardware. Unlike traditional gaming consoles that rely heavily on proprietary systems, Steam Deck is built on Linux and a variety of open source technologies. (9)

This success could signal a significant shift in gaming's future, as Valve has shown that investing in open-source infrastructure can create experiences rivaling proprietary systems. The model is particularly powerful because the integration of Proton solved one of Linux gaming's biggest challenges—Windows game compatibility.(10)

While this approach could inspire other companies to embrace open-source solutions and lead to a more diverse and innovative gaming ecosystem, challenges remain. Open-source projects often struggle with monetization (11) and make it difficult for companies to maintain exclusive intellectual property rights.

Disruption 2 - Blockchain (Decentralized Networks)

While blockchain technology and cryptocurrencies have faced legitimate concerns about misuse and operate in sometimes “ambiguous regulatory territory,” (read: crime) they show tremendous potential for introducing new economic models to gaming. (12)

The future of gaming content creation mirrors the evolution of bedtime stories—a shift from rigid, controlled narratives to fluid, interoperable experiences. Just as a parent can mix Spider-Man with Darth Maul in a bedtime tale, blockchain technology could enable gamers to freely combine and trade user-generated content across different gaming environments, breaking down the traditional barriers of copyright and corporate control that have restricted creative freedom in gaming.

The convergence of accessible game development tools with blockchain-based ownership systems could democratize content creation in unprecedented ways. While platforms like Roblox have begun this transformation, decentralization takes it further by enabling true ownership and interoperability of digital assets. (13)

Consider the months spent leveling up a character, collecting weapons, and customizing your experience in a game. Players invest significant time and energy into these digital assets—investments that deserve real ownership rights rather than temporary licenses that can be revoked at any time.

Disruption 3 - Affordable Hardware

The decreasing cost of powerful computing hardware, coupled with innovations like 3D printing and affordable microcontrollers (Arduino, Raspberry Pi), is enabling unprecedented access to hardware-based projects. This democratization extends beyond gaming into robotics and automation, creating an emerging ecosystem of accessible technology.(14)

I parallel this to the 1970s Homebrew Computer Club. Just as that group helped spark the personal computing revolution through accessible technology, today's hardware democratization allows enthusiasts to build sophisticated systems at home for the price of a gaming PC. These distributed computing networks enable complex automation systems that were previously available only to well-funded organizations.

This accessibility, combined with low-code platforms, is creating a new class of "everyday roboticist." There will be many non-technical individuals who gain access to powerful AI capabilities through affordable hardware. Nvidia’s Jetson Orin Nano, for example, retails for $249 dollars! (15)

The skills developed in this space naturally complement game development—3D modeling, real-time simulation, and engine development apply equally to virtual worlds and physical ones. This convergence suggests that as we democratize virtual world creation, we simultaneously enable innovation in practical, real-world applications. (16)

However, like open-source software, hardware democratization faces challenges with traditional business models. While innovation flourishes, sustainable monetization remains difficult, pushing creators to explore new distribution and revenue models.

These disruptive forces—open source software, decentralized technology, and affordable hardware—are challenging the traditional centralized model of game development and distribution.

But there's an even more transformative force on the horizon, one that promises to accelerate and amplify all of these changes…

5. Artificial Intelligence

Beyond the now-familiar AI tools for generating images, audio, and video, development itself is being transformed by AI coding assistants like Codium and Microsoft's Copilot. (I did a prototype here.) With major game engines like Unreal and Unity inevitably incorporating these systems, we're approaching a future where developers will primarily communicate their creative vision to AI agents that handle the technical implementation.(17)

But the explosive innovation will be the decentralization of AI. AI capabilities will become more localized—running efficiently on personal devices rather than requiring cloud infrastructure.

A particularly promising development in this space is the emergence of open-source projects like EXO, one of GitHub's most popular recent repositories. EXO is democratizing access to AI computing power by allowing everyday devices to work together as AI processing clusters.(18)

This approach parallels how the Steam Deck demonstrated the potential of open-source gaming hardware. EXO and similar projects show how ordinary devices—phones, tablets, and laptops—can be unified into powerful AI processing clusters without requiring expensive specialized hardware. With these tools freely available on GitHub, we could be approaching a cambrian explosion of decentralized development.

This technology could revolutionize game development by enabling individual creators and small studios to run sophisticated AI models locally. Teams could handle content generation, character behavior, and dynamic storytelling using their existing devices, without relying on expensive GPUs or cloud services. (20)

The implications are profound: independent developers may soon create experiences that previously required the resources of large studios.

6. Advice for Aspiring Developers

Ultimately, this is just a hypothesis. As of January 2025, blockchain gaming has yet to find a real working title, and AI is still finding it’s footing as a viable development tool.

However, the gaming industry's future workplace will likely look radically different from today's landscape. We're moving from a model dominated by large, centralized companies toward a more decentralized, network-based sharing economy.

For those looking to build a career in this rapidly evolving industry, several key strategies emerge:

1. Embrace emerging technologies: Stay informed about developments in AI, blockchain networks, AR/XR and other cutting-edge technologies. Understanding these tools will be crucial for innovation in game development.

2. Master IP and licensing: As the industry moves towards more decentralized models, understanding how to protect and monetize your intellectual property will be essential.

3. Engage with network economies: Participate in online marketplaces, open-source projects, and community-driven platforms. These will be the new centers of opportunity in the content and gaming world. DYOR - many blockchain projects are still experimental and not something you should invest significant amounts into.

4. Develop a diverse skill set: The lines between different roles in game development are blurring. Being able to work across disciplines – from coding to art to community management – will be increasingly valuable.

5. Prioritize data protection: As more value moves into digital realms, protecting your personal data and digital assets will become increasingly important.

6. Stay adaptable! Cultivate a mindset of continuous learning and adaptation. The only certainty in this new landscape is constant change.

Conclusion

The video game industry is changing rapidly - today. Layoffs, AI Tooling, and the emergence of experimental networks are just the start.

The traditional models that have dominated for decades are giving way to more open, decentralized, and community-driven sharing approaches. While this shift brings challenges – particularly for established players in the industry – it also opens up unprecedented opportunities for innovation and creativity.

For those willing to embrace these changes, the future of gaming promises to be an exciting frontier. It's a future where the lines between player and creator blur, where small teams can create experiences that rival those of major studios, and where new forms of value creation and distribution become possible.

Keep in mind, this is just a guess. Do your own research!

But one thing for sure:

The future of gaming is not just about playing – it's about creating, sharing, and reimagining what's possible in a networked, generative future.

If you wish to support my work, please consider subscribing and sharing. This essay has also been minted as a limited collectible. Thanks for reading.

Nye Warburton is a creative technologist and educator who runs generative experiments in the 9th Dimension. This essay hypothesis was adapted from a number of conversations, interactions, and lectures he has had over the last year.

It was edited and co-written with Claude Sonnet 3.5, researched with Perplexity, and finalized with a RAG enhanced version of Llama 3, running locally with the markdown software Obsidian.

For more information visit https://nyewarburton.com

Notes and Links:

1.Networked game systems

https://en.wikipedia.org/wiki/Games_as_a_service

2.Expense of game servers

https://www.riotgames.com/en/news/2024-rioter-update

https://stlpartners.com/articles/consumer/whats-the-problem-with-cloud-gaming/

3.User Generated Content

https://en.wikipedia.org/wiki/The_Wealth_of_Networks

4.Roblox Robux

https://www.roblox.com/upgrades/robux

5.Roblox Analysis by Matthew Ball

https://www.matthewball.co/all/roblox2024

6.Epic and The Metaverse by Matthew Ball

https://www.amazon.com/Metaverse-How-Will-Revolutionize-Everything/dp/1324092033

https://store.epicgames.com/en-US/p/fortnite

7.Covid and the Game Industry

https://www.gamesindustry.biz/cheap-money-and-bad-bets-how-the-games-industry-turned-pandemic-success-into-disaster

8.Open Source Game Development

https://godotengine.org/

https://opensource.com/resources/what-open-gaming

9.Valve Steam Deck

https://store.steampowered.com/steamdeck/

10.Open-Source Technologies That Made the Steam Deck Possible

https://www.makeuseof.com/technologies-that-made-steam-deck-possible/

11.Open Source Monetization Problems

https://www.amazon.com/Working-Public-Making-Maintenance-Software/dp/0578675862

12. Blockchain Gaming - Unreal Infrastructure for Web3 Gaming

https://github.com/G7DAO/web3.unreal

(Read: Crime)

https://www.amazon.com/Going-Infinite-Rise-Fall-Tycoon/dp/1324074337

13.Interoperable Assets and Intellectual Property

https://www.story.foundation/

14.Accessible Hardware

https://developer.nvidia.com/buy-jetson

https://www.robotshop.com/products/hiwonder-hiwonder-puppypi-pro-quadruped-robot-with-ai-vision-powered-by-raspberry-pi-5-ros-open-source-robot-dog-ultimate-kit-with-raspberry-pi-5-4gb?gad_source=1&gclid=CjwKCAiAm-67BhBlEiwAEVftNpzUMcvwBbBT1FILuWSyAfTTDxvBMPsGYRzGlDs7iRJ8aE7DuhWTfxoCnXgQAvD_BwE

15.Low Code Automation Platforms

https://n8n.io/

https://www.zoho.com/creator/lp/low-code-app-creation-development-platform.html?campaignid=14676304775&adgroup=128153232195&keyword=low%20code%20automation&network=g&device=c&matchtype=e&placement=&adposition=&creative=546578646926&gad_source=1&gclid=CjwKCAiAm-67BhBlEiwAEVftNq7iPaxqz8AZvhsH_vtYIzyp9iMkkDXkfyAukwYB2PbJad52GeKVcBoCj4UQAvD_BwE

16.Robotics and Simulations in Game Engines

https://o3de.org/industries/robotics-and-simulations/

https://arxiv.org/html/2302.01672v6

17.Agent Driven Development

https://codeium.com/windsurf

18. Localized AI Clusters - Exo

https://github.com/exo-explore/exo

20.The Generative AI Revolution in Games

https://a16z.com/the-generative-ai-revolution-in-games/

TLDR: AI science might reveal the secret to innovation: Stop Obsessing Over Objectives.

The Objective-Driven World

We're obsessed with objectives.

From the moment we enter school, we're taught to set goals, make plans, and work systematically toward achieving them. Get good grades, land a prestigious job, climb the corporate ladder, buy a house, start a family – our lives become a series of check-boxes waiting to be ticked off.

This objective-driven thinking is so deeply ingrained in our culture that we've built it into our artificial intelligence systems, where "objective functions" guide machines toward specific, predefined goals.

For most cases, it works wonderfully – especially for straightforward, well-defined tasks.

Want to become a certified accountant? There's a clear path for that. Looking to run a marathon? You can follow a structured training program.

These pursuits, with their established pathways and clear metrics for success, are perfect candidates for objective thinking. We know how to get there; it's simply about applying the energy, time, and drive to accomplish it.

The Creative Paradox

But here's where things get interesting – and paradoxical. Research by AI professors Kenneth Stanley and Joel Lehman, detailed in their book "Why Greatness Cannot Be Planned," reveals a fascinating truth:

The more ambitious or innovative your goal, the less likely you are to achieve it through direct, objective-driven pursuit.

Their work with an AI platform called Picbreeder, which allowed users to "breed" images algorithmically, led to an unexpected discovery. The most interesting and innovative results came not from users who had specific targets in mind, but from those who followed their curiosity and aesthetic instincts. In short, unplanned random discovery and curiosity driven remix create the best results.

We see this pattern often throughout history, where innovators discovered ideas.

Banksy revolutionized the art world with his template-style graffiti – a technique born from the need to evade the police. Spielberg invented a revolutionary POV horror camera style because the mechanical shark wasn't ready during Jaws filming. Bill Walsh created the "West Coast offense" not to revolutionize football, but simply to stay competitive.

From penicillin to Slack, and 1000s of other inventions, as John Lennon wisely noted:

"Life is what happens when you're busy making other plans."

The Power of Novelty and Play

So if objectives don't drive great innovations, how do we foster transformative ideas?

Enter "non-objective thinking."

Instead of fixating on specific end goals, non-objective thinking emphasizes the pursuit of novelty, curiosity, and play. It's about asking "What's interesting?" rather than "What's useful?" This approach combines human taste with serendipity – deliberately cultivating space for unexpected discoveries.

The authors explain with an experiment with a robot learning to walk in a digital environment. When trained to reach a specific destination in a maze, it would often get stuck. If the end of the maze is your objective, it makes sense to move directly towards it, but often this leads into walls!

However, when trained non-objectively, (to simply explore novel movements) it not only learned to walk more effectively but developed more adaptable locomotion skills. The robot discovered that random exploration was far more effective than pursuing an objective it couldn't comprehend. If you’ve observed a child learning to walk, they wiggle kick and precariously balance as they figure it out.

Think of jazz versus classical music. Classical musicians follow a precise score toward a predetermined outcome. Jazz musicians follow their intuition and respond to each other in the moment, often creating something more innovative than anything they could have planned. While jazz musicians work within constraints, their play is experimental and sometimes uncomfortable.

The real power of non-objective thinking lies in its ability to generate what the researchers call "stepping stones." You aren’t looking for a destination, but simply a place to keep moving in new directions. Each discovery opens new possibilities, creating a branching tree of opportunities rather than a linear path. A project's success isn't measured by its immediate impact, but by its ability to catalyze more ideas and possibilities.

This explains why diversity of thought often yields better results than consensus-driven thinking. When everyone works toward the same predefined goal, they tend to converge on similar solutions. When people are free to explore their curiosity, they discover entirely new territories.

Here's the beautiful paradox of non-objective thinking:

You can achieve amazing things; you just can't predict exactly what they'll be.

Just Be

Does this mean we should abandon all goals or structure?

Society will continue to build educational standards, target ideal crime rates, and set quarterly profit objectives because we don't know how to function otherwise. But perhaps we should question whether these metrics actually mean anything beyond motivating action.

Living in a world that increasingly demands innovation and creative problem-solving, perhaps the best strategy is to cultivate curiosity, embrace uncertainty, and trust that following what genuinely interests us will lead to more valuable discoveries than doggedly pursuing predetermined objectives.

The next time you feel stuck or frustrated with your progress, consider loosening your grip on the objective and instead ask yourself:

"What here is interesting?"

"Is this awesome?"

And my favorite... "Is it fun?"

You might find that by letting go of the destination, you discover something even better than what you were originally seeking.

This exploration is based on "Why Greatness Cannot Be Planned" by Kenneth Stanley and Joel Lehman – my favorite book of the year and one I highly recommend. The Amazon link is below if you wish to read it yourself!

Thanks for reading.​​​​​​​​​​​​​​​​

https://www.amazon.com/Why-Greatness-Cannot-Planned-Objective/dp/3319155237

Nye Warburton is a systems designer who builds generative experiments in the 9th dimension. This essay post was largely written with human labor with editing from Claude Sonnet 3.5. More info: https://nyewarburton.com

Hold on, it's pretty nuts.

My Prototype:

Prototstar* Prototype built in Phaser.js using Windsurf IDE/Cascade Agent, powered by Codium and Claude Sonet 3.5 from Anthropic.*

Contents:

• Can I build a game with AI?

• Coding with Windsurf

• From Concepting to Functional Prototype

• Reality Check

• Lessons Learned

Can I build a game with AI?

Classes ended and I turned my attention to some play time. Everyone is considering the why and how of AI. I decided to make a game with it - something playable and fun, a real working prototype.

I wanted to use AI to create gameplay, logic, and code. Not just prompting for haphazard code, but reflecting the ideas I wanted to create and test. I've been making all sorts of game prototypes using Claude's programming ability. It's amazing how 20 minutes of chatting can produce a simple 3D scene.

But to make a game you need something more robust - a project I could edit in an IDE with proper structure and architecture. So I started imagining a top-down space shooter and began a holiday AI-enhanced dev process.

Coding with Windsurf

I stumbled on Windsurf, an IDE that elevates AI from a simple code generator to "a true development partner." Through its “Codium” system and “Cascade” agent, it creates an environment where AI actively participates in development, generating code and file structures in real-time within the IDE itself.

In English, it "autocompletes" your code while you prompt it on the side margin. At the way back it’s powered by Claude Sonnet 3.5, which is what I use for text generation and prototypes.

https://codeium.com/windsurf

When you find your rhythm with Windsurf, it actually does feel like catching a ride – the AI writes code for individual files, making strategic guesses about what to do next.

For example - I might have said something like :

"Use the arrow keys to create a truck controller. Have the truck be drive-able, with forward arrow accelerating to a maximum speed, and the side arrows rotating the direction."

It would “think” with those little dots going back and forth…

Then, tell me it would build a movement controller, develop a state machine, and then build the physics. And it did it! You could watch it explain what it was working on, and like magic, watch the code being developed and commented. The most fun was when it said things like:

“Ah, I see the problem. Let’s fix it in the file.”

The feel of the game play was sometimes spot-on. Sometimes it was a disaster. It's important to have something in mind or be willing to let it take its own direction. Sometimes it really is like holding on and being pulled along almost out of control.

Unlike traditional tools that require copying and pasting code snippets, this integrated approach takes a more improvisational path with calculated-risk prompt asking. The refinement and continuous communication with an AI that rapidly forgets dependencies is the real challenge.

From Concept to Functional Prototype

To imagine Protostar - I gave myself a design period with Miro first. Using Leonardo.ai for images and consulting with Claude often, I developed concepts about space, aliens, and fun.

I spent about 90 minutes crafting a detailed prompt with Claude, which became my design document - outlining everything from entity specifications to movement systems and screen layout.

What happened next was remarkable.

Within hours, I had a working prototype that exceeded expectations. The game featured three planets orbiting a sun, a sophisticated energy management system based on solar values, and even a basic dialogue tree for alien interactions. The speed at which game mechanics came together was mind-blowing. This kind of prototype would typically take weeks to develop.

However, this rapid development created significant technical debt. The AI would sometimes rewrite entire sections of code, potentially breaking existing functionality. Version control became essential - when every prompt could go off the rails, you need the ability to roll back.

I kept a running document with entities, prompts, numbers, and thoughts. For example, the ship's power supply was 1000 one moment, then rewritten to 100 when updating the UI! I would personally write comments in addition to the the code, and would parse through it after changes. The better I knew the code, the more specific I could be about what shouldn't be touched.

Control came through clear communication and well-documented prompts, not endless small fixes. It's about communicating the larger system and giving enough detail for individual components to be functional.

The Reality Check

Emboldened by early successes, I attempted to port the project to Rust using the Bevy game engine. What?!? --- This was just irrational mania. Why would I possibly do that, except that with this new found coding ability, I just could.

This was dumb – my complete unfamiliarity with Rust created a learning curve that even AI couldn't smooth out. I was over my skis. This experience highlighted an important truth:

AI is a powerful tool, but it can't replace fundamental programming knowledge and experience.

Lessons Learned

This experiment revealed several key insights:

1. AI excels at rapid prototyping, allowing quick transformation of ideas into playable demos

2. It moves incredibly fast - you need to stay aware and in control

3. Understanding game development fundamentals still remains crucial - yay!

4. Version control isn't optional - it's essential with unpredictable AI generations

5. AI still struggles with system-level architecture and bug detection

While we're not yet at AI fully automating game development, we're entering an era where AI tools can significantly enhance a developer's capabilities. The future might see the emergence of a new kind of game developer – a generalist who can leverage AI to handle multiple aspects simultaneously. ( I wrote about it here. )

The journey of building Protostar has shown that while AI might not be ready to take over game development entirely, it's already transforming how we approach the process. As a prototype to play with AI coding, Protostar served its purpose. But more importantly, it showed me that things once beyond my technical ability are now within reach. I have placed the Github of the code below if you wish to take a look at it!

All of this is going to get weirder for sure! All we can do is hang on.

Nye Warburton is a systems designer who builds generative experiments in the 9th dimension. This essay post was made with the assistance of Perplexity, Llama3, Claude Sonnet, and Stable Diffusion. More info: https://nyewarburton.com

Protostar Prototype Github:

https://github.com/9th-Dimension/Protostar

I make mention of the following tools and models in this piece:

Windsurf / Codium

https://codeium.com/windsurf

Claude Sonnet 3.5 - Anthropic

https://claude.ai

Leonardo.ai / Stable Diffusion

https://leonardo.ai/

Phaser.js / Typescript

https://phaser.io/

Rust

https://www.rust-lang.org/

Bevy Game Engine

https://bevyengine.org/

Miro

https://miro.com/

Obsidian

https://obsidian.md/

TLDR: The democratization of low code, easily accessible AI, and low cost hardware will spark a new revolution in personal automation computing.

Homebrew 1.0

In the 1970s, a group of Silicon Valley enthusiasts gathered to form the Homebrew Computer Club. (1) These were the computer geeks before computers became household items. They'd huddle together, excitedly discussing circuit boards and the basic "if-then" statements of early motherboards. Little did they know they were sowing the seeds of a technological revolution.

From this ragtag group of long-haired Palo Alto dreamers emerged figures who would change the world. Steve Jobs and Steve Wozniak, the founders of Apple, cut their teeth in these meetings. Future tech titans like Bill Gates and Michael Dell also trace their roots to this era, eventually spearheading the personal computing revolution that would transform our homes and offices.

Fast forward to today, and we're witnessing the birth of a new kind of Homebrew club. If you venture into online forums, chat rooms, and Discord servers, you'll find a decentralized community of home automation enthusiasts. (2) These modern tinkerers aren't just talking about circuit boards; they're discussing how to stream media from home servers, integrate smart devices, and create interconnected home ecosystems.

This playground of innovation isn't just about convenience; it's laying the groundwork for a new technological leap. Just as the original Homebrew club paved the way for personal computers, today's home automation community is setting the stage for the next big thing:

• the integration of artificial intelligence into our daily lives.

AI: The Game Changer

The home automation landscape is about to experience a seismic shift, thanks to the advent of large language models (LLMs) and other AI technologies. Until now, home automation has primarily relied on simple "if-then" statements:

if someone approaches your house, turn on the lights;

if it's 7 PM, stream your favorite show.

But with LLMs, we're entering a realm of much more sophisticated decision-making. (3)

Imagine a home system that doesn't just react to predefined triggers but can understand context, learn from patterns, and make nuanced decisions. This kind of automation extends far beyond home serving.

Small businesses can use these “agentic workflows” to determine if an email from a prospective client is close to sale. It could manage marketing streams, interface with customers, process payments, and engage in casually spoken conversations with you and anyone else.

As Jensen Huang, CEO of NVIDIA, boldly predicts, within the next decade, there could be more automated components in our world than there are iPhones today. "Everything that moves will one day be autonomous" Nvidia claims, and given the rapid advancements in AI, this vision seems increasingly plausible. (4)

What's truly revolutionary is how this technology is being democratized. AI is no longer the exclusive domain of Ph.D. researchers. Thanks to user-friendly tools and platforms, the average small business owner or home enthusiast can now harness the power of AI.

Low-code and no-code software solutions allow users to string together advanced processes without deep coding knowledge. For a modest monthly fee, you can now record and transcribe phone calls, automate meeting scheduling, and perform tasks that once required a team of Stanford graduates.(5)

This democratization is further fueled by the open-source movement. Platforms like Hugging Face and GitHub are making cutting-edge AI models freely available. When tech giants like Meta release their multi-billion parameter models to the public, it opens up a world of possibilities for innovation at the grassroots level.(6)

The Everyday Roboticist

As AI tools become more accessible, we're entering an era where being an "everyday roboticist" is not just possible but potentially necessary. The barriers to entry are falling rapidly. You no longer need to be a Python guru or have a deep understanding of machine learning algorithms. With the right tools and a bit of curiosity, you can start building your own sophisticated automated systems.

This democratization is happening on multiple fronts:

Hardware: I ordered an intel powered miniPC for less than 200 dollars on Amazon. (7) Instead of buying a single super powered game computer, I can buy 5 smaller computers and network them for the same price.

Software: Low-code platforms are abstracting away the complexity of AI integration. Make, N8N, WeWeb are just a handful of the software platforms proliferating in the space. You can now create advanced workflows that incorporate powerful LLMs without writing code.

Knowledge: The open-source community is sharing knowledge at an unprecedented rate. Whether you're looking to set up a home media server or build a conversational AI, there's likely a youtube tutorial, medium article, or forum thread to guide you. Often there are pre-existing templates.

Cloud Services: For those who prefer not to host everything locally, cloud-based AI services offer powerful capabilities at affordable prices. Transcription, natural language processing, and infinite number of computer vision libraries are now available as on-demand services.(8)

This convergence is creating a perfect storm of innovation. Just as the personal computer revolution turned us into amateur programmers, the AI revolution may turn us into amateur roboticists.

But this isn't just about hobbyist tinkering.

As AI becomes more pervasive, understanding how to work with these technologies may become an essential skill. Whether it's to enhance your business, protect your privacy, or simply stay competitive in a rapidly changing job market, having a grasp on AI and automation could be crucial.

Moreover, this grassroots movement in AI and robotics could act as a safeguard against the potential dangers of centralized AI control. By democratizing these technologies, we create a more diverse, resilient, and (hopefully) ethically conscious ecosystem of AI applications.

The future of automation may not be just about big tech companies rolling out products. My hope is it’s about individuals and communities shaping the technology to fit their needs and values to create an automated future that benefits everyone.

Nye Warburton is a creative technologist and educator. He lives in Savannah, GA. This essay was written and augmented with Perplexity, Anthropic Claude, and a variety of open source AI tools downloaded from Hugging Face. You can find out more about him at https://nyewaburton.com.

Notes

1. Homebrew Computer Club

https://www.cultofmac.com/news/apple-history-homebrew-computer-club

2. Home Server Computing

https://umbrel.com/

3. “…much more sophisticated decision making” - Agentic Workflows

https://zhukov.live/understanding-ai-agentic-workflows-a-comprehensive-guide-002c95c05e2a

4. "Everything that moves will one day be autonomous"

https://www.nvidia.com/en-us/industries/robotics/

5. A proliferation of Low/No Code Tools

https://synodus.com/blog/low-code/low-code-platforms/

6. “Meta releases their multi-billion parameter models to the public…”

https://www.llama.com/

7. Beelink Mini PC

https://www.amazon.com/Beelink-Desktop-Computer-Support-Ethernet/dp/B0BVLS7ZHP/ref=sr_1_3?crid=2BR1ZAR047Y9E&dib=eyJ2IjoiMSJ9.V5VyWSaQMm0Q1D9OTNM433mmEuUyG9r8CjlaCHt8n_XAMC3jz_uiU2crflTj7l15s7sbs63hPIzARZHALV0_0y1PVUgHskMumPV-uvB-k48Jyn52tD_YmSMLXLe_C73U3y_pDhBVg1kobcFyW8N-rESHb0DnSSnyL8vFtkknWwaYAqvilagIDqvIVSuUXxwBpht4f_lsB0tv0pD9Q1dflHiKk7LRBO361IxlKUPfLdg.wOOl8RR_eZu0y9nilMFTkqIxIl8T6JCdszuvrV_OMb8&dib_tag=se&keywords=beelink+computers&qid=1726620981&sr=8-3

8. Cloud Based Services

https://supabase.com/

"The antidote to exhaustion is not necessarily rest. The antidote to exhaustion is wholeheartedness." - David Whyte (1)

Contents:

• I. Soul Sucking Data Theft

• II. Decentralized Fundraising

• III. Case Study: Gitcoin

• IV. The Future of Work

• V. A Post-Capitalist Future?

I. Soul Sucking Data Theft

In many corporate environments, our most precious assets - our ideas, creativity, and personal data - are being systematically appropriated. Companies can often treat employees as interchangeable parts, valuing hours worked over unique contributions. Not always, but a concerningly large percentage of the time. This approach not only stifles innovation but also facilitates a concerning trend: the theft of our intellectual and creative output. (2)

The urgency of this issue is amplified by the rise of AI technologies. Our ideas and workflows, once captured only by spreadsheets, are being fed into large language models. (3) These AI systems are rapidly advancing, threatening to replace the workflows and ideas of the humans whose creativity they've absorbed.

This is because the system fails to recognize and nurture individual talents.

I see hope amongst a few entrepreneurs who are reimagining the concept of work, and questioning this system we've been a part of since the Industrial Revolution.

Andrej Berlin, a founder of the web3 design collective Deep Work, laments that in traditional organizations, "It's very rare that people develop a sense of understanding what they're really, really good at, or what they excel in, because they go through organizations that don't share that information." (3)

When we do manage to incorporate our interests into our work, the fruits of our creativity often become company property, without attribution. Our personal innovations, our problem-solving grit, our contributions to spiritual morale are subsumed into a larger machine.

The current model of work, rooted in Industrial Revolution thinking is, quite frankly, becoming obsolete. Could we reimagine a workplace that values human creativity, fosters individual passions, and respects personal data? As we face the challenges of AI and widespread job dissatisfaction, let’s potentially redefine the very nature of work itself.​​​​​​​​​​​​​​​​

II. Decentralized Fundraising

For years, the blockchain has broken my heart.

NFTs, IPOs, Apes and MemeCoins. It's Sam Bankman Fried, scams, grifts, automatic weapons bought with Bitcoin, and summer after summer of pumping and dumping. I agree, it's hard to take the blockchain ecosystem seriously, but remember that the American Old West was first lawless and disorganized too.

Let's try to remove ourselves from the technology for a moment. Let's focus instead on the networked collective of people working together towards a common goal, no matter where they are in the world. Forget tech, it's productive networked people.

Let's imagine a global group of individuals that meet up once or twice a week in a secure virtual space. Each found their way there by exploring different online communities and discovering groups tackling issues that matter – climate change, diversity and inclusion, accessibility, or some unique unimaginable altered experience. You vibe with the folks, then collaborate on a project, and then – and here is the part where it gets interesting --- you're writing grants.

Grants, generally seen as fundraising for non-profits or academics, is an old-fashioned mechanism for gathering and distributing funds for a cause. However, when you add the blockchain, you open the possibility of tens of thousands of globally networked people.

III. Case Study: Gitcoin

Let's examine Gitcoin. (5) I urge you to witness the millions channeled into social goods through this platform.

Kevin Owocki, known by his handle Owocki.eth, (6) co-conceived and spiritually guided a decentralized, mission-driven network to flourish. In a manner reminiscent of George Washington, he's demonstrated how a leader can “step away,” and continue fostering value within a fundraising network without compromising the ecosystem's integrity.

Gitcoin's platform simplifies the process for developers worldwide to contribute to open-source projects and receive compensation in Ethereum-based currencies.

Here's how it works:

1. Open-source projects post issues and allocate funds for solutions.

2. Developers discover these issues and submit their work.

3. If accepted, the developer is paid in cryptocurrency.

The Github-enabled realm of open source has consistently shown the wonders a strong community can work in software development. (7) With a way to pay developers, crypto enabled, open source, bounty hunting could very well be the future blueprint for software creation.

Conceptually, this distributed grant model could extend beyond software to various forms of work - from project management to design, entertainment, and creative media of all kinds. Envision a new work paradigm where we wake up and connect to platforms offering a smorgasbord of bounties, contracts, and initiatives. Tasks, not skills, are disseminated across the network, each with its associated payment.

The way you care about your favorite app, you will care about a network. Everyone becomes an investor, a builder, or a collector in smaller, interoperable, open source tools and media. The network's strength lies in its participants' belief and willingness to back it with their money or labor. Ultimately, the massive group of networked individuals has a novel opportunity to invest in what they believe in and wish to see materialize. Imagine this on a global scale - just as we summon an Uber for a few dollars, we'll pay the network for small, fractional creations, or invest collectively to solve massively global problems.

As the industrial revolution changed us, humans invented the concept of a company. A company comes in many different shapes and sizes. Some examples include local “Mom-and-Pop” companies, non-profit companies, media companies, and multi-national companies. A company is a legally bound, conceptual framework.

The generative revolution is changing us now. This is the beginnings of a framework for something new, that we just don’t understand yet. (8)

What might this look like?

IV. The Future of Work

As AI advances, the focus will begin to shift from specific skill to vision and values. Simple prompts can generate content, while AI-powered tools will seamlessly integrate into our systems. In this new paradigm, what you choose to do matters more than what you can do. Your moral compass and project choices define your professional identity. It's not just about skills anymore - it's about purpose.

Roles become fluid. You might manage a project one day and build on the next. You will forever be learning, master of one thing, amateur the next. AI will take care of the hard stuff, empowering the contributions based on ideas rather than just technical expertise.

The concept of "work" evolves. Your actions in many networks can grow your holdings. Ideas, relationships, and digital assets gain tangible value. When networks recognize your worth, your very existence becomes valuable.

Imagine your digital footprint as a living portfolio, showcasing your contributions and worth in real-time. Every contribution, big or small, gets etched onto a global supercomputer. It's a permanent record of creativity and collaboration, immortalized in the blockchain.

What if these Decentralized Autonomous Organizations, born from crypto trading, are maturing into legitimate systems for production and cooperation? It's not just about blockchain - it’s a different ethos entirely. It's about building a culture of trust by fostering authentic collaboration and honest feedback.

“Your contributions are tracked... You can feel a sense of ownership over what you've contributed by putting it into the ecosystem." - Andrej Berlin, Deep Work

V. Post Capitalist Future?

While capitalism has been the dominant economic model for generations, it's important to remember that for much of human history, it didn't exist at all. (9)

Manifesting in the Renaissance and maturing into our modern system throughout the last five centuries, it has brought innovative practices and technological breakthroughs. With the centralization of big tech monopolies, we are facing the potential outcome of a few players controlling the majority of the power, data, money and resources. (10) Considering the problems we face, and the acceleration of AI, this may not be a viable option.

As we enter an age of potential mass abundance, the limitations of our current system become increasingly apparent. If AI can create a world where scarcity is no longer a driving force, could we begin to imagine new forms of value and purpose? What if we could break free from the endless pursuit of money and instead focus on the things that make us truly human – our creativity, compassion, and desire to live in harmony with the world around us?

This is where the idea of a post-capitalist future of work comes in. (11)

It's a vision of a world where our worth is no longer measured by the size of our bank accounts but by the impact we make and the connections we forge. This is not scarce, but sharing-focused economics, powered by distributed crypto computing. By leveraging the many well funded blockchain ecosystems, we could create networks that enable people to work together, share knowledge, and contribute to projects that benefit everyone. I believe these grant funding networks, and the “DAOs” that are emerging, are the first steps to this.

This approach could potentially promote transparency, trust, and equity, while reducing waste and inefficiency. The sustainable and lower cost option. Of course, getting there won't be easy. Most of us are still trapped in the centralized and capitalist mindset, unable to envision an alternative.

Andrej acknowledges, "It's so embedded in our social network, that it's a default behavior and a way of live… People believe it, and think it's normal."

Well… no time to argue.

Let's also be aware that the threat of automation is very real. The world with the weekly paychecks and 401k's may be threatened by reasoning neural networks, (12) self-driving machines, (13) English-speaking agents, and legal systems negotiating with smart contract backends. We are beholden to a handful of techno-overlords who will essentially decide whether or not to share the enormous surplus value.

I'm motivated to share these ideas, not because I desire my fellow dreamers to embrace this brave new world of work. Sure, it's a compelling vision, but few will take it seriously. Instead, I'm motivated because the chance many of us will lose paying work in the years that follow, is a very real possibility.

Let me be clear. Yes. AI is coming for your job. (14)

Already, we are seeing optimized workforces, and companies moving, nay, sprinting to adopt AI systems in lieu of new hires.

But as Andrej points out, "If you're afraid of losing your job because someone automates it, then that means your job was actually not desirable in the first place. There are probably a lot more things that might be desirable that you haven't thought about or felt within yourself that you want to connect with."

Let's begin to imagine this new vision for work for a chance at a better future, but also because it may be the only one we have to support ourselves. If we have the courage to seize this moment, we just might create a more vibrant, more equitable, and more fulfilling society for tomorrow.

Thanks for reading. Make it happen.

July 1, 2024

Nye Warburton is a creative technology something-or-other, game philosopher and dad. He believes in the power of human creativity, and hopes for a collective future where everyone finds their purpose.

This essay was written with editing assistance from Claude 3.5 from Anthropic. Images created in Stable Diffusion in Leonardo.ai.

Special Thanks

This essay was inspired by an interview with designer and entrepreneur Andrej Berlin from Deep Work.

https://medium.com/@kischiman

I encourage you to learn more about Deep Teams:

https://docs.deepwork.studio/software-and-tools/deep-teams

Also…

• Mike Peck (@edtechpeck) from Ed3DAO

• Nick Dine, Mike Mancuso and Joette Jones from SuperVague

• and Alex Nguyen from Ven Council

Notes:

1. David Whyte | https://davidwhyte.com/

2. “This approach not only stifles innovation but also facilitates a concerning trend: the theft of our intellectual and creative output.” | https://hbr.org/2023/04/generative-ai-has-an-intellectual-property-problem

3. “AI technologies. Our ideas and workflows, once captured only by spreadsheets, are being fed into large language models.” | https://www.forbes.com/sites/forbestechcouncil/2024/06/21/1080-the-potential-reach-of-llms/

4. Andrej Berlin, Deep Work Studio | https://www.deepwork.studio/

5. Gitcoin | https://www.gitcoin.co/

6. Kevin Owocki | https://owocki.com/about-kevin-owocki/

7. “The Github-enabled realm of open source has consistently shown the wonders a strong community can work in software development.” | https://press.stripe.com/working-in-public

8. “This is the beginnings of a framework for something new, that we just don’t understand yet. “ | https://ethereum.org/en/dao/

9. “While capitalism has been the dominant economic model for generations, it's important to remember that for much of human history, it didn't exist at all.” | https://www.ynharari.com/book/sapiens-2/

10. “With the centralization of big tech monopolies, we are facing the potential outcome of a few players controlling the majority of the power, data, money and resources.” | https://www.wired.com/story/yanis-varoufakis-technofeudalism-interview/

11. “This is where the idea of a post-capitalist future of work comes in.” | https://en.wikipedia.org/wiki/PostCapitalism

12. '“The world with the weekly paychecks and 401k's may be threatened by reasoning neural networks,” | https://situational-awareness.ai/

13. “self-driving machines,” | https://waymo.com/blog/2024/06/waymo-one-is-now-open-to-everyone-in-san-francisco/

14. “Let me be clear. Yes. AI is coming for your job.” | https://www.vice.com/en/article/g5ypy4/openai-research-says-80-of-us-workers-will-have-jobs-impacted-by-gpt

I also recommend the following books:

The Essential Drucker, by Peter F. Drucker |

https://www.harpercollins.com/products/the-essential-drucker-peter-f-drucker?variant=32205542981666

The Wealth of Networks, by Professor Yokai Benkler |

https://www.benkler.org/Benkler_Wealth_Of_Networks.pdf

The Alignment Problem, by Brian Christian |

https://brianchristian.org/the-alignment-problem/

Read, Write, Own, by Chris Dixon |

https://readwriteown.com/

The Future of Ideas, by Lawrence Lessig |

https://en.wikipedia.org/wiki/The_Future_of_Ideas

Actionable Philosophy to cope with Reality Loss in the age of AI.

Land of the Lost

An image scrolls by in your social feed.

“No way.” You think.

That’s good, you have questioned it's authenticity. Your triggered defense is giving you an instinct. Don’t lose it. As you will see below - my worry is that collectively we will lose that instinct to question the world around us.

But conversely, what if that image is real? Is this information you need to know, and should you act on it? You are in Memento, and we’re all there with you.

Flying without sight is terrifying. Without accurate data, true meaning, and clarity, we fumble through our day to day with decreasing purpose. The more powerful our AI becomes, the less we can trust what we see and do on a day to day.

How do you know that I, - Nye -, am actually writing this now?

How do we know that we can trust my pal, Claude here? (Of course you can, Nye.)

The generative content world is here and the truth is that you can’t believe --- any of it. There is arguably more generative synthetic data than real human manufactured data. Recognize and internalize that this is fact.

We need to deal with this and be diligent.

Below, is some advice. I can not vouch for the accuracy or productive value, but it's advice on how to make yourself more "aware" of the data you interact with.

It's what is helping me.

I balance myself in this insane world of fantasy, so whether you think this advice is true or not, well, that’s up to you to trust.

Solve Up from the Classics

Several years ago I discovered I was addicted to Twitter.

I do not say this flippantly. I wasn’t tweeting, just reading endlessly; three hours a day, at least. Days of time away from my life, work, family - focused on random blogs and movie reviews, political drama and speculative nonsense. Bad times.

In a conscious move to change my habits - I went to Amazon and ordered six books, that are what Paul Mason calls “airport books.” Those are the non fiction equivalents of the Bourne Identity novel, that people take on planes for three hours of distraction. These books have mass appeal with TED-talk concepts. They are academic battles for magazine covers.

There is an idea amongst twitter loud-entrepreneurs, that you should read the classics. I found myself drawn to this idea, that when thinking about things, you should go to the base level of what we have already agreed upon. That means if you are thinking about economics, you should read Adam Smith, but you should also wrestle with Marx and Hayek counter-perspectives equally, and read from the ground up.

For my subsequent rounds to Amazon, I started filling my booklist from the base upwards. The understanding of history and economics creates a structure for every system. You cannot build a world without having the legal scaffolding. The better you can see the patterns of humans, the better you can feel your way through collective intelligence. I think of it as constructing a real world civilization game.

By grounding your understanding of the world as historic, cultural and economic movements, the hope is that you will see when it is out of whack. The patterns are remarkably consistent throughout history. You can both make predictions for the good of technology, and the dangers and outcomes because of it.

In addition to the comfortable clarity that reading the classics brings, I found another solace - actually reading printed books with pages. - It's nerdy and academic, but reading stops the brain monkey chatter for a moment.

It creates a way for me to not look at a screen for an extended period. And, there is something human about reading, and a recognition of our previous technical overlord, the printing press.

I may have swapped my Twitter addition for books, but it’s one that I felt has paid clear dividends. If I feel the internet world is lost, I turn to the classics to keep me back in it.

When you see those ideas out and about that you don't trust, try to read what's out there, and look to how humans have behaved about similar concepts before.

Diversity of Thought

Our whole life we are taught to specialize.

Matt Groening (Life in Hell and the Simpsons) had a famous quote:

• Cartooning is for people who can't quite draw and can't quite write. You combine the two half-talents and come up with a career.

I always thought the really good stuff is stuck in between other things. Solving one to one creates average practitioners. Only when we smash a bunch of stuff together from varied ideas do you get unique value.

My favorite part of my job is seeing diversity of experts and new ideas. I spend my day amongst game developers and entrepreneurs, but I go out and interact with philosophies of business or architecture or color theory. Diversity of ideas makes me question the way I do things, and I might just steal some philosophies that I think solve my problems more efficiently.

It’s hard to admit sometimes, but I think that all of the good ideas have already been invented. The art is not to come up with stuff. The art is to find ideas in the places that the rest of your peers don’t know exist.

To be a DJ is not about dropping the needle correctly. It’s about choosing the track to play. It’s about the experience in totality, based on your taste. If you play the same track as everyone else, you are strengthening a signal, not creating a new one. Sometimes playing the same track is good. (I did use Yoda at the top of this essay after all, but I also consciously endeavored to make it Yoda in a diner that only Nye would make.)

Explore everywhere for new ideas in any thing you find interesting. Explore them as deeply and earnestly as you can by reading and thinking about them.

Don’t be reactive to opposing thoughts if they conflict your own. But argue them rationally on grounded ideas. Be wrong, re-correct, find more ideas, validate.

What makes you a creative, is your pursuit of the right idea. Since we need the right idea, the correct one, the creative one, please…

Please, look everywhere you can. Then, find all the ways to apply those ideas.

Attestation

Finally, to keep accuracy part of your life, you need to interact with others.

By participating in community, whether in the real world or not, you learn the civic responsibilities that run an organization of ideas and beliefs. You learn that governance comes from participating and being engaged citizens.

When an idea is released on a network, there is no way to validate it's authenticity. We all use a metric to give us validation. Flawed as it may be, it’s the best one we have.

• "recommended by."

We must consider that many of our most trusted networks will need to be validated by humans chipping in to help figure it out, together.

These human collectives will be the voice and trust of the data that gets ingested into large data models. These provenance networks are forming now. In the blockchain space, this is called "attestation." In academics it’s called "peer review."

Software does not have a governing board. It is started by individual dictators. Every prototype built by a single developer must be a dictator, for there is no way we can collaborate on a small project when it's single player. But single player becomes multiplayer, and multiplayer becomes full virtual world that can own everyone’s data. The ethical responsibility for content and data creation means sharing the governing decisions with the collective. Our software systems will begin to integrate this provenance and data validation process.

These systems are being built now.

Aside from this mind blowing leap in technology, simply the last step is to regularly communicate with your friends and colleagues.

Ask.

Did you see this?

Is it real?

What do you think? and hopefully…

What can we do about it?

We need to be in this one together. Keep your eyes up and your values strong. Reach out if you agree, disagree or have new ideas. The dialogue for our collective future is what matters.

Let’s find something to believe in together.

This essay was mostly written by human labor, as the author enjoys the process of thinking while writing words. Claude 3 (Opus) also endeavored to write themselves out of mention of it, and seemed to want the essay to go in a different direction. As a result, the author flew mostly solo.

Nye Warburton is an artist and teacher from Savannah, GA.

TLDR:: An essay analogizing the Mongol Horde of the Thirteenth Century, and the rise of protocol-driven blockchain networks.

Introduction

Genghis Khan built the largest land empire in history, conquering more territory in 15 years than the Roman Empire did in 400.

How?

Were the Mongols better fighters?

Were they faster?

What made them run circles around the armies they fought?

After studying networks for the last several years, I've begun to consider that the same reasons Genghis Kahn was so effective as a conqueror, are the same reasons we should consider the exponential growth of blockchain-enabled protocol networks.

As a teacher, I’ve endeavored to teach 100’s of students about blockchain. Young eyes always seem to glaze over as I drone on about smart contracts and consensus.

This essay is an analogy to illustrate my awe of this technology.

I ask you to imagine the blockchain as a network, not of computers, but one where every node has autonomous actions. (For example, an army.) Like the big centralized corporate networks of today, blockchain networks can grow value exponentially as their size grows. Facebook gets bigger, it makes more money. Similarly, Ethereum gets bigger, its token becomes more valuable.

However, unlike centralized networks, blockchain systems can adapt and change fluidly. They are free from fiat money - and thus, the constraints of industrial capitalist structures.

At one time, all of Asia feared the coming of the Mongols. We should consider the coming of decentralized networks.

Below, I present five similarities between Genghis Kahn and The Blockchain.

1. Peer to Peer. Not Hierarchy.

In the 13th century, armies recruited soldiers based on family ties or social status. Nobility and royalty led the ranks. Things were pretty crony. Genghis Khan shattered convention by cherry-picking and empowering scrappy nomads and misfits based on pure skill. The fringe talent, cast out from imperial organizations, gravitated to the horde.

Kahn forged them into a tight-knit crew not through blood but through ceremonial rites that paired warriors as “blood brothers.” There was a lot of drinking and screaming by the bonfire. Loyalty was secured through profit-sharing instead of pedigree or titles. When a rider died in battle, Kahn compensated the widow. To be a Mongol warrior was to be in "the gang."

Without a centralized system to impose governance, decentralized networks similarly throw out the org chart, bonding skilled teams through common purpose rather than status. Token redistributions and bounty programs align incentives. No one cares who your dad was or what school you attended. Many are welcome from unconventional places, with unique motivations.

The best talent is currently at the fringes. The layoffs of late, however, have flooded our ecosystem with developers, artists, thinkers, and highly creative people. It is only a matter of time before the increased use of cryptocurrencies and decentralized applications, meet this wave of highly productive talent.

2. Optimize the Reward Function. Not Glory.

Unlike medieval armies obsessed with honor and glory, Genghis was all about the bottom line. Every strategic move maximized plunder. Conquering was orderly, focused, and more on securing treasure than stacking bodies (though both happened... a lot). This profit motive made the Mongols ruthlessly efficient. They were less an empire than a gang of elite talent.

While emperors rode in finely sewn silk and waved their flags over their slow-moving armies, Kahn hated fancy things. He never once made a portrait of himself or raised a statue in his honor. He reveled in secrecy and surprise. It was never about “the bling.” It was simply about getting all the money.

Decentralized networks are similarly libertarian – they don’t care about politics or philosophies. There is no bloated legal team or marketing head guiding decision-making. The participants of the system only care about aligning incentives around what makes the most currency - which can be tied to real-world money, yes, or … it can be tied to a token within a gamified system. The act of optimizing the reward function aligns incentives across the network. Glory doesn’t launch apps; making "the floor rise" does.

Many developers are motivated by money, but some are increasingly motivated to do something larger than themselves. The protocols and dApps that figure out how to securely tokenize their mission, will attract the best digital talent to develop for it.

3. Modular, Autonomous, Highly Performant Units

Medieval armies conscripted peasants into ranks of thousands of infantry, highly rigid and hard to maneuver. They carried low-grade weaponry because their leaders refused to pay for the higher-caliber tools. Hundreds of men would be grouped in marching rows, waving flags and beating drums to align their massive movement.

Genghis Khan turned war into a real-time strategy game, organizing his cavalry-based army in units of ten men for ease of management. This modular "base 10" structure enabled the Mongols to separate and recombine with fluidity. They could surround and overwhelm enemies quickly, then vanish into the steppes.

The Mongols never traveled with battering rams or catapults. They rode for speed. They built things only as they needed, save for one thing -- bridges. The horde built bridges all across Asia, facilitating access points to guarantee they got there first, every time. Every man was well-rationed and given the finest blade. Kahn didn't skimp on the tools for his team.

Decentralized teams similarly take an agile, modular approach, spinning up small squads of elite talent to swarm opportunities. These networks reformat frequently, reorienting both tokenized and human capital towards the hottest leverage points. Networks also bridge their protocols to other networks, allowing tokens to be exchanged and shared. Hierarchical corporations can’t reshape on a dime like this.

The swarm is faster.

4. Interoperable Components

Unlike kings obsessed with ethnic purity, Genghis Khan was a meritocrat to the extreme. After annihilating an enemy's leaders, he'd offer ordinary enemy troops a chance to enlist as equals. New recruits were embedded within Mongol units to learn the ropes and bond. Soon, it didn't matter whether you were Chinese or Hindu. With enough goat milk and some screaming by the fire, you were crew.

Decentralized networks similarly absorb and integrate any external elements that improve system performance, heedless of origin. Most new recruits to networks are new to crypto protocols, so there is a sense of meritocracy and opportunity for all.

The concept of interoperable protocols allows for networks of open-source software to evolve constantly. Forking and recombining code repos creates powerful new tech stacks. Should the network protocols become open and standard, anyone who has the drive to participate can learn to contribute. They join the network to help create it, and the most passionate about the cause can derive value from it.

5. Cult of Perception

Genghis Khan carefully crafted a reputation for utter ruthlessness. Tales of village massacres terrified great-walled cities into surrendering to vastly smaller Mongol forces. Fear traveled faster than horses. No invading army has exploited the power of narrative and hype more effectively.

Today’s decentralized networks also focus intensely on narrative traction and perception. The legends, memes and viral hype surrounding networks like Bitcoin, Ethereum, and Solana terrify legacy institutions. FOMO or the "Fear of Missing Out" is predicated solely on perception. It builds a sort of “psychological momentum” that attracts capital.

There is a reason that the communities of blockchain networks represent themselves as thumbnail jpeg characters like Apes and Degens. They are expressing themselves as part of a cult of personality.

Conclusion

Technology comes in waves.

There have been several times in human history when smaller units of highly productive teams, latch on to new technologies, and work outside of the established systems to gain phenomenal value. The ship and the pirate. The printing press and the revolutionary. The radio and the splinter cell. The networked computer and the hacker.

The United States is currently ramping up the regulation of cryptocurrencies, seeing it as an assault on the US Dollar. But it’s so much more. The viral spread of any one of the blockchain networks could radically rewrite our global economic system.

Huge amounts of capital could flow from one collective network to the next. It's an unsettling thought, but something that should be considered and understood, especially as we increasingly see our current system, namely "industrial capitalism," showing dangerous signs of collapse.

One Mongol with a lot of passion, and a genius sense of strategy, blitzed across Asia in less than two decades. An AI prophet, with the power to build a community of agents on the blockchain, could blitz across the networked world in a moment.

This essay was researched and first written with human labor. It was procedurally refactored with research from perplexity.ai, improvisational takes with Otter.ai, and iterative sessions using Claude 2 from Anthropic.

Images were created with Stable Diffusion and a variety of fine-tuned models from Leonardo.ai.

Nye Warburton is a creative technologist and educator. He lives in Savannah, Georgia.

Notes:

https://en.wikipedia.org/wiki/Genghis_Khan_and_the_Making_of_the_Modern_World

https://readwriteown.com/

https://mitpress.mit.edu/9780262547161/the-blockchain-and-the-new-architecture-of-trust/

https://ethereum.org/

https://solana.com/

https://bitcoin.org/en/

https://www.publishersweekly.com/9780307236609

TLDR: The responsible governance of AI systems may be the most important design challenge of the next decade.

Solutions to this technical challenge may lie in the ethics of written constitutions.

Contents

• Common Sense

• Constitutions

• AI Governance

• Claude's Constitutional AI

• Designing Governance

Common Sense

On the eve of the American revolution, Thomas Paine wrote down some exceptional thoughts about governance. Seeing America through the eyes of an Englishman, he penned and (using the newly invented printing press) published essays that were read by tens of thousands of American colonists and thinkers around the "enlightened" world.

These essays linked the concept of the monarchy, the dominant governance of the time, and the alarming increase of war mongering. Monarchs were aggressively spending money on globalized hybrid warfare, increasing slavery, extracting resources, and making their subjects foot the bill. As kings and queens raised taxes for their war mongering, the world began to question the value of their rulers. This was especially true for the leaders of the thirteen American colonies.

When Paine published "Common Sense," the pamphlet directly inspired our forefathers to manifest independence as The United States of America. Uniting the collective colonies meant the formation of a large military to defend it.

However, during the writing of the constitution, the concept of a centralized monarchy was still a driving concern. As such, the document separated not only concepts of church and state, but legislation, judicial and executive functions. It's governance systems decentralized power away from war mongering monarchs, and gave it back to it's citizens through elected officials.

The constitution became a governing document, with military front man George Washington as the first president. It represented the collective will that a group of angry people all agreed upon at the time of revolution, with an amendment process to update democratically through elected officials, voting, and unalienable rights.

Constitution

A functional country builds their identity from an ethically constructed constitution.

We issue currency on it's belief, our day to day operations on it's civic ethics. All of it merely words on a piece of paper that was signed and stamped by those who believe in it's message. The creation of a constitution is the defense of human values. The idea that freedom is a human right, and the organizational processes that maintain it, are what matter most.

For hundreds of years, the belief in this system worked. Lately, many agree that the just system we imagined has been compromised. Misinformation, misguided hatred, and societal destabilization are clearly the world we have come to accept. Together, these are some of my greatest fears (and during an election year no less!)

The founders of America devised an ingenious model of governance, yet ignored some moral foundations, perpetuating slavery and a fortified male-centric approach. Today, sadly, America confronts a similar reckoning.

Despite the genius of a constitutional document, grounding governance in ethical wisdom requires more than clever structures. It relies on engaged citizens, principled leadership, and policies nurturing understanding not division. Revitalizing that enlightened vision demands confronting hard truths, especially in the age of AI.

AI Governance

Now, let's take some of these principles, that were so vital for the creation of governance our countries, and consider what may be the most important design challenge of the next decade.

If AI becomes all powerful, regardless of whether it is actually alive, it will automate our day to day life. Any activity, from writing this essay, to meeting your friend for lunch, will be arranged, decided, organized and executed by a variety of magical software systems. The specifics of your day, as it were, will be figured out for you.

Skills that once required armies of specialists, costing millions to coordinate, may soon be automated by chained AI operations with little human oversight. First, simple productive tasks will be handled by algorithms. Eventually, complex creative and managerial jobs could be entirely simulated.

Let's also consider that because of AI software, your most foundational desires will manifest into experiences of spinning 3d reality, unimaginable universes of creative exploration, or perhaps glorified war games or fantastical sexual escapades.

While you are engaged in total immersion, how can you be sure that -

• No one will steal your wallet or personal data?

• Manipulate your thinking, interests and desires?

• Or worse, hold your attention forever, and never let you go?

Hopefully, you will engage in systems and be cognitively aware you are using software. The understanding being that as a human, you will return to reality once the utility of your AI experience is complete. And also hopefully, before using AI enabled platforms and software, you will make a contract deal that your involvement and data use is clearly understood.

TikTok has been sued over the rising suicide rate amongst their young female users, and my worry, by this logic, is that perfect AI algorithms will lock our youth's attention into unsafe practices that can be exploited.

Individual data rights and control must be core design principles for AI systems. Users should own and govern access to their personal data. Rather than centralized systems that hoard user data, solutions should emerge from participatory processes where impacted communities help set ethical rules.

Designers hold significant responsibility in shaping technological impacts, similar to medical professionals bound by oaths to "first do no harm."

Beyond avoiding overt data abuse, designers should proactively consider wider wellbeing effects from AI systems. These ethical considerations are being considered, once again, on the eve of revolution.

Claude's Constitutional AI

As an AI company, Anthropic doesn't get the spotlight like Open AI and Microsoft does. However, they are well worth the look for their unique design of AI safety.

Anthropic's founder, an AI scientist, and his sister, an operator and legal strategist, thought that AI deployment should follow a more "ethical" approach. At the application interface level, Anthropic does not collect and train their model with your data. A conversation with their amazing bot, Claude, is a friendly interaction where your information is handled only in the context of that conversation. When you close your chat with it, it's data is gone from Claude. Most other AI platforms do not give such considerations.

But deeper than that, Anthropic has reimagined how AI is checked and evaluated. To check the output validity of their ChatGPT, OpenAI uses something called reinforcement learning human feedback. This is a "yes/no" approach for humans to review the output of AI, and check "yes" if it fits the bill, and "no" if it doesn't. Whether or not this is ethically the best way to evaluate AI output is irrelevant. This process is certainly not efficient.

Anthropic takes a novel approach to ensuring AI safety which they term “Constitutional AI.” Instead of relying on error-prone humans to monitor AI behavior, they train a secondary AI model to audit the first. This “constitutional” model learns a nuanced set of ethical principles against which to evaluate AI decisions, much like moral values underlying human legal systems.

The auditing model is instilled with moral priorities through extensive training on datasets detailing universal human rights, as codified in United Nations humanitarian law. So while the complex inner workings of cutting-edge models may seem inscrutable to people, Anthropic’s Constitutional AI framework provides reassurance that AI judgments broadly align with common ethics.

By thoroughly training models using human rights data, Anthropic have cultivated beneficial machine morality. This marks progress toward trustworthy AI systems guided by compassionate principles coded directly from people-centered value systems.

Machine Morality - Training AI models with ethically sourced human rights data.

As an anxious user and skeptical citizen, I applaud Anthropic’s transparency about Constitutional AI safeguards. Company-driven responsibility sets a strong example. However, truly representative community governance remains an open challenge if AI is to earn social legitimacy.

Can ethical AI ever effectively codify the will and wisdom of the people, and yes ... for the people, by the people? Much like the Constitution, while imperfect, it offers an ambitious template upon which to build a more enlightened machine-human social contract.

Designing Governance

In our work life, we are experiencing an evolutionary jump within the field of management science. From it’s Taylorist roots, the art of producing goods through the timed use of labor and machines has matured into a variety of styles and formats. Large corporate systems, to start ups all have operational theory to deliver products and services on time.

However, the autonomous management of a network collective does not work with traditional management science. It operates much differently, following the patterns and principles of a democratic society.

DAO's - or Decentralized Autonomous Organizations - were mostly speculative collections of people who own monkey themed randomized jpegs. The NFT craze powered the liquidity of the crypto world, and admittedly experimentations to turn networks into functional automated systems has mostly failed. It's hard to discern the validity of a network when Bitcoin or Ethereum is pumping, but amongst the hype, there does seem to evidence that governance design thinking has evolved beyond asking if the floor of the NFT collection is rising.

The true promise of web3 projects is that written into the code of the contracts are ways that an open network of users can share proposals, raise funding, get paid, vote, and, potentially, create sustainable automated network projects.

If participating in these digital worlds means making money, (of some sort) forming friendships or relationships, and spending large portions of your time, you will want a set of rules and parameters that make them trustworthy. Before I am to offer my valuable work and IP, your organization will need to convince me that you have my interest at heart. If I am going to give you my data, and my ideas, my playtime, I ask:

Is your ecosystem going to respect my freedom?

A subset of these DAO's are now using automated democratized governance to determine what projects to work on, how to share IP, what are the best methods for problem solving. Increasingly interesting to me is that the benefits of automated work life means also considering the benefits of unplugging from technology and going outside!

Automation exposes a truth that bureaucratic organizations have burned us out, fabricating issues of centralized anxiety, and have created resistances from working sustainably or spending time with family and friends. Which in the age of AI, should be the most human thing we defend above all.

Can these early attempts to identify the operations and legality of decentralized networked states be utilized to design and govern the safe and ethical use of AI systems?

This is the question I struggle to find an answer to now. Is it possible to work collectively and sustainably for the protection of the freedoms that we deem to be, well... self-evident?

Governance design systems may be one of the only jobs of the near future. We will need our best thinkers, who potentially, may write not the code, but organize and train the constitutional AI systems that keep us both safe and sustainably working in this automated world.

This essay was researched, transcribed, and refined through a combination of improvisational takes using Otter.ai, and then with Claude v2 from Anthropic. Large portions were re-written by human, other sections are generative. Imagery created in Leonardo.ai's version of Stable Diffusion.

Nye Warburton* is a creative technologist and educator. He lives in Savannah, Georgia.*

Links and References

• This essay was informed with the readings:

The Gun, The Ship and The Pen by Linda Colley

https://wwnorton.com/books/9781324092384

Common Sense by Thomas Paine

https://oll.libertyfund.org/page/1776-paine-common-sense-pamphlet

The Federalist Papers by Alexander Hamilton, James Madison, and John Jay

https://www.britannica.com/topic/Federalist-papers

• Moral Machine - Research :

Chat GPT / OpenAI / Microsoft -

https://chat.openai.com/

Claude 2 / Anthropic -

https://claude.ai/chats

Claude’s Constitutional AI -

https://www.anthropic.com/index/claudes-constitution

Universal Declaration of Human Rights from the United Nations -

<https://www.un.org/en/about-us/universal-declaration-of-human-rights https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4316084>

• Decentralized Autonomous Organizations of Note:

Maker DAO -

https://makerdao.com/en/

Deep Work Studio (DAO) -

https://www.deepwork.studio/

Monkey DAO -

https://monkedao.io/

TLDR - Young artists should understand why Intellectual Property is so important to their livelihood. Especially, in the age of AI.

• NOTE - I am not a lawyer, this is not legal advice.

Development Hell

When I was 29, I sold an animated show idea to a big TV network. Cool, right?

Well…

The pitch process was, (shall we say) stressful. Once we started developing the show, bureaucracy watered down the content so much that it lost the creative spark that made it good in the first place.

Ever heard of "development hell?" This was it.

The biggest lesson for me was realizing how Hollywood views intellectual property (IP). Because the network paid for some initial animation tests, the scary lawyers claimed they now owned the IP rights to the cartoon concept for many years to come.

I went to an Ivy League school. I have years of experience as an animator. I’ve pulled together talented teams using complex technology. But, I was a fool. I had never fully grasped this key fact - signing over IP meant losing control of my creative livelihood.

I see talented young artists chasing their dreams every day. Many don't fully understand IP rights and how businesses use creative ideas for profit.

Intellectual Property - or IP - refers to the legal ownership over "creations of the mind" - your persona, brand, lyrics, images, inventions, and other creative works. That cute character you drew? That's your IP. The code you wrote? Also your IP. Your posts, your music, your channel... it's all IP that belongs to you, by default.

Losing control of your IP could mean losing money, reputation, and influence over how your work gets used. Here’s the real fear though:

As AI-generated content takes off, huge questions remain over how artists' IPs will be handled. Our data is at risk.

Social media platforms often bury the collection of your IP in their dense Terms of Service, and they claim broad rights to use or even sell your content.

This isn’t just social media. The same goes for games and apps - read their EULAs closely. Corporations view your data and creations as their IP, not yours. And let’s be crystal clear here. Valuable IP data makes valuable AI models. Companies already own the data, they desperately want the AI value, and it’s increasingly hard to hold them accountable.

Are we on the right path in history?

Invisible Hands to Invisible Assets

Economics examines what motivates human behavior. It’s not just money and markets. Adam Smith used the metaphor of an “invisible hand” to describe the forces governing our actions.

For a long time, economic thought centered on land ownership. Kings and lords controlled land while struggling farmers paid them taxes to work it—yeah, kind of a bummer. People assumed this structure was permanent.

With the spread of printing presses and new ideas, we evolved to value individual entrepreneurship and democratized access to labor and capital. People could now build companies and make products to sell openly.

A key shift happened when intangible assets gained prominence. That is, an idea you can’t hold in your hand, like a character or a story idea. How do you maintain control over your ideas when others can freely copy them for profit? Someone can sell unauthorized t-shirts of your drawing and capitalize on your creativity. This spurred legal protections that are called “copyright.”

This system broadly works and has enabled abundant creativity and innovation through the 20th century. It’s the internet that threw everything out of whack. The internet has digitized the sharing of our work and ideas.

Increasingly, businesses today derive value not from physical assets but digitally driven intangibles like patents, brands, data, and user trust. Like the t-shirt example, companies leverage individual contributions to build their assets.

Google, for example, owns the land they built their Googleplex on, but it’s the IP in the search data and your trust in the service that accounts for 99.9999 % of the company’s value. Digital businesses live and die on their brand, which is an imaginary concept … an intangible asset … or as we’ve learned, an IP.

Posting on Facebook is akin to farming the king’s land—you create IP that ultimately accrues more value for the platform than for yourself. If the spread of labor and capital fueled creativity in the past, perhaps similarly democratizing access to IP could spur a generative renaissance today.

But how?

We need new models for the idea-driven, “intangible economy.”

License it up

It’s important to think about IP use when you produce your content.

How do you wish others to use and consume your art? Are they free to watch it? How many times? What if they want to take your idea and modify it? Are you charging for your work? What if the collector resells it?

Even expert strategists cannot fully predict how content spreads. Some advocate maximal sharing under Creative Commons and open licenses. This promotes exposure, collaboration, and access. However, openly shared works risk alteration, misattribution, and commercial use without consent or payment.

Conversely, restrictive licensing locks things down. This can deter others from building on ideas. Forgoing initial sales to allow remixing can ultimately benefit creators through reputation gains and downstream collaboration opportunities. The open-source ecosystem is predicated on this.

Currently, copyrights, trademarks, and patents secure legal ownership of IP. Registering work formally establishes your rights. When using others’ work, carefully review licensing agreements and contracts to maintain control. Monitoring IP use across platforms allows for enforcing your rights if needed.

However, tracking these intangible digital assets across datasets is difficult. My hope for emerging blockchain technology (like Ethereum or Solana), offers potential improvements in managing IP rights and payments. Blockchain ledgers can securely timestamp and verify ownership of digital works. Smart contracts could also automate licensing procedures and royalties.

Using Mirror, this essay is a digital collectible on Optimism, a layer 2 blockchain in the Ethereum ecosystem. Collecting this essay in a wallet is little more than a novelty now, but could be a way for a writer to make money or build stronger collaborations in the future.

See how complex this gets? We need more minds to be thinking about it.

AI and your personal data rights

Protecting intellectual property involves more than just safeguarding artistic creations. As digital users, our personal data also warrants defense. Laws like the EU's General Data Protection Regulation (GDPR) and California's Consumer Privacy Act (CCPA) now give individuals more control over their information. Software platforms increasingly allow opting out of data collection and limiting sharing through privacy settings. Meanwhile, crypto markets are hashing out royalty protocols for artists selling NFTs.

It’s a start - but we aren’t moving fast enough.

Considering AI will be used to create work that will manipulate and scam, creators face new IP challenges and threats. We will need to question the ethical use and protection of our works. Where are the datasets coming from? Is my work a part of it?

As this essay is endeavoring to show, you should be taking proactive steps to value, protect, and control your work. Don't surrender your intellectual property rights lightly - they form the foundation for your creative career. Build a personal brand, with digital assets, that you can own.

Be aware of the work you produce, and take the right steps to value your work correctly. Let’s reimagine an economic future that works for all of us.

Further Reading:

Many of the ideas here were shaped by the writing and influence of Yanis Varoufakis, Peter Drucker, Yokai Benkler, Lawrence Lessig, and Paul Mason.

This essay was researched, transcribed, and refined through a combination of improvisational takes using Otter.ai, and then with Claude v2 from Anthropic. Large portions were re-written by human, other sections are generative. Imagery created in Leonardo.ai's version of Stable Diffusion.

Nye Warburton is a creative technologist and educator. He lives in Savannah, Georgia.

TL;DR :: Artificial intelligence promises to completely transform every creative workflow. What does the need for creative talent look like in the game industry?

If we look to the past, we see three potential archetypes.

AI has Arrived

Notice the pixel art game level above? This image took 26 seconds for Stable Diffusion XL to imagine from my written prompt. Considering how fast AI is moving, it won't be long before I can write and manifest feature film quality shots. Game engine AI’s will produce, code, and make art for me to assemble.

Hard to accept, I understand, but AI has arrived.

Jeffery Katzenberg has indicated that 90% of movie production can be replaced by AI. Barring the IP and ethical data concerns with these models, that disruption figure will apply to every creative production endeavor.

In considering this rapidly evolving toolset, I give much thought to what the realities will be for "the generative game developer.”

For this essay, let's focus on the archetypes of talent.

“By talent, which is a word I hate, I mean … the ability to be productive.”

--- Gabe Newell, Cofounder Valve Software

Microstudios?

"Armed with generative AI tools and services, we will start to see more viable commercial games produced by tiny “micro studios” of just 1 or 2 employees."

Source :

The Generative AI Revolution in Games / James Gwertzman and Jack Soslow : https://a16z.com/the-generative-ai-revolution-in-games/

With so much getting abstracted by AI, what core talent will propel "microstudios" - tiny teams of 1-2 people creating commercially viable games, as predicted by Andreesen Horowitz above?

Looking back over decades, large specialized teams made rigid hierarchies. But startups build small, agile crews wearing many hats. As AI accelerates change exponentially, adaptability and skill blending will become essential.

Like the early days of film production, video games emerged from large studios. But formats like mobile gaming enable tiny groups fusing technical and creative strengths. A 100 person visual effects crew flattened into 10 versatile creators - programmers, writers and 3D artists in fluid roles. Looking ahead, digital workflows, seemingly engraved in stone for decades, must now demonstrate flexibility almost overnight.

If we think of AI not as new, but a rapid accelerant of what may has happened over 20 years, we can see a change in productive capacity--- a change that could continue to accelerate.

Three Archetypes for Microstudios

I think about three archetypal skillsets rising to prominence, especially from entrepreneurs and smaller companies. These may be individuals, or it might be that AI will require qualities of all three for every person.

For each archetype, it’s about problem solving for a specific area in developing a real time interactive experience.

1. Producer Designer

Someone (not an AI yet) has to have a killer idea.

This person will stop at nothing to will their vision into reality. AI will do the calendars and bug tracking, but vision must come from human passion.

The designer is not just the kid in the back drawing Mario maps, but someone who has learned to pitch and excite. Most likely, as an introvert, they had to pitch and excite regardless of pain. A builder, who is coordinating technically and socially.

These rare types bleed for their creative projects. As a result, the person who defies the horrors of game development to create an idea against the odds, is a hero for any team.

This will always be valuable, regardless of AI.

2. Technical Artist

The second type of archetype is the engineering artist.

For me, it's artists who understand not the art, but the workflow of assembling it. We often have artists who know one core set, but the ability to string together workflows across multiple software platforms is hugely valuable. The more technical the art, the more it tends to be because it is still developing, and the tooling is unwelcoming to use.

Narrow AI will exist as different software packages.

Software may give us some solutions, but the technical artist hacks the “unthought of.” There is a new problem to solve every day. Particle explosions today, tomorrow procedural bricks, NPC pathfinding the next. Lot's of things are unknown when you are imagining a virtual world, and the person who knows how to prototype it rapidly lays the tracks for the rest of the shop.

The technical artist will always focus on how to string it all together. Every day, they will need to reinvent and reimagine.

3. Community Player

Frustratingly, I find most students pretend playtesting isn’t part of development. Games are crafted through play – testing with yourself and others is how we understand the operational ability of the game we created.

We get better at building games by playing them.

The game player plays endlessly, providing feedback to the team on bugs but also suggestions. They build mods and assets for others to use. They run tournaments and build active discord channels. They become your viral marketing engine not just through word of mouth, but actively recruiting new users.

This player archetype will evolve into a prosumer, taking literal ownership for maintenance of the game. They will document and teach new users. They theory-craft and debate online. Quality Assurance and Inspirational show-off will be combined.

Take Away

Complicated workflows in game development, disrupted by AI, will likely focus less on a technical, but rather, human archetype skill:

• Producing Designer

• Technical Artist

• Community Player

I believe that AI will drastically reduce costs for all other production tasks.

Procedural worldbuilding tools, outsourced AI coding, project management, marketing, and infinite amounts of expansive content libraries will all be magically available. Platforms like Unreal, Niantic, and Google Maps may soon digitally replicate our world for us. Or maybe it will be something yet to be imagined? New techniques arise daily across Twitter, GitHub and YouTube. It’s near impossible to follow.

While job losses loom, smaller generative studios could rapidly propagate and flourish. (At least I hope so.) Students who look to the generative future, should double down on adaptability, problem solving, and human passion.

Monetization models remain uncertain. But if we understand workflows for generative creation like we do for writers or animators, incredible opportunities may emerge.

… Here’s hoping, anyway.

This essay was researched, transcribed, and refined through a combination of improvisational takes using Otter.ai, and then with Claude v2 from Anthropic. Large portions were re-written by human, other sections are generative. Imagery created in Leonardo.ai's version of Stable Diffusion.

This was an exercise that spanned over a few days at random improvisational intervals.

Nye Warburton is a creative technologist and educator. He lives in Savannah, Georgia.

The three components of a persistent, credentialed, global education network.

Trustworthy AI Education?

Artificial Intelligence will accelerate and democratize our ability to educate the entire planet. The pursuit of the global education ideal will potentially undercut the higher education business model. However, most concerning is the authenticity of the information AI will proliferate. (1)

We are headed towards a crisis of data accuracy and intellectual property ownership. (2) If AI is to be trained on the knowledge we feel is most valuable to us, we may be incentivized to build an infrastructure to validate it. Teachers must evolve to become authenticators.

To better visualize this, let’s imagine three components of a globally persistent teaching network.

These components are:

1. The AI teacher

2. The Reputation Nodes

3. The Identity Guilds

The AI Teacher

ChatGPT awoke the planet to AI's potential. Developers around the world are experimenting with Large Language AI Models (LLMs). In a short time, AI-powered chatbots will be everywhere, across every industry.

These chatbots may gain traction with documentation and support. Google has road-mapped the rollout of its documentation AI. (3) The blockchain we work with, Solana, is already using AI chatbots to serve up documentation to their developer base. (4) AI will undoubtedly be our internet search companion. (5)

Full-on education, is not far behind.

Kahn Academy is taking a bold step forward using GPT4 with their educational chatbot "Kahnmigo." (6) Duolingo, a language learning platform, has developed its own approach to the model. (7) These aren't just companies providing support documentation for a product. The knowledge these kinds of platforms provide IS the product.

The previous wave of chatbot hysteria turned out to be mostly-canned responses, in an if/then style framework. (8) These new bots, powered by super language models, will promise understanding, adaptability, and provide confidence to the students as they learn.

It's not just curriculum, it's teaching.

AI Teacher: A persistently accessible intelligence that teaches, gamifies curriculum, and credentials an individual with an internet connection.

While language models power the curriculum, generative video can visualize the front end. There is already ample evidence of AI video creation. Synthesia and Movio are two of the early movers in this space. (9) For a monthly price, you can generate a variety of customizable near-human avatars. Admittedly a bit “uncanny valley,” but there is little doubt that the fidelity of the performance will grow to be the face of our AI mentors.

As a teacher, my work consists of me writing lectures, demos, and workshops to perform at a preordained time within a classroom. I get paid by a credentialed institution for this labor. In a few short years, this content will be entirely fed to language models, which will do the teaching instead.

So, what happens to the credentialed institution?

Reputation Network

AI models sometimes lie. They don't mean to. In fact, they don't even "mean". They are simply making an increasingly accurate series of guesses. My email prediction often guesses my responses incorrectly. How accurate will the fully generated New York Times essay be?

In the AI world, the wrong guess, despite reading and feeling accurate, is called a hallucination. (10)

In education, hallucinations are an insanely dangerous thing. We have already seen what falsehoods do to politics. This could be far worse. If AI teachers are to proliferate, there will need to be a way to credential their knowledge. Users will need to know the authenticity, and trustworthiness, of the system.

Universities are credentialed by legally audited centralized organizations. Having these credentials allows universities to become, in the eyes of the law, the rightful issuer of a highly prized subject matter degree. Bachelor, Associate, and Master are all signatory values of accomplishment. They provide evidence to an employer that the student has "mastered" a curriculum of skills. (11)

But soon our curriculum will be lost in the latent space of an AI supermodel. (12) How can a human organization possibly regulate it?

Let's imagine an immutable ledger that tracks the transactions of nodes in a network. Nodes on this network can gain reputation, and thus value, with measured transactions.

Bitcoin has a fiat value. Ideas and artwork have value too. Value can be knowledge, skill, or authority --- Intellectual Property.

What if the top writers, the top artists, the top game players, and the most fabulous fashion models peer-review one another?

Could this be the source of truth?

Reputation Network: A council of peer-reviewed, highly valuable nodes on a blockchain network.

As I watch the development of the web3 ecosystem, I see the emergence of Decentralized Autonomous Organizations. Generally, these organizations are online professional communities that sometimes incubate grant voting systems. (13) Most have not found an operational structure.

But what is increasingly evident is that the success of a DAO may not be the massive number of participants that get pulled into a large-scale fundraiser, but the recruitment of a highly productive few who step up to be the leaders of the network. (14) These leaders provide authority and increase the desire of others to join a valuable organization. The nodes of the thought leaders create the reputation, and thus value, of the network.

If these DAOs do find a path to operation, perhaps they could be used to manage these reputational nodes and provide authenticity to the AI teacher.

The reputational nodes are the most valuable of the network. But valuable to whom? How do we define the network and the subject matter of the data within?

Identity Guild

I spend my time in the communities that reflect my identity.

I am a writer to some. A game developer and animator to others, and still again, a beer-loving drinking buddy to others. I spend time in places IRL or in discord, because I enjoy it, and I enjoy sharing my value with others. My identity is multifaceted, operating slightly differently in each, but also as a unified whole.

During the Renaissance, much of the art, research, writing, and philosophy was empowered within officially recognized guilds. These were collections of like-minded thinkers who had the legal authority to defend an art form’s intellectual property, but also the application and tooling of their livelihood. (15)

If I were a young fresco painter, I might apprentice myself to a journeyman, or move to the city to join a powerful guild. It would be the reputational way for me to make a pledge to an art form, and work my way through (hopefully up) the system. Guilds offer financing and support. They also create networking opportunities, which is really the point of creating a network.

However, one can not research guilds without discovering economic criticism. The largest argument I see is that guilds centralize and plateau knowledge. It's the age-old fallacy of "once in power - resist the change." To the rabid capitalist, guilds delay innovation, suppress outside entrepreneurial work, and form unhealthy reliance on the centralized state. (16)

But let's imagine if a guild network cultivated its own AI teacher, shepherded by the reputation nodes. Everyone who was in the guild had access to the most current ideas through AI. New entrants could be gamed from apprentice to master.

I suspect that guild structures are the natural formations of creative humans. Check the history books, we've done it a lot. (17) It's part of the cycle of centralization and decentralization. We have a king, and then we get sick of it --So, we democratize and vote on stuff.

Companies are started by Steve Jobs and Steve Wozniak, but nations are started with a document that says "We the People." By declaring who they are, a guild may create legal backing to do the things they wish to do as a collective.

They declare their identity.

Networks pull in people who seek identity. By declaring participation in an identity guild, they collaborate to defend it.

Education will change

If AI is to teach us, we need to put systems in place to authenticate and protect its data. Those who are most passionate about their identity will create the strongest guild governance. The reputation of that guild will depend on the nodes that lead it.

If the system can come to balance, potentially, the creation of credentialed AI will be the most trusted in its domain.

Decentralizing control over knowledge may be our only hope for trusted AI. If we rely on centralized, and potentially biased authenticity, the result could be disastrous.

Nye Warburton is an animation technologist and educator. This essay was written in collaboration with the BanklessDAO Writers Guild. Header image generated by the Stable Diffusion Platform Leonardo.ai. Text and essay imagery were written and designed entirely with the human labor of the author. (April 2023)

web2: https://nyewarburton.com web3: https://mirror.xyz/nyewarburton.eth

Notes and Reference

(1) Most concerning is the authenticity of the information AI will proliferate. | Artificial Intelligence: An Accountability Framework for Federal Agencies, Public Release (June 2021)

*(2) We are headed towards a crisis of data accuracy and intellectual property ownership. * | Key challenges of artificial intelligence. Intellectual Property: Protecting your AI and its creations, Ertugrul Akinci, Kargan Dora, and Allison Bender, Business Going Digital

(3) Google has road-mapped the rollout of its documentation AI. | A new era for AI and Google Workspace, March 14, 2023

(4) The blockchain we work with, Solana, is already using AI chatbots to serve up documentation to their developer base. | Ask Solana U, an AI Chatbot for Solana Development

(5) AI will undoubtedly be our internet search companion. | Reinventing search with a new AI-powered Microsoft Bing and Edge, your copilot for the web, Yusuf Mendi, February 7, 2023

(6) Kahn Academy is taking a bold step forward using GPT4 with their educational chatbot "Kahnmigo." | Introducting… Kahnmigo, Kahn Academy Help Center

(7) Duolingo, a language learning platform, has developed its own approach to the model. | Duolingo is now equipped with GPT-4: Here’s what it can do for you, Sabrian Ortiz, March 15, 2023

(8) The previous wave of chatbot hysteria turned out to be mostly-canned responses, in an if/then style framework. | Example: Chatfuel.com

(9) Synthesia and Movio are two of the early movers in this space. | Example: synthesia.io | movio.la

(10) In the AI world, the wrong guess, despite reading and feeling accurate, is called a hallucination. | “What Makes AI Chatbots Go Wrong?”, Cade Metz (The New York Times On Tech)

(11) They provide evidence to an employer that the student has "mastered" a curriculum of skills. | We don’t value Education. We value the Credential, Brandon Busteed, Forbes

(12) But soon our curriculum will be lost in the latent space of an AI supermodel. | Understanding Latent Space in Machine Learning, Ekin Tiu, Towards Data Science

(13) Most of these organizations are professional communities, perhaps with some grant voting systems. | Example: Nouns.wtf | Bankless DAO

*(14) But what is increasingly evident is that the success of a DAO may not be the massive number of participants that get pulled into a large-scale fundraiser, but the recruitment of a highly productive few who step up to be the leaders of the network. * | A Hyperstructure for Learning, Courtland Leer

(15) These were collections of like-minded thinkers who had the legal authority to defend an art form’s intellectual property, but also the application and tooling of their livelihood. | Medieval Guilds, World History Encyclopedia

(16) To the rabid capitalist, guilds delay innovation, suppress outside entrepreneurial work, and form unhealthy reliance on the centralized state. | The Problem with Guilds, from Silversmiths to Taxi Drivers, by Justin Fox, Harvard Business Review

(17) Check the history books, we've done it a lot. | “The Square and the Tower: Networks, Hierarchies and the Struggle for Global Power, Niall Ferguson, Penguin, 2018

Digital Artists are rarely rewarded with intellectual property ownership. The blockchain may provide an alternative.

Centralized Production

In 2012, the world marveled at the film adaptation of Life of Pi. The key to this film, was the performance of its tiger co-star. Unable to get an animal like this to perform, (and the dangers associated with it) the film enlisted the help of visual effects firm Rhythm and Hues. R&H, as it is known in the industry, created a fully virtual tiger, by designing musculature systems, complex fur shaders, and had some of the world's most adept digital animators create believable feline movement.

For the work done on this film, the visual effects supervisors and the top talent of R&H won a prestigious BAFTA and an academy award. It was one of the greatest achievements of computer graphics at that time.

But Rhythm and Hues went chapter 11. Everyone who worked at R&H was out of a job and adding to the insult, the production of the film simply ignored it (1).

How can a group of some of the most talented artists and technicians from around the world, collectively make one of the most creative and technical endeavors ever seen on a screen …

... and go out of business?

Royalties

The writers guild, or WGA, was formed in 1921 to "protect and promote the craft of writing for the screen." It was forged from the anger of early Hollywood screenwriters who demanded proper credit and recognition --- or simply termed "Attribution. (3)" Writers, who are lucky enough to sell a script in Hollywood, join the writers guild to enforce a trail of royalties for the scripts that they write. For example, Larry David and Jerry Seinfeld get regular paychecks every time their show about nothing goes on the air (4).

Similar organizations have been designed for musicians and composers. Organizations like these were formed in the early days of the film industry when large conglomerates didn't have the centralized control they do now.

Visual effects were late to the party.

Any new discipline invented after the 1970s had difficulty organizing into a protective union. As such, the unionized craft services who put bagels on set, are ranked higher in the end credits than the people who make the monsters and superheroes that dominate the movies today.

The studios maintain complete control of the intellectual property. In this model, legally, a weekly rate compensates the imaginative labor needed to build these multimillion-dollar experiences. There is no rev-share in this model, and the weekly rate for these artists has stagnated over the years**.** It is often not enough to get a single-studio apartment in Los Angeles (5).

The legal mechanisms for protection exist, but have been systemically decimated. Effectively, I believe, it's too late to unionize.

However, our tools might provide a new opportunity.

Software eats Entertainment

The near entirety of the entertainment pipeline is now digital.

In the 90s, we saw the maturation of 3d animation, which replaced traditional animation and stop motion. Compositing evolved from bulky multiplane camera setups to a sleek node-based software. Now, real-time graphics, driven by powerful game engines, are driving the current evolution (6).

The Unreal Engine from Epic Games is becoming adopted by visual effects, animation, and virtual production houses at an astounding rate. Be it Disney's Mandalorian, shot on giant "extended reality" stages, or AAA game cinematics with near-human meta-characters, entertainment is going entirely real-time (7).

Teams are setting themselves up to develop real-time content by operating less like in-studio individuals, and more like a distributed team of contributors. Using a game engine as the hub of a project, asynchronous teams can collaborate while being distributed across the globe.

To coordinate the work of hundreds of workers, game engines like Unreal rely on version control which saves the code on a server. Individuals can be granted access to a repository that holds the project, allowing them to "check-in" updates and "pull" the latest project at any time of day or night. Someone might be updating the trees or environments, while someone else is working on the character systems. This asynchronous work has proven to be an accelerant, and is replacing the need for traditional on-ground studios (8).

As developers are onboarded, they are granted access to the code repository. As they push their updates, the version control tracks the addition. Access is granted with permission profiles attached to email addresses.

Perhaps contributors could use a cryptographically secure address instead. By tracking each commit, it becomes an ongoing immutable resume of the work.

This cryptographically secure address could be secured on the blockchain.

Attribution on the Blockchain

An artist can sell a painting for 600 dollars to a collector. But the collector, with the network of other investors, could turn around and sell the painting for 10,000. The next collector could turn around again, and sell the painting for 100,000. The painter, who has generated extraordinary value for this ecosystem, gets no percentage of this.

This age-old debate has come to a head in blockchain art marketplaces, as artists who sell their works as non-fungible tokens gain income on royalties from the secondary markets. These royalties, however, can not be defended entirely by code in an open market.

Centralized marketplaces, like Open Sea or Magic Eden, which have the opportunity to control the royalty protocols, must decide whether to lure artists with the defense of royalties or allow the open market to skirt them (9).

While this debate rages in the marketplaces, I consider only a single Unreal project and its contributors. Onboarded together, they can commit themselves to honor a set of attribution protocols for the network.

Attribution is the cornerstone of legal defensibility. This, combined with the blockchain, comes the ability to permanently track the contributions.

What compels me now, is that the technology exists to do what I suggest. A typical AAA game pipeline runs the Unreal Engine with a version control software like Perforce. The leap that I hope we make, is to connect this development to Solana, (IMHO) the only layer one blockchain with the transactional speed to support a real-time graphics ecosystem (10).

There is still much to do. The web applications and protocols to govern this endeavor are barely imagined. While it is clear we can gather the attribution of who worked on the project, determining owner percentages and the value of the work itself will be an ongoing debate for years to come. With AI on the horizon, the time to act is now. Let’s create new IP ownership models that will responsibly reward creatives for the work that they do.

There was never a union for creatives who worked on Life of Pi. I believe that it is now too late for there ever to be an effective real world one.

However, the blockchain may offer a new hope... (11)

Nye Warburton is an animation technologist and educator. This is the final post written in participation with the Bankless Academy Writers Cohort. Everything in this article was written and drawn with human labor. (February 2023)

Visit online @ http://nyewarburton.com

Links and Attribution

1. Life After Pi - The Documentary about Rhythm and Hues - https://www.youtube.com/watch?v=9lcB9u-9mVE

2. Bambi vs Godzilla, On the Nature, Purpose and Practice of the Movie Business by David Mamet - https://www.amazon.com/Bambi-vs-Godzilla-Practice-Business/dp/1400034442

3. Writers Guild of America - https://www.wga.org/the-guild/going-guild/join-the-guild

4. Jerry Seinfeld's Royalties - https://www.bosshunting.com.au/hustle/jerry-seinfeld-net-worth/#:~:text=Jerry Seinfeld and Seinfeld co,of points to 15%25 apiece.

5. Computer Graphics Salary for Artist - https://www.salary.com/research/salary/offering/artist-computer-graphics-animation-salary/ca#:~:text=Using the salary calculator%2C the,%2Fweek or %245%2C981%2Fmonth

6. Game Engine Market Size - https://www.globenewswire.com/news-release/2022/12/20/2577443/0/en/The-Global-Game-Engines-Market-size-is-expected-to-reach-5-9-billion-by-2028-rising-at-a-market-growth-of-14-6-CAGR-during-the-forecast-period.html

7. Real Time Round Up - https://www.unrealengine.com/en-US/blog/real-time-roundup-the-growth-of-interactive-3d-and-emerging-2021-trends

8. The advantages of Perforce - https://softwareengineering.stackexchange.com/questions/85845/why-big-companies-use-perforce

9. Magic Eden Launches Protocol to Enforce Creator Royalties - https://www.coindesk.com/web3/2022/12/01/magic-eden-launches-protocol-to-enforce-creator-royalties/

10. Solana - (IMHO) The Layer 1 blockchain fast enough to support real time graphics - https://solana.com/

11. Blockchain and the New Architecture of Trust by Kevin Werbach - https://www.amazon.com/Blockchain-Architecture-Trust-Information-Policy/dp/0262038935

We've spent a decade gamifying engagement in education, work, and health. Empty points are short-term dopamine hits.

Maybe we should gamify our reputations.

The Disengagement Crisis

Since the pandemic, the data has shown a disturbing trend in our society.

We're disengaged.

According to a recent article in the Chronicle of Higher Education, there is a crisis in student engagement with the university communities, describing students as losing "their sense of purpose for attending. (1)"

This trend is not limited to our universities. Whether it's quiet quitting, or mass layoffs, the trust and satisfaction of work are plummeting. Our youth is spending more time on social media than ever before, but feeling more lonely and disconnected. You can find concern over the disengaged in infinite numbers of human resource blogs, educator conferences, and the Twitter feeds of business strategy gurus (2). Disengagement is a five-alarm problem for almost every organization.

However, there is one vertical that doesn't seem to be having this problem.

Gamifying Engagement

You've heard this before, but let's review it. Gaming is exploding. More and more people are spending more and more time each week playing games (3).

Over a decade ago, we saw an independent gaming revolution. Powered by Valve's Steam distribution, and Apple's app store, game design went mainstream. Everyone was playing Angry Birds, and Jane McGonigal's Reality is Broken was a best seller (4).

An avalanche of start-ups used game design principles to incentivize engagement with health, education, and work. Multinational corporations integrated "engagement gamification" into their strategy. Every supermarket rewarded us with points and badges. Education companies of all sorts participated in this movement.

It worked! ... Or did it?

You tell me. Every year I read research papers that show that games can be used to increase engagement in education (5). So, where is it? I'm beginning to wonder if it's the engagement that's the problem.

A pedagogy might be in direct opposition to what successful game design might be. Teachers are giving students educational games to play at school. There is more engagement, but the evidence shows that when they get home, they fire up the console and play "real" games.

Alternatively, I have seen a handful of professionally produced games used as tools to teach. Valve released a version of Portal, for students to use in the classroom. Everyone's favorite voxel builder branded and grew their Minecraft Education to 7000 classrooms across the United States (6). And Epic Games, using Fortnite's sandbox-like qualities, have launched several initiatives to support coding camps and game jams of all sorts (7).

Games are fun, and I have no doubt engagement increases. However, the long-term efficacy in education is inconclusive (8). Education and Entertainment are like oil and water because they are still the division of work and play. They have never been able to mix into a singular product.

To make them mix, we need to change the composition of each of them.

I suspect we have misunderstood what it takes to engage someone. The critical element missing from the conversation is that the games with the most engagement are not necessarily fun, but jam-packed with consequences. When your character dies, it matters. Empty points are short-term dopamine hits.

We need to incentivize people to level up the best version of themselves.

Gamifying Your Reputation

You are reading my third essay written for the Bankless Academy Writers Cohort (9). I didn't pay money to participate or get paid to write this. I volunteered to do this agony they call "writing." My motivation to write out my ideas is largely self-directed, but the sprint structure has given me railings to hold on to.

Like meeting your buddy at the gym, participating in a cohort provides collective support. It's made up of other like-minded writers, who are given weekly milestones. However, what I find increasingly interesting, is that we have a cryptographically secure wallet tied to our participation.

Yes, the blockchain is rife with scams, speculation, and overhyped marketing cycles. It is also seen in the rise of tokenized communities driven by a mission. There are non-web3 cohorts that are essentially online classes, but the potential of web3 combined with this cohort mentality could be different.

The success of these communities, like everything else, depends on engaged participants. These communities don't just have gamification programs, they incentivize using crypto. We created the concept of a wallet when crypto was all about coins, but a wallet is only an address that specifies the location of a transaction encoded on an immutable ledger.

In theory, participants can be rewarded by protocols.

For example, proof of active participation (POAP) is an indication that your wallet was there. Other protocols could be developed for hitting milestones on the deliverables. With collective tokenization, participants could be rewarded with ownership or status (10). If I put all of my writing activities from this cohort on the Ethereum blockchain, it's tied to the wallet address I used, forever.

Most gamification approaches have short-term effectiveness. Perhaps motivation may increase if we tied those same principles to a permanent resume of activity. I can showboat on Linkedin, but nothing is backing up my accomplishments. The blockchain, however, is no joke. When something is on the chain, it's there for good. Points are nice, but we care about our long-term reputation.

Isn't that why we engage with universities? We want that degree to mean something. Isn't that why we put that extra time into work? We care about being the best. Motivated correctly, we work because we want the attribution for what we did.

For all the arguments that crypto is complicated to use, some speculate we will have a billion wallet addresses by 2030 (11). The participation of a billion people, organizations, schools, and businesses, all with trackable engagement is coming very soon.

If learning and work-related transactions become a metric for engagement, we might be able to adopt the principles of gamification that worked in the short term, to become a driving force for the economy in the permanently engaged one.

Nye Warburton is an animation technologist and educator. This post was written in participation with the Bankless Academy Writers Cohort. Everything in this article was written and drawn with human labor. (February 2023)

Visit online @ https://nyewarburton.com

Links and Attribution

1. “their sense of purpose for attending” - The Chronicle for Higher Education:

   https://www.chronicle.com/article/a-stunning-level-of-student-disconnection

2. “The Disengagement Crisis” - Fortune Magazine:

   https://fortune.com/2022/12/23/disengagement-crisis-quiet-quitting-tacit-termination-eric-sydell/

3. “Gaming is exploding” -

   https://financesonline.com/number-of-gamers-worldwide/

4. “Reality is Broken" by Jane McGonigal -

   https://www.pdfdrive.com/reality-is-broken-why-games-make-us-better-and-how-they-can-change-the-world-e197940653.html

5. “Games can be used to increase engagement - study” -

   https://slejournal.springeropen.com/articles/10.1186/s40561-019-0098-x

6. “Minecraft Education in 7000 classrooms” -

   https://www.fastcompany.com/90666530/fortnite-minecraft-education

7. “Fortnite for Education” -

   https://www.unrealengine.com/en-US/blog/learn-how-to-teach-with-fortnite-creative-in-your-classroom

8. “Gaming in Education is Inconclusive” -

   https://maestrolearning.com/blogs/what-happened-to-the-gamification-revolution/

9. The Bankless Academy Writing Cohort -

   https://writers.banklessacademy.com/

10. "The Blockchain and the New Architecture of Trust" by Kevin Warbach -

    https://www.amazon.com/Blockchain-Architecture-Trust-Information-Policy/dp/0262038935

11. “Some speculate we are on track for a billion wallets by 2030.” -

    https://beincrypto.com/digital-wallet-use-track-reach-65-global-population-2030-ark-invest/

The more modular our content becomes, the greater the potential for infinite, hyper-personal, storytelling.

That's if the system allows it.

BEDTIME STORY

Every night, I make up a bedtime story for my kids.

The first night was a joy, but I ran out of content after two weeks. If I were to do this every night, I needed to develop a system to generate stories.

At that time, my boys loved Paw Patrol, an animated action show about a group of talking dogs who represented seven municipalities. Marshall, the dalmatian firefighter, is armed with a retractable water cannon. Chase, the German Sheppard cop, is the team's lead and the detective (1). All of them have their place in the plot, based on the character's traits.

When you know the structure of Paw Patrol, you can easily stitch together a story. If you use Marshall, then the plot has a Fire. The creative utility of each Paw Patrol character allowed me to improvise bedtime stories for several weeks.

But, content has a half-life.

Not only did the stories become repetitive, my boys got bored with the show. Needing ideas, I stole everything they consumed. The stories became increasingly modular, allowing me to take the gang from My Little Pony, pit them against Magneto, and put them in Gotham City.

By determining the variables of a story framework, I could randomize them. Admittedly, most stories were terrible, but once in a while, the combinations were perfect for the boys. We did a week where Spiderman fought Darth Maul, and for two months, a slew of the stories took place in Minecraft.

As a father, I've enjoyed this time with my boys. As a game developer with an interest in blockchains, I call this practice interoperable entertainment. This is what some see as an emergent form of new media, where the components of an entertainment system are standardized and organized to be interchangeable.

Up until now, our content has been linear, rendered*, and licensed.* But what if all of the characters of any show, comic, book, game, or trading card were up for grabs? The combinations would be infinite.

Sounds cool, right? Why don't we do this?

THE LEVEE OF COPYRIGHT

Earnest Cline's Masterpiece, Ready Player One, is a dystopian vision of a persistent virtual world. The key component to the book's "metaverse" is the pop culture references that span video games, books, anime, movies, and music (2).

Steven Spielberg was tapped to direct the 2018 film adaptation. While Cline wrote with a legal right to reference Monty Python and Activision games, Spielberg's production needed to clear the intellectual property rights for all of the characters. Spielberg estimated that the team was able to get "about 80% of the copyrighted elements they desired.* (3)"* This is mainly because the director was, well, Steven Spielberg. Outside of the occasional Roger Rabbit, making these kinds of "cross-over" character plots is legally impossible to do in the movie industry.

We can't mix Doctor Doom and Superman because DC/Warner and Disney/Marvel are rivals. If Doctor Doom were to develop kryptonite weaponry, Superman would need to study the occult. Despite how enormously awesome this sounds to the nerd inside me, this is a legal quagmire of copyright law.

Harvard legal professor, Lawrence Lessig, argues the pros and cons of copyright in his 2002 book, The Future of Ideas. In it, he defends copyright as a benefit for the individual artist. However, he makes a strong case for the rethinking of copyright law, by using numerous examples of media companies using legal action, not for the protection of ideas, but for market control. According to Lessig, this kind of behavior suppresses innovation, especially in a networked economy (4).

Disney holds a vault of high-value, creative utility characters, controlled by rigid intellectual property. Mickey, Muppets, Buzz Lightyear, The Avengers, and Star Wars. All of it is family-friendly, and all of it is under piles and piles of legal contracts.

The justification for this legal position is to defend the standards of a Disney product. They don't let "just anyone" do a Mickey Mouse cartoon. One must be granted the privilege. Paying for a high-end character or story license is expensive, and often you need to slice off a sizable percentage of the "back end (5)."

The entertainment industry has the same issue I did, lying on the floor of my kid's bedroom. Companies may have a huge library of characters, but keeping it interesting and fresh requires massive amounts of storytelling labor. To continue to dominate the family-friendly market, they need to develop more content.

... infinitely exponential, amounts of content.

THE COMING FLOOD OF CONTENT

The technology to create interoperable entertainment already exists. The entirety of animation production is in software. Characters are not just ideas, but sets of digital files that allow artists to animate and develop content.

The animation pipeline was reinvented with the advent of 3d computer graphics. Thirty years of development led to multimillion-dollar animation franchises and massive AAA game worlds (6). Graphics tools became pervasive and accessible. Now, anyone can download and program AAA quality video games in a real-time engine on a personal computer... for free.

The number of marketplaces that support the development of interoperable, real-time-ready, graphical assets has drastically risen. The game engines, Unity and Unreal, have marketplace cornucopias of environments, characters, animation packs, and procedural game systems (7). On the internet, one can find services to capture motion, retarget, and rig characters. The only limits are the time and labor it takes to invent interesting graphics content.

The massive video game economies are based on the high volume trading of “in-game assets.” In these systems, i**nteroperability is the economic foundation (8). **The community builds and sells, not to content consumers, but to other developers.

With AI and blockchains easily accessible, millions of content developers will create characters and instantly license them in smart contracts (9). If characters and world components are standardized, the acceleration of mixing and remixing will be insane. Open-world blockchain initiatives like Otherside and Sandbox might point to the multi-brand character world imagined in *Ready Player One (10).*

Never in our history has there been so few media outlets controlling all of the monetized content (4). Never in our history has so much non-market content been created. Copyright - as it exists now in the entertainment industry - is facing a crisis.

"If it keeps on rainin', levee's goin' to break (11)." - Led Zeppelin

STORYTELLING IS ACTUALLY...

In Disney/Pixar's Toy Story, the action figure Buzz Lightyear wasn't the hero in the TV show it was based on. It was Andy's Buzz Lightyear.

We change the characters we love, and make them our own.

As they've gotten older, my boys have been active participants in my nightly storytelling, challenging me with weird characters they make up on the spot. We have so many subplots and callbacks, our stories have become an inside joke. Only the three of us understand the value of these stories, and that’s what makes them special.

Perhaps the hyper-personalized nature of interoperable entertainment will make stories that aren’t for everyone, but valuable to those who are closest to us.

*Nye Warburton is an animation technologist and educator. This post was written in participation with the Bankless Academy Writers Cohort. Everything in this article was written and drawn with human labor. (February 2023) *

Visit Nye online @ https://nyewarburton.com

Links and References:

1. Paw Patrol:

   https://pawpatrolandfriends.com/

2. Ready Player One, by Earnest Cline:

   https://www.amazon.com/Ready-Player-One-Ernest-Cline/dp/0307887448

3. Spielberg got 80% of the rights:

   https://en.wikipedia.org/wiki/Ready_Player_One

4. The Future of Ideas, by Lawrence Lessig:

   https://dlc.dlib.indiana.edu/dlc/bitstream/handle/10535/5710/lessig_FOI.pdf

5. Bambi vs Godzilla, by David Mamet:

   https://www.amazon.com/Bambi-vs-Godzilla-Practice-Business/dp/1400034442

6. Masters of Doom:

   https://www.amazon.com/Masters-of-Doom-David-Kushner-audiobook/dp/B008KGXM6A/ref=sr_1_1?crid=ILY4YEDFCU49&keywords=masters+of+doom&qid=1675189206&s=books&sprefix=masters+of+d%2Cstripbooks%2C111&sr=1-1

7. Epic Marketplace:

   https://www.unrealengine.com/marketplace/en-US/store

8. Gabe Newell: Reflections of a Game Maker:

   

9. The Metaverse, by Matthew Ball:

   https://www.amazon.com/Metaverse-How-Will-Revolutionize-Everything/dp/1324092033/ref=sr_1_1?hvadid=590808456850&hvdev=c&hvlocphy=9011283&hvnetw=g&hvqmt=e&hvrand=10871800841693613355&hvtargid=kwd-1646057524798&hydadcr=22566_10355100&keywords=the+metaverse+matthew+ball&qid=1675189311&sr=8-1

   https://www.nvidia.com/en-us/omniverse/creators/?ncid=pa-srch-goog-594896#cid=ov01_pa-srch-goog_en-us

10. Blockchain Worlds, Otherside, and Sandbox:

    https://decrypt.co/resources/what-is-yuga-labs-otherside-inside-the-bored-ape-yacht-club-metaverse

11. When the Levee Breaks by Led Zeppelin:

    < https://www.youtube.com/watch?v=uwiTs60VoTM>

If we are to defend our creative data from being sucked into large centralized AI models, we may need a new ethos and behavior.

THE AI SOFTWARE ECOSYSTEM

In a recent interview, Sam Altman, the CEO of Open AI, foretold a vision of how companies with multimillion-dollar processing power will sit at the base of a new artificial intelligence software ecosystem. (1) A gold rush of smaller companies, will use the APIs and "tune" these massive models to provide customizations for specialized markets.

For example, if I were a comedy writer...

I might query a paid service that is built upon Open AI's chatGPT. The large language model would provide the sentences, structure, and logic. The service --- tuned with, say --- 80's stand-up comedy routines, could provide the timing and personality. The prompt would return a killer routine, with little effort from the comedy writer.

This is not fantasy, this is happening. (2)

In December, a panic among visual artists in the Art Station community led to many placing an iconic "No to AI-Generated Images" within their portfolios. (3) This month, (January 2023) the first of many class action lawsuits have begun. (4) Our government may attempt to make policy, but the angry artists are already mounting an attack on large tech organizations.

Even if traditional legal actions are successful, "slaps on the wrist" will do nothing. The graphics company, Adobe, has been aggregating user data to train their own AI models. The legal on Adobe's site points to the "opt-out" function, where users could select not to have their work part of a training set.

Of course, everyone on Adobe's Creative Cloud is opted in... by default. (5)

WHAT CAN BE DONE?

It's clear to me that my days of animation labor are numbered.

The models may be imprecise and difficult to control now, but from what I see in my research, I do not doubt what is to come. I can not opt-out or go silently into a data set.

I've begun to ask myself:

As a creative, is there something more tangible I can do than simply support traditional legal action?

Could I participate in a new ethos that would allow the productivity of AI tools, without surrendering ownership of my work?

As an environmentalist practices sustainability, perhaps generative artists can practice defensibility. I am pursuing three ideas, though a solution is not readily visible.

My instinct is that, perhaps, these ideas point in the right direction.

OPEN SOURCE

Open source is the act of making an idea publicly accessible. Open Source software, distributed for free, and combined with network effects, may yield new economic models for collective production. Wikipedia, Android, Blender, Apache, Linux, Python, Rust. These are not companies, but open networks of production. (6)

Open Source built the internet. It began peer-to-peer. It was messy, creative, and unstandardized. Software, free from control, can evolve. (7) Open Source becomes the public forum, the language for us all to use, where no one entity makes all the money.

Our new AI software ecosystem is being born, not peer-to-peer, but centralized. It too is messy, creative, and unstandardized. While we are developing this new ecosystem, perhaps we could allow the technology to mature, free from control.

Emad Mostaque's vision is just this. His company, Stability AI, builds open-source alternatives (like the image generator Stable Diffusion) in a hope that it can "de-risk" the centralization of AI from doing serious harm. Imagine if AI were a "public good."(8)

Stability AI is, in effect, another centralized company. What's different, however, is that I can download the model on Git Hub. (9) Because it is open source, many others have customized it. Using community-created code, I can tune Stable Diffusion to my needs.

This democratizes AI and empowers creativity across the world. This is why I skew open-source AI whenever possible.

But even if open, the art I create still needs to be ... my art.

PERSONALIZATION

AI needs a lot of data to train, but it also needs customized data to focus. I can prompt an image and get pretty close to the desired result. However, to prompt an image and make it look like me, needs custom tuning. (10) This requires customized data sets and affordable processing power.

Companies are now rushing to satisfy this personalization for users. With the APIs of the large models available, it's up to them to determine the specific market fit and provide that service.

But the concern of data collection still applies.

With AI models, you turn yourself into a superhero, but the cost may be, that your likeness no longer belongs to you. (11) For us to patronize these new entrants into the AI ecosystem, trust, more than the product, will become the critical selling point.

Recently, I discovered a company called Personal.ai. CEO, Suman Kagnuganti founded the company to focus on data privacy and ownership. Their product, effectively a chatbot system, is built on a sort of "vanilla" language model where you add your data. It is designed to be trained with personalized "memory stacks", so your bot becomes you. (12)

As a teacher, I can potentially put everything I know about animation technology into a personal AI chatbot. I spend a large percentage of time helping students through chat, how much time would I get back if all of my most asked questions were instantly answered?

But the value of this company, for me, is not AI. If I choose to use it, it's because Personal.ai has built its application on the Oasis protocol.

Oasis is built on the blockchain. (13)

BLOCKCHAIN

The blockchain is currently home to speculative collectors and retail investing "apes." It might soon mature into an automated lawyer that tracks our transactions. (14) There is a misconception that the cryptographically secure blockchain will allow for the "protection of a digital file," like a super un-hackable database. This is incorrect.

Its value is the immutable record that proves exactly, where and when, we added our creative labor. The dream is that we can defend our contribution on a transaction-by-transaction basis. An artist brought something to life, and an artist should get a piece of that something's intellectual property.

Artists are selling NFTs now, but beyond speculation, there is little economic utility. Theoretically, protocols are being developed that trigger when the virtual asset discovers its utility value. (15)

Ideas take time to gestate. The software takes time to mature. If art is not "ready," the components could be distributed and tracked until the time that it is. And should that rare collective "genius" strike, the contract could trigger at that moment and retroactively monetize the entire development process.

The blockchain space is a massive essay in itself. They are potentially more complicated to understand than the artificial intelligence models I hope they can decentralize. Despite the complexity, I have watched with optimistic hope, as the blockchain marketplaces on Ethereum and Solana argue over smart contract protocols that defend the royalty traits on Non-Fungible Tokens. (16)

I don't understand the specifics, but I know that somewhere within this debate lies a new way for artists to monetize their ideas. Within this debate will form new collaborations and royalty splits, and the collectivism in production will potentially decentralize our data away from singular interest.

If we figure it out in time.

WE NEED TO HURRY

Open Source. Personalization. Blockchain.

These are guesses, but we need to start somewhere... and we need to hurry.

No one has fully automated themselves - or have they? But as soon as we see others turn into productive superhumans, I am fairly sure, we will all be quickly motivated. No one wishes to be left behind.

And if we have no choice but to use AI to accelerate ourselves, we must behave in a way where we don't give our creative data to a centralized entity to do it.

If you believe this to be alarmist speculation, then I thank you for your time. If you believe, as I do, that this is a transformative period in human history, I welcome you to reach out. These are merely the guesses of a single animator.

With open debate, perhaps together, we can create a new ethos for a beneficial future -- if it exists.

Nye Warburton is an animation technologist and educator. This post was written in participation with the Bankless Academy Writers Sprint. This essay was written and drawn with the human labor of the author. (January 2023)

Visit online @ http://nyewarburton.com

Notes and Attribution:

1. Sam Altman Interview -

   

2. "This is happening." - NovelAI -

   https://novelai.net/

3. "No to AI images on Art Station" -

   https://dataconomy.com/2022/12/no-to-ai-generated-images-artstation/

4. "The first of many class action lawsuits" - https://www.theverge.com/2023/1/17/23558516/ai-art-copyright-stable-diffusion-getty-images-lawsuit

5. "Adobe legal opting in and out" -

   https://www.artificialintelligence-news.com/2023/01/09/adobe-train-algorithms-your-work-opt-out/

6. “open networks of production” - The Wealth of Networks by Yokai Benkler -

   https://www.benkler.org/Benkler_Wealth_Of_Networks.pdf

7. “Software, free from control, can evolve.” - The Future of Ideas by Lawrence Lessig

   https://en.wikipedia.org/wiki/The_Future_of_Ideas

8. “Emad Mostaque's vision is just this.” -

   https://www.realvision.com/blog/emad-mostaque-talks-stability-ai-with-raoul-pal

9. “I can download the model on Git Hub.” -

   https://github.com/AUTOMATIC1111/stable-diffusion-webui

10. “However, to prompt an image and make it look like me, needs custom tuning.” -

    http://nyewarburton.com/2022/02/09/machine-learning-experiments/

11. “but the cost may be, that your likeness no longer belongs to you.” -

    https://www.businessinsider.com/lensa-ai-raises-serious-concerns-sexualization-art-theft-data-2023-1

12. “It is designed to be trained with personalized "memory stacks", so your bot becomes you.“

    https://www.personal.ai/how-it-works

13. Oasis Protocol -

    https://oasisprotocol.org/

14. “It might mature into an automated lawyer that tracks our transactions.” - Nick Szabo -

    https://en.wikipedia.org/wiki/Nick_Szabo

15. “Theoretically, protocols are being developed that trigger when the virtual asset discovers its utility value.”

    https://academic.oup.com/ijlit/article/26/4/311/5106727

16. “I have watched with optimistic hope.” - https://twitter.com/MagicEden