CNBC previously reported rumblings of a possible deal to sell Cheddar to Regent. Archetype oversees media brands including Sunset Magazine and Military Times.

“Cheddar has helped transform the way millennials have accessed television news since its groundbreaking debut broadcast from an iPhone in 2016,” Archetype said in a statement. “We are excited to assist Cheddar in expanding its reach as the definitive independent ‘Voice of What’s Next’ empowering new audiences to be informed and engaged citizens in an ever-changing world.”

Terms of the deal were not officially disclosed, but a person familiar with the matter told CNBC it is structured as a so-called “earn out” deal. Altice USA will collect proceeds in the future if Cheddar meets certain performance targets. Those payments could amount to about $50 million based on internal projections, CNBC previously reported.

Cheddar, founded in 2016 by Jon Steinberg, was bought by Altice USA in 2019 for $200 million.

“We are incredibly proud of what Cheddar News has accomplished within the Altice USA portfolio, growing its distribution to reach new viewers with fresh and exciting need-to-know news content,” said Keith Bowen, president of news, advertising and programming for Altice USA, in a statement.

Previously, Meta employed around 12 scientists on a project called ESMFold, which trained a large-scale language model capable of processing large amounts of biological data to predict protein structures, and used AI to create the first database containing over 600 million protein structures. The progress was once praised by those in medical circles involved in developing new drugs and treatments.

According to three people familiar with Meta's reorganization plans, the ESMFold team was disbanded this spring as part of the company's massive layoffs. But that had never been reported before.

Meta still employs thousands of AI scientists and engineers; the ESMFold team is small by comparison, the people familiar with the matter added. Nonetheless, the move to cancel the program suggests that Meta is looking to move away from blue-sky research (meaning engaging in basic science research without regard to the possibility of practical applications in the short term) in favor of AI projects that can generate revenue.

Yaniv Shmueli, a former research scientist and engineering manager at Meta AI who worked on ESMFold, said, "Meta is trying to restructure its research strategy to learn more about how to create advanced intelligence so that it becomes a business for Meta and not just some novelty project."

The ESMFold team

Meta established the Fundamental Artificial Intelligence Research (Fair) Lab in 2013, hiring leading scholars in the field to work on this area.

Last November, Fair researchers published a paper in Science detailing the results of ESMFold: a database of 617 million macrogenomic protein structures created by machine learning, known as the ESM Macrogenome Atlas. Macrogenomics is the study of little-known proteins from environmental samples from all over the planet, including microorganisms in the soil, ocean, and human body.

The ESMFold project first trained a large language model to learn evolutionary patterns and generate accurate structure predictions directly from the DNA sequences of proteins.

Meta also created an open-source database that allows scientists to easily retrieve specific protein structures relevant to their work, and expressed hope that the work will be able to "catalyze further scientific progress."

Meta's project is considered a competitor to DeepMind's protein folding prediction technology, AlphaFold, which was considered a scientific breakthrough for 2020 and has accuracy comparable to laboratory methods. ESMFold's language model, on the other hand, describes structures 60 times faster than AlphaFold, albeit with less accuracy.

Tim Hubbard, a professor of bioinformatics at King's College London, said large tech companies may have an advantage in deploying computing resources quickly and at scale, as well as providing computationally expensive services to scientists.

In the long run, however, the huge costs of keeping algorithmic services and databases running are an issue. meta has not confirmed whether it will continue to offer this service in the future, but for now the data will remain available to the research community. hubbard expects that academics will find a way to continue this type of work.

Full steam ahead in AI

Meta was one of the first large tech groups to invest in AI. Since establishing Fair Labs, it has published numerous papers and has been recognized by the scientific community for its advancements in AI.

However, as of now, the company has begun to lag behind competitors such as OpenAI, Microsoft, and Google, all of which have consumer-oriented generative AI (AIGC) chatbots.

The year 2023 has been dubbed the "year of efficiency" by CEO Mark Zuckerberg, and Meta has undergone a massive reorganization in recent months, restructuring its management and laying off around 20,000 employees.

Meta's new focus will be to leverage its long history of research and development in AI to create products centered around AIGC, a technology that generates human-sounding text passages, as well as images and videos.

In February of this year, Meta formed an AIGC team led by product director Chris Cox, which currently employs hundreds of people, including employees who transferred from Fair Labs, according to two people familiar with the matter. Meta is now reportedly trying to reconfigure Fair's research to match the GenAI team's goals.

Last week, it was reported that Meta plans to launch a series of chatbots with different character styles as early as September this year in a bid to catch up with its competitors.

Joelle Pineau, Meta's vice president of AI research, said, "Meta remains committed to conducting exploratory research based on open science, and the transfer of other projects from Fair's labs to our business has always been an integral part of how the team operates."

However, along with the convenience and efficiency these tools bring, fake users, spam ads, and misinformation have followed.

Just days ago, a social app startup, IRL (IN REAL LIFE), was once valued at $1.7 billion and raised $170 million in a Series C round led by SoftBank. As a result, an internal board investigation found that 95% of the company's 20 million monthly users were "bots".

Recently, NewsGuard, a company that provides trust ratings for online news media, released a new analysis showing that due to the advertising budgets of major global brands such as tech giants and banks, they are providing advertising revenue to AI-generated low-quality websites, allowing these AI-generated low-quality content sites to receive significant financial support and continue to survive.

In this regard, The Verge reporter James Vincent concluded, "Now AI is killing the old Web and the new Web is being born with difficulty. And in his opinion, that's not necessarily a bad thing.

Generative AI can create large amounts of text and images in just a few minutes

The Verge points out that in a broad sense, years ago, Web sites used to be a place for individuals to create innovations, and many people developed sites, forums and mailing lists on the Web to make a little money.

Later, many companies were formed and felt they could do better, so they created flexible and feature-rich platforms and opened the doors for more people to join them.

It's a little bit like, they put boxes in front of us, we fill those boxes with text and images, and people come to see what's in those boxes. These companies chase scale because once enough people gather here, there's usually a way to make money from it.

But the advent of artificial intelligence has changed those assumptions.

With ChatGPT, Bard, and the new Bing popular today, they can quickly generate large amounts of text and images, as well as produce music and video.

Realistically, their output may surpass the news, information, and entertainment platforms we rely on.

Advertising revenue feeds a large number of AI-generated news and information sites

According to data released by NewsGuard, which has been tracking AI-generated news and information sites (UAINs) since May of this year, it finds 25 new UAINs every week, and today there are probably hundreds of AI-generated content sites.

So what's the point of having these sites filled with tons of AI content?

NewsGuard points out that one of the key points is that they are the place where many brand companies are placing their ads.

Analysts have found that the ads placed on these UAIN sites are programmatically generated, meaning that many well-known companies don't choose to place their own ads on UAIN, but are targeted by the ad placement system, most of which are placed by Google Ads.

NewsGuard says that their analysts have added 217 sites to their UAIN site tracker, many of which appear to be funded entirely by programmatic advertising.

Because sites can make money from programmatic ads, they have an incentive to publish content frequently. The company found one of these UAIN sites that published about 8,600 articles during the week of June 9 to June 15 this year, an average of about 1,200 articles per day.

By comparison, the New York Times, a news site that publishes about 150 articles per day, has a large number of editors and reporters behind it.

In fact, in the most recent study conducted in May and June of this year, NewsGuard analysts browsed sites in the U.S., Germany, France and Italy and found 393 programmatic ads from 141 major brands appearing on 55 of 217 UAIN sites.

Such trends, based on advertising revenue, are keeping alive a plethora of new AI-generated news and information sites that are flooding the Web.

Old Web sites are being "baptized" by AI

In addition, a lot of AI-generated content has infiltrated many older communities and platforms, such as LinkedIn, which is using AI to activate users; Snapchat and Instagram, which want bots to talk to you when your friends aren't talking, and so on.

At the same time, some Web sites are also being passively impacted by ChatGPT, such as Stack Overflow, a well-known community of programmers.

But stopping the expansion of AI use isn't the answer, and Stack Overflow is targeting AI use with plans to charge companies that crawl their data when building their own AI tools. In addition, Stack Overflow itself has plans to offer AI-related services.

Another platform that will be impacted by AI is the Q&A community Reddit. "Reddit's data is valuable, but we don't need to give it all away for free to some of the biggest companies in the world," said Reddit CEO Steve Huffman, signaling that the company is making a move. The company was about to make a move.

To no one's surprise, when it updated its Reddit API fee policy to generate more revenue and to give some value to its data, it was met with protests from many moderators who blocked the community section.

Finally, as the gateway to many websites, Google, the world's number one search engine, holds the lifeblood of modern Web sites. However, driven by the trend of Bing AI and ChatGPT as alternative search engines, Google is also taking action, with media reports suggesting that it is looking to build a new search engine powered by AI technology, with one of the key features of the new engine being the ability to "guess what users want", which will The engine will learn and predict what users want to know based on what they search for, and will provide pre-selected lists of things to buy, research information and other information. If Google does implement this plan, the impact of AI on traditional websites will be huge.

What happens when you put AI at the helm of a Web site?

There's no doubt that AI is becoming ubiquitous, so what would happen if all platforms were cannibalized by AI?

In response, Avram Piltch, editor-in-chief of the tech site Tom's Hardware, points out that while AI has the ability to restructure text, it's people who ultimately create the underlying data - whether it's a journalist picking up the phone to fact-check, or a Reddit user who can happily tell you when they have a battery problem how to fix it.

In contrast, the information generated by AI language models and chatbots is often not always right, and more problematic is that when it is wrong, the way it is wrong is often hard to spot. As a result, it takes time and expertise to further verify.

If machine-generated content replaces human authorship, there is less chance of correcting our collective mistakes when there is more AI itself making mistakes on top of the original human-only mistakes, and even somewhat hindering the ability to draw on human expertise.

At the same time, The Verge reporter James Vincent points out that the impact of AI on the Web is not so simple to summarize. Even in the few examples cited above, there are many different mechanisms at work.

In his view, the most successful sites tend to be those that use scale to their advantage, either by increasing social connections or product selection, or by sorting through the vast swarms of information that make up the Internet itself, but that scale relies on large numbers of humans to create potential value, and humans clearly can't beat AI when it comes to mass production.

But is this necessarily a bad thing?

Not really, argues James Vincent, "Some would say it's just one way the world works, and point out that the Web itself killed what came before, and often for the better. Print encyclopedias, for example, are almost extinct, but I prefer the breadth and accessibility of Wikipedia to the thickness and assurance of Encyclopedia Britannica. For all the problems associated with AI-generated writing, there are also many ways to improve it - from improved citation features to more human oversight. Moreover, even though the Web is awash in AI garbage, it may prove useful in spurring the development of better-funded platforms. For example, if Google is always giving you spammy results in search, you may be more inclined to pay for sources you trust and access them directly."

Indeed, the changes currently caused by AI are just the latest in a long struggle in Web history. Essentially, it's a battle over information - who makes it, how it's accessed, and who gets paid. But just because the battle is familiar doesn't mean it isn't important, nor does it guarantee that subsequent systems will be better than the ones we have now. The new Web is trying to be born, and the decisions we make now will determine how it evolves.

The big model industry has entered the era of "Hundred Model War", and all parties are constantly thinking and debating. "Is there duplicate construction in the '100-model war'?" "How to promote the innovation of vertical application?" Become the focus of industry attention.

A number of industry insiders interviewed by Securities Daily said that the big model industry is one of the key competitions in future technology competition. For most companies, exploring large model-based application innovation for vertical scenes, vertical industries and vertical fields will be the key direction to attack. The local run-through will drive the overall industry boom, innovation enthusiasm and creative vitality to improve.

Enterprises are competing for layout

In the field of China's big model industry, Ali, Huawei, Tencent and other companies have relatively early layout. 2019 Ali conducted the research and development of big model, and released "Tongyi" big model series in 2022. Tencent also disclosed the R&D progress of its "hybrid" big model in 2022.

In 2023, ChatGPT started a wave of big models. Baidu released its big language model "Wenxin Yiyin" in March, which became the first ChatGPT-like product in China. After that, a number of companies in China released big models to compete for the debut.

The Securities Daily reporter found that, as of July 3, China's 1 billion parameters above the scale of the large model has more than 80. In addition to the Internet giants, Shangtang Technology, cloud from technology, science and technology and other artificial intelligence track listed companies, light years beyond, Baichuan intelligence and other startups, Shanghai artificial intelligence laboratory, Harbin Institute of Technology and other research institutes units, have released the big model.

"We divide the big models and related products into three categories. The first category is generic big models, such as OpenAI's ChatGPT, Baidu's 'Wenxin Yiyin', and KU Xunfei's 'Starfire' are all generic big models; the second category is industry big models; the third category is based on generic big models or industry big models The third category is the application-based services based on the general model or the industry model. At present, most of the released products are concentrated in the first and second category." Some industry insiders said, "From the number of participants, the number of participants of generic large models such as 'Wenxin Yiyin' is at the level of 100 billion, and the number of participants of large models of other enterprises or startups is usually at the level of 10 billion or 1 billion."

Is there duplication of construction in the "hundred model war"? Chen Duan, director of Digital Economy Integration and Innovation Development Center of Central University of Finance and Economics, said in an interview with Securities Daily, "China has grown up a group of once leading Internet enterprises in the world in the PC era and mobile Internet era, and it is a good thing that these enterprises have taken the initiative to join the early R&D competition of large models out of the need to cope with the next round of survival competition. However, the competition in the field of general-purpose large models will produce a horse-power effect in the future, and only a few strong players will be able to win."

Zhang Xiaorong, president of Deep Technology Research Institute, also said in an interview with Securities Daily, "Big model training has a high threshold, and the number of companies that can really run through the commercialization of big model will not be many due to the limitation of data and arithmetic power. Now the domestic large model is still in the laboratory stage, manufacturers need more time and resources to train the model, debugging parameters, etc. The competitive market environment is conducive to industrial development, and finally it is bound to be a big wave."

Landing application is the key

"From the point of view of the big models that have been released, the number of generic big models is high, and the number of application-oriented big models is low. At present, there is a gap between domestic products and ChatGPT, and we have to face this gap squarely, make key breakthroughs through scenario-based traction, create benchmarks to form demonstrations, and effectively and quickly narrow the gap." Wang Peng, a researcher at the Beijing Academy of Social Sciences, said in an interview with the Securities Daily.

Chen Duan told reporters, "The market demand for realizing the value of large models in specific areas and scenarios is very large, and there will be good market compatibility to accommodate more competitors. Therefore, for more participants, exploring the innovation of applications based on big models will be the breakout direction."

This view is also highly shared by the track companies. Robin Li, founder, chairman and CEO of Baidu, recently said, "What is more important than the number of large models is the application, a breakthrough in vertical applications. The key point of the new international competitive strategy is not how many big models there are, but how many native applications are on the big models and to what extent these applications have improved productivity."

At the launch of "Jia Du Zhi Xing Traffic Big Model" of listed company Jia Du Technology, Liu Wei, Chairman of the company, said, "The birth of the general big model is just a starting point, which ultimately has to land on specific application scenarios and solve industry-specific problems. With the industry big model as the key driver, empowering the industry to improve production efficiency and service quality will bring about profound changes in economic and social development and industry. And the data and feedback brought by the advantages of application scenarios will further accelerate the technical iteration of the industry's big model, which will also become the greatest competitiveness of the domestic big model."

It is understood that in the field of government, public security, medical and other fields, vertical application-based large models are being landed one after another. The listed company TOPS has built a professional big model of government based on its own data of official documents, policy documents, government office guidelines and other data as professional training data; MYAI big model independently developed by MPC focuses on vertical applications and has been applied in the construction of big data projects in many industry fields such as public security, government, taxation and enterprise digital transformation.

A few days ago we shared some of Jen-Hsun Huang's philosophy on managing a company, and today this is a WSJ interview with Nvidia's co-founder talking about trivia from 30 years ago.

Compare that to those other trillion dollar tech companies, Microsoft and Apple that were made into movies, Google with its genius twins, Bezos who gave up a high paying job at a hedge fund in his garage ...... Few people care about the original story of Nvidia.

But like a semiconductor chip, it's not usually seen, but it's an essential engine for the entire computing world.

Three people, 10 cups of coffee

Denny's, an American chain, open 24 hours, cheap, large portions, and high calorie, is one of the largest restaurant chains in the country.

Often located along the highway, like the one we're talking about today.

Thirty years ago, three engineers met at a restaurant in San Jose to discuss the future of computers.

A "Grand Slam" breakfast set ignited a dream to change the world.

"We're not good customers, 10 cups of coffee in four hours (for three people)," says Chris Malachowsky. Chris Malachowsky says.

Because they often stayed too long, they were kicked out of the business area by the restaurant manager and relocated to a small room in the back of the restaurant.

That small room became a co-working space for two teams, with the California police writing reports on one side and the three founders of NVIDIA on the other.

"We sat there with our laptops, trying to figure out what we were doing.

Not just starting a business, but creating a market

Thirty years later, we all know what they were doing. But nobody could figure it out then. "[The GPU market] didn't exist."

In the hotel, the first thing the founders of Nvidia discussed "was what we wanted to be.

They wanted to create a better chip and create a business model around it. chris Malachowsky was in charge of hardware design, Curtis Priem was in charge of software architecture, and Jensen Huang was in charge of business decisions.

They did market research in hotels, studying potential competitors, the price of silicon, and the potential profit margins of companies they hadn't named yet.

That moment set up Nvidia's current success - targeting the 'market that doesn't exist'.

Jen-Hsun Huang likes to call it the "$0 billion market," but of course now people would say that it is a trillion dollar market.

Every trillion dollar business has its origins in the exploration of 0 billion, whether it's PC gaming or AI computing.

Grassroots trivia, no air conditioner, no name

"Huang refused to join the company unless it could achieve $50 million in sales in a year," says Priem, who is responsible for software architecture. Priem, who is responsible for software architecture, said Jen-Hsun Huang was the head of sales at LSI Logic before starting the business.

The three founders of NVIDIA chose to meet at the restaurant because they came from different companies, Chris and Priem from Sun Microsystems (acquired by Oracle in '09) and Jen-Hsun Huang from LSI Logic, and they needed a place to talk about quitting, so they needed a "middle ground.

They met several times between 1992 and 1993 to discuss chips built specifically for 3D gaming, and they started the company at Denny's, but moved away before it was officially named NVIDIA.

"When they noticed the bullet hole in the front window, they realized that a restaurant on the side of the highway would not be the ideal office.

"Maybe this isn't the place to stay," Chris joked to reporters.

Then they moved to a townhouse in Unicron Priem, where privacy was protected, but there was no air conditioning and no name.

"It shouldn't be a real word or say what we're going to do," Jen-Hsun Huang told Chris, "The three of us sitting in an apartment with no air conditioning, who knows what we'll end up doing?

The only thing they knew for sure was that they were going to enter the chip industry. At the time, graphics cards were generally named with only two letters, and the founders liked the sound of NV, envy, jealousy.

At first they wanted to call it Nvision, not a word in the dictionary, and without revealing their business, perfect.

Then they realized the problem: there were already several companies with similar names, including one that made toilet paper.

Then they started going through the Latin dictionary and found the Latin word for jealousy: Invidia.

Take away the first letter.

The trillion dollar leather man who worked as a waiter 40 years ago

Many people may not know that Jen-Hsun Huang used to be a waiter at that Denny's restaurant. He said because of this job, he was forced to go from tech geek to 'social cow'.

Bonus takeaway: If you don't have a relationship, don't just go to a restaurant and get in the way of other people's business.

Jen-Hsun Huang has been running Nvidia since Mark Zuckerberg was in elementary school, but he wasn't always the confident leather-clad guy people remember now.

Denny's feels like old home to Jen-Hsun Huang. Without his waitressing job at Denny's, Jen-Hsun Huang might not be the tech leader he is today - in his own words.

Early on, Jen-Hsun Huang was very shy, but his simple job as a waiter at Denny's transformed him.

Taking orders for pancakes from others taught him how to interact with strangers and how to make compromises in situations beyond his control.

A vision that matters and deserves to be believed by no one

In the early days, it was hard for them to sell their vision. When Jen-Hsun Huang told his mother, his mother didn't believe him.

Jen-Hsun Huang still remembers what his mom said to him when he told her he was going to start a chip company and let people buy cards to play games:

"Why don't you get a job?

Until 1997, when Nvidia released the RIVA 128, they were at risk of bankruptcy.

The story of CUDA is the same.

In 2008, NVIDIA's CUDA parallel computing architecture was not well received by the market, and their market cap fell below $5 billion during the financial crisis.

The contrasting figure is that when Nvidia's market cap soared last week, Jen-Hsun Huang's personal fortune grew by $6 billion in one day.

As it was 30 years ago, and as it was 15 years ago, Jen-Hsun Huang has always believed in the future he saw.

If you are concerned about the Big Model space, please scan the code to join our Big Model Exchange Group to discuss the consensus and perception of the Big Model era and keep up with this wave of the Big Model era.

According to MARC ANDREESSEN, founding partner of a16z, AI offers the opportunity to enhance human intelligence and enable us to achieve better results in all areas. Everyone can have an AI mentor, assistant or partner to help us maximize our potential. ai can also drive economic growth, scientific breakthroughs and artistic creation, improve decision-making and reduce casualties in war. However, there are risks associated with the development of AI, and the current moral panic may exaggerate the problem, with some actors possibly acting in their own self-interest.

How can AI be viewed rationally, and from what perspectives should it be viewed? This article provides a viable, credible and insightful example of how to explore it.

The following is the full text:

The age of AI has arrived, and with it comes much surprise and much trepidation. Fortunately, I'm here to bring good news: AI will not destroy the world, but may in fact save it.

First, a brief introduction to what AI is: the application of mathematics and software code to teach computers how to understand, synthesize, and generate knowledge, just as humans do. ai is like any other computer program - it runs, takes input, processes, and generates output. the output of ai is useful in many fields, from coding to medicine, law, creative arts, and more. It is owned and controlled by people, just like any other technology.

AI is not killers and robots that start up and decide to murder humans or otherwise destroy everything, like you see in the movies. Instead, AI could be the way to make everything we care about better.

Why could AI make everything we care about better?

Social science has conducted thousands of studies over the years, and the most reliable core conclusion is that human intelligence can improve life outcomes. Smart people have better outcomes in almost every area of activity: academic achievement, job performance, career status, income, creativity, physical health, longevity, learning new skills, managing complex tasks, leadership, entrepreneurial success, conflict resolution, reading comprehension, financial decision-making, understanding others' perspectives, creative arts, parenting outcomes, and life satisfaction.

In addition, human wisdom is the lever we have used for millennia to create the world we live in today: science, technology, mathematics, physics, chemistry, medicine, energy, architecture, transportation, communications, art, music, culture, philosophy, ethics and morality. Without the application of wisdom in all of these areas, we would still be living in a quagmire, barely making a basic agricultural living. Instead, we have used our intelligence to improve our standard of living by about 10,000 times over the past 4,000 years.

AI offers us an opportunity to augment human intelligence so that all the fruits of intelligence - from creating new drugs to solving climate change to interstellar travel and more - can get better from here.

AI's augmentation of human intelligence has already begun - AI is already all around us in various forms, such as many types of computer-controlled systems, now rapidly escalating through large language models like ChatGPT, and will accelerate rapidly from here - if we let it. -if we allow it.

In our new era of AI:

Each child will have an AI mentor with infinite patience, infinite compassion, infinite knowledge, and infinite help. the AI mentor will be with each child as they grow, helping them maximize their potential with infinite love. Every person will have an AI assistant/coach/mentor/trainer/consultant/therapist who is infinitely patient, infinitely compassionate, infinitely knowledgeable, and infinitely helpful. AI assistants will be with each person through all of life's opportunities and challenges, maximizing each person's results. Every scientist will have an AI assistant/partner/associate, greatly expanding the scope of their scientific research and accomplishments. Every artist, engineer, businessman, doctor, and caregiver has the same AI assistant in their field. So does every people leader - CEOs, government officials, nonprofit presidents, athletic coaches, teachers. The incremental effect of leaders making better decisions about those they lead is enormous, so this intellectual enhancement is paramount. Productivity growth throughout the economy will accelerate significantly, driving economic growth, the creation of new industries, new job creation and wage growth, and leading to a new era of high global material prosperity. Scientific breakthroughs, the emergence of new technologies and medicines will expand significantly as AI helps us further decode the laws of nature. Artistic creation will enter a golden age, as AI-enabled artists, musicians, writers, and filmmakers will be able to realize their visions faster and on a larger scale than ever before. I even believe that when war is inevitable, AI will improve it by dramatically reducing wartime mortality. Every war has been characterized by terrible decisions made by constrained human leaders under extreme pressure and with extremely limited information. Now, military commanders and political leaders will have AI advisors to help them make better strategic and tactical decisions that minimize risk, mistakes, and unnecessary bloodshed. In short, anything people do today with their own natural intelligence can be done better with AI, from curing all diseases to enabling interstellar travel. It's not just about intelligence! Perhaps the most underrated quality of AI is how human it is. AI art empowers people who otherwise lack the technical skills to freely create and share their artistic ideas. Talking to an empathetic AI friend really improves their ability to deal with adversity. ai medical chatbots are already more empathetic than their human colleagues. Infinitely patient and compassionate AI will make the world warmer and kinder, not harsher and more robotic. However, the stakes are high here. AI may be the most important and best thing our civilization has created, on par with, and perhaps even beyond, electricity and microchips.

The development and spread of AI - far from being a risk we should fear - is a moral obligation we have to ourselves, our children, and our future. With AI, we should live in a better world.

So why the panic?

In stark contrast to this positive view, the public conversation about AI is filled with fear and paranoia.

We hear voices claiming that AI will kill us all, destroy our society, take away all the jobs, and cause gross inequality. How can we explain this wide variation from near-utopian to anti-utopian outcomes?

Historically, every major new technology, from electric lights to automobiles, from radio to the Internet, has triggered panic - a social contagion that has led people to believe that new technologies will destroy the world, destroy society, or both. The excellent work of the Pessimist Archive has documented these technology-driven moral panics for decades; their history makes the pattern abundantly clear. As it turns out, such panics have now been had before.

Of course, many new technologies do lead to undesirable consequences-often those that are otherwise very good for us. Thus, the mere existence of a moral panic does not mean that there is nothing to be concerned about.

However, moral panic is inherently irrational - it exaggerates what may be legitimate concerns to a level of hysteria that allows truly serious issues to be ignored.

We now have an AI moral panic.

This moral panic has been used by a variety of actors as a driver for policy action - new AI restrictions, regulations, and laws. These actors have made extremely dramatic public statements about the dangers of AI - satisfying and further fueling the moral panic - all of them self-proclaimed disinterested champions of the public good.

But are they?

Are they right or wrong?

Economists have observed a long-standing pattern in such reform movements. The actors within such movements fall into two categories-"baptists" and "smugglers"-drawing on the "bourgeoisie" of the 1920s U.S. Prohibition. The example of Prohibition in the United States in the 1920s:

The "baptists" were true believers in social reform who believed that new restrictions, regulations, and laws were emotionally, if not rationally, needed to prevent social disaster.

For alcohol prohibition, these actors are usually true believers in Christianity, who believe that alcohol is destroying the moral foundations of society. For AI risk, these actors believe that AI may create some kind of existential risk - and if given a lie detector, they really do think so.

"Smugglers" are self-interested opportunists who can benefit financially from the imposition of new restrictions, regulations, and laws to insulate themselves from competitors. In the case of alcohol prohibition, these people make their fortune by selling illegal alcohol.

In the case of AI risk, these are the CEOs who will make more money if regulatory barriers are erected because the government protects them from new startups and open source competition.

Some would argue that there are people who are ostensibly "baptists" who are also "smugglers"-especially those paid by universities, think tanks, activist groups and media outlets to attack The AI people. If you receive a salary or a grant to foster AI fear ...... you are probably a "smuggler.

The problem with "smugglers" is that they win. The "baptists" are naive ideologues and the "smugglers" are cynical operators, so these types of reform movements usually result in the "smugglers" getting what they want -regulation, protection of competition- and the "baptists" wonder what's wrong with their drive for social improvement.

We have just experienced a stunning example of this - banking reform in the wake of the 2008 global financial crisis. "The Baptists told us that we needed new laws and regulations to break up the "too big to fail" banks and prevent such a crisis from happening again. As a result, Congress passed the Dodd-Frank Act of 2010, which was advertised as meeting the goals of the "baptists" but was actually controlled by the "smugglers" - the big banks. The result was that the "Great Reckoning" of 2008 was a major financial crisis. The result is that the banks that were "too big to fail" in 2008 are now even bigger.

So, in practice, even if the "baptists" are sincere - and even if the "baptists" are right - they will be overwhelmed by cunning and greed. they can be used to benefit by cunning and greedy "smugglers.

This is also happening now in the push for AI regulation, and it is not enough to identify the actors and question their motives. We should evaluate the "baptist" and "smuggler" perspectives.

Revenue has declined for three consecutive quarters, social family growth almost in place, the first to open the second round of this year's 10,000 layoffs ...... especially under the sudden tide of AI, Meta's previous heavy bet on the meta-universe seems to have been forgotten in the corner.

But in such a situation of struggle on all sides, Meta this time stood out as a dark horse and delivered a bright report card. Not only has Meta reversed its decline this quarter, but its AI-enabled social family has also started to revive. After Meta released its optimistic growth forecast for the next quarter, Meta's share price soared after the bell today, once surpassing 12%.

However, it is worth noting that Meta's meta-universe business not only did not grow but declined significantly this time, which may also further push Meta to tilt its strategic focus from meta-universe to AI, and the next stage of the giant melee in the AI track may be more intense.

Meta releases optimistic expectations as revenue and social family return to growth

Overall, the following information revealed in this earnings report drove the market's confidence in Meta to soar.

First, revenue and profit finally stopped falling and started to rebound. meta's revenue in the first quarter was US$28.645 billion, up 3% year-on-year, much better than the market's expectation of a year-on-year decline of over 0.8%. This compares with declines of 4% and 3% in the third and fourth quarters of last year, respectively. Diluted net income per share was $2.20, down 19% year-over-year but also well below market expectations of a 26% year-over-year decline, and a significant rebound from a 52% year-over-year decline in the fourth quarter of last year.

In addition, its social family returned to the upward curve and delivered significant growth in advertising revenue. The market has been skeptical about Meta's user growth after the first decline in social family users in the second quarter of last year. However, this quarter, the number of social family users rose again from the previous quarter, with 2.04 billion daily users and 2.99 billion monthly users, three consecutive quarters of positive growth, proving to a certain extent that Meta's social family is back on the upside.

During the quarter, advertising exposure generated by the social family grew 26% year-over-year, and overall advertising revenue reached $28.101 billion, up 4.1% year-over-year, also much better than the market's expectation of a 0.9% decline.

In addition to the above two points, this time Meta gave a very positive second quarter earnings outlook, once again clearing market concerns and pushing Meta's stock back to its highs since January 2021. Meta expects total revenue for the second quarter to be in the range of $29.5 - $32 billion, implying growth of between 2.4% - 3.8% year-over-year.

In addition, Meta's biggest competitor, TikTok, has been in a regulatory quagmire recently, which may also benefit Meta to some extent by increasing the social family's user base and user stickiness.

Meta Universe business has been hit hard by the lack of success in "burning" money

The advertising business, which is the "lynch pin", has apparently been stabilized this time, but Meta's bet on the future of the metaverse still seems to have failed to take off, and it can even be said that it is developing badly.

Since Meta's full transformation into the metaverse, the entire Reality Labs division recorded a total loss of $13.72 billion last year. And this quarter, Reality Labs again lost $3.99 billion, expanding its loss by nearly 35% year-over-year and exceeding market expectations of a 28% loss.

While this loss figure was down slightly from the previous quarter's $4.28 billion, in terms of revenue, metaverse revenue for the quarter was down by more than half from the previous quarter. While the metaverse business generated $727 million in revenue in the fourth quarter of last year, that number fell to $339 million in the current quarter, the third worst quarterly performance since 2021.

From the representative work "Space Opera" to take the gold medal of the competition, to a series of fake AI pictures of Musk and Trump, MJ single-handedly let the world know about AI painting.

And with the aforementioned labels and legendary resume, MJ is already a global model for AIGC startups. Even its success has been attributed to the opening of a new era of venture capital belonging to the AI era: a new form of startup that is growing wildly, smaller in size, lighter in assets, faster in growth, and scarier in profitability ......

MJ, how exactly did it catch fire? What kind of a new business paradigm does it represent? Can we copy its model and make a Chinese version of MJ?

Technology-driven, building the aesthetic pinnacle of AI painting

In the field of AI painting, MJ's development speed is definitely the strongest. the first version went online in March 2022 and evolved to V5 version in April 2023.

Previously, AI painting had been criticized for being unrealistic, especially the details of the character's hands, and AI painting had a high frequency of 6 fingers, deformities and other odd effects, which was called "crippling AI". But with the launch of V5, it perfectly solves this technical problem, and even presents fingerprints and skin patterns of the hands, achieving a leap forward in AI painting.

In addition, the V5 version completely overturned the "definition" of AI painting, its finished picture can rival the photo, a lot of photographers, especially advertising photographers wail: photography is finished.

A large number of media started to cry: MJ has opened Pandora's Box, seeing is not necessarily believing, and false information based on pictures will sweep the world.

Among the many AIGC practitioners and designers we interviewed, they commonly used MJ for their creations. The reason is simple: the effect is outstanding. Ben, the commercial director of Boundless AI, just said that MJ is defining the aesthetic height of AI painting.

In fact, MJ will boost the confidence of everyone who has never used AI painting before. Just type in a few prompt words, and MJ will almost always give stunning effect pictures.

Why MJ can fire, the top stream of technology, no one can match, this is the "basic plate" of its popularity.

Open community and create a "fountain of creativity" to ignite an exponential explosion of users from 0 to 1

First-time users of MJ will find it very strange that it does not have an official website, let alone an app.

The entrance to MJ is in the social software Discord, which Tencent's QQ channel imitates, and it is this odd move that has given MJ its powerful creativity.

Any user can directly access MJ's channel in Discord and then see painters from around the world enter prompt words in the group to get the finished AI painting. MJ's users are learning from each other and growing rapidly in this environment, and Discord provides a kind of co-creation ground for MJ. It's no exaggeration to say that MJ may have nurtured the world's first group of AI painting players and artists.

"It comes with a creative spirit, and the keywords learn from each other and create infinitely so that they emerge." Aben said.

Discord that is MJ's creation platform, but also a learning and communication platform for MJ users. Many people who enter MJ's Discord will find that it is simply a rabbit hole with endless treasures hidden inside, inexhaustible.

"MJ's content is more about Idea innovation than skill creation." In Ben's opinion, MJ has technically brought AI painting to a current pinnacle, and what amazing work you can draw with it depends on your ideas.

David Holz, the founder of MJ, mentioned in an interview why MJ was loaded into Discord. In his opinion, it would be terrible to treat the AI as a chatbot and then have the user communicate with it one-on-one.

"I don't think the Midjourney experience works at all if it's just talking to a chatbot in a room. But if it's in a room with a lot of people, it becomes very interesting. That's another area where I've never seen chatbots before, is a chatbot in an environment with multiple people, rather than trying to be one person."

In addition, he makes the very interesting point that if MJ is a one-to-one product, users can explore its potential for themselves and then take the valuable experience for themselves. But is that a good product? What kind of product is a good product?

He has a very "brilliant" analogy.

User A wants to draw a dog, so he gets a dog, then he can try to draw a big dog, and then he can draw a big shaggy dog. But if it is an open drawing environment, the stranger will draw a "space dog", "space dog with laser", "space dog with laser and angel wings" based on the idea of a dog. "...... So, the ideas were endlessly extended.

"MJ created an imaginative environment and made people more imaginative." David Holz said.

Today, MJ has tens of millions of users, and it has gone from niche to mass. After users come, it may be hard to leave it.

An atypical event that ignites global hotspots

MJ took one year to become popular and spread in a massive circle-breaking way, which cannot be separated from several landmark events.

First, in August 2022, Jason Allen, a non-artist, won the grand prize of the Colorado State Fair Art Competition with a piece of "Space Opera". All these events pushed MJ into the public opinion for the first time, whether AI painting is art or not, and how AI painting produced this "amazing work".

According to the data, the user volume of MJ was around 300,000 at the end of August, but by the end of September, the user volume reached 1.5 million+.

Secondly, the V5 version was launched, as already mentioned in the previous article, which directly brought AI painting to a new level from the technical point of view. As a result, several explosive points of public opinion were created.

Among them, the most powerful one is a series of fake photos, for example, Trump's arrest, Musk in China, Chinese couple, Chinese national soccer team winning the World Cup ......

The topicality of these images and the amazing effect they presented completely stirred the public's attention, and like a virus spreading, a series of fake photos were born on social media at home and abroad, and the debate of AI painting swept the streets.

These landmark events may be accidental, but they are also inevitable. So many AI painting software, which triggered the public opinion frenzy, were mainly born in MJ.

MJ's model cannot be copied, but AI painting has a business model unique to the AI era

Can MJ's model be copied? There is absolutely no answer to this question, at least, in China, we do not see projects that copy MJ's model, one does not. This shows that MJ may not be easy to imitate ......

But we found a very interesting point. In the opinion of Liu Qiushan, chief researcher of Boundless AI, AIGC, AI painting is still in its early stages and does not have a model of strong business.

"If we use the past understanding of entrepreneurship to say MJ is undoubtedly successful, it took one year to achieve huge profits, very bull. However, AIGC is the proposition of the whole era, and its value is incomparable to the traditional Internet. At least, the business form of AIGC in the future is not only MJ's current membership payment model. If MJ can find a business model (a new model) that belongs to it, the value is unimaginable." Liu Qiushan said.

What kind of innovative business model can AI painting have?

MJ and Stable Diffusion, as mentioned at the beginning of the article, are the "twin stars" of AI painting.

Ben told Babbitt that Stable Diffusion is open source, and its choice of open source strategy was a turning point for the AI painting industry, after which AI painting tools of all sizes were created, resulting in a number of open source projects and communities. This is like Android, where different developers created a thriving Android ecosystem based on Android. And MJ like Apple, although not open source, but create the ultimate painting effect of AI painting.

"The intersection of their two continues to break the boundaries of AIGC. The startup is based on Stable Diffusio, creating more, vertical use scenarios for AI painting. MJ, on the other hand, defines the high standard of the industry in terms of aesthetics and high requirements." Aben said.

We found that there are a lot of AI painting projects based on Stable Diffusion done in China, and the ecology is thriving. And, we found some business models in AI painting that are different from MJ.

For example, creating a business closed loop for AI painters. From the product system of AI painting tool Boundless AI, it has AI Square, which can show users' creative works, and it has certain social and sharing attributes. And, users can follow their favorite creators, and creators can thus build their personal brand and community. Even, creators can not only sell prompt words, but also sell copyrighted works directly. From this perspective, Boundless AI inherits MJ's community concept, but at the same time provides a path for creators to grow and profit.

At Thera, we believe in preserving the traditional ways of French cooking while exploring new avenues to create unique and flavorful dishes. Our chefs are trained in the art of French cuisine, and our research team is constantly exploring new ingredients and techniques to add to our repertoire.

Neeta, on the other hand, is our innovative brand that takes the traditional methods of cooking and adds a technological twist to it. Our team of food scientists and engineers work together to create the perfect blend of science and culinary art. We use modern equipment and techniques to create a new generation of molecular gastronomy.

Our dishes are not only delicious, but they also appeal to the senses in a way that traditional cooking methods cannot. Our dishes are visually stunning and have a unique texture and flavor profile. We create dishes that are not only delicious but also an experience in themselves.

At Thera, we believe that food is not just about taste, but also about the experience. That is why we have created an exclusive membership program that allows members to access our latest creations before they are made available to the public. Members can also receive updates on our latest research and development, as well as exclusive invitations to our events.

To make this membership program even more exclusive, we have also included a unique NFT that comes with each subscription. This NFT not only gives members priority access to our latest creations, but it is also a work of art in itself. Each NFT is unique and can be collected or traded amongst members.

https://opensea.io/assets/ethereum/0xFa3c575A0a999F50Ddd485Da146dCA318931820e/0

Our commitment to preserving the traditions of French cuisine while also exploring new avenues through technology is what sets Thera and Neeta apart from other food companies. We believe that food is not just about sustenance but also an art form that can be used to create unforgettable experiences. Join our exclusive membership program today to be a part of this culinary revolution.

Students enrolled in the master's program in sustainability, entrepreneurship and technology at the Vienna University of Economics and Business can complete the entire program - including attending lectures, meeting fellow students for coffee and more - simply by logging in via their laptops.

Developed in cooperation with a Berlin-based edtech startup university called the University of Applied Sciences of Tomorrow, the course is one of many examples of business schools using metaverse, 3D technology, virtual reality devices and avatars to expand the scope of management and leadership training.

Offering the course "gives us a bigger platform to make teaching more global," explains Barbara Stöttinger, Dean of the School of Administration at the Vienna University of Economics and Business.

However, she is quick to add: "Vienna is also a great place, so coming to campus is still very attractive for most students. This is at the heart of many business schools' reluctance to enter the metaverse for course instruction: learning in the real world has its unique advantages.

Developing skills such as leadership and interpersonal skills is an integral part of graduate management programs (such as an MBA) and is best done in person, and attending offline courses also avoids the need to fund the purchase of hardware and software needed in a metaverse program

At the same time, the metaverse is an extreme example of being caught in a "hype cycle," after all the frenzy over a new technology often turns into widespread rejection by the public because it fails to live up to the level of reality it claims.

The metaverse first came into the public eye a few years ago, especially when Facebook renamed itself Meta to "help bring the metaverse to life" at a time when online multiplayer games were very popular.

However, enthusiasm for the metaverse has since waned at an alarming rate. In fact, criticism of the metaverse is now becoming a popular pastime, just as it was praised in the early days.

Meta CEO Mark Zuckerberg was even forced to say that the metaverse "is not the main thing we're doing. The project.

But because business schools operate at a different pace than the technology industry, many are still testing the metaverse concept. In some cases, they have been seeking partnerships with gaming and virtual reality technology companies to help build teaching platforms.

"Meta has invested billions of dollars in the metaverse and the gaming industry is worth $20 billion, but in education, we don't have those budgets," said Steve Muylle, associate dean of digital learning at Vlerick Business School in Belgium.

"The problem is that technology is constantly evolving. So even if we do make investments, we can't keep up with the rapid change of hardware and software."

The Vlerick School of Business is one of the members of a global consortium of business schools interested in developing online teaching and learning technology, known as the Future of Management Education (FOME.) The Vlerick School of Business is currently working with a local gaming company to develop a virtual teaching and learning environment for Vlerick students and hopes to provide the same immersive experience as when students play games, while controlling costs.

We're here for the technology though, right?

Bear markets are often referred to as get-rich-quick opportunities, but here's why.

This is because the opportunity to buy projects at very low prices compared to their activity, development and utility is abundant throughout the crypto space. It is not easy to choose the right project, but the opportunity is clear.

1. using L2

In the blockchain space, there is a clear and current push to enable scaling and increase transaction throughput. During the last bull market, we saw a lot of interest and speculation around projects like Solana and other Alt L1s. This is in large part because Ether has not yet scaled appropriately to handle the bull market's demand for its block space.

However, many of these blockchains, while boasting incredible speed and throughput, have continued downtime that has left many users outraged or underperforming during times of high demand. Ultimately, many of these blockchains lose because they are monolithic, not modular, and they try to provide all the security, decentralization, and throughput in a single product.

This doesn't work at scale, and it's pretty obvious (the point is biased, but well supported). So what is the solution that provides high throughput, high security and high decentralization?

Enter L2 Layer 2 solutions offer the ability to increase throughput, thus improving the scalability of the blockchain, while inheriting the security of the main chain. Solutions like StarkNet and zkSync enable "batch processing", where thousands of transactions are bundled into a single transaction and published to the main chain (ethereum). This reduces the cost per transaction by several orders of magnitude and increases the speed and total number of transactions that can be processed on the chain.

So, why is this so amazing and why should we care? In order for this amazing technology to seep into the mainstream and be adopted as the core technology of the new Internet, we need it to be fast, secure and decentralized.

The L2 solution solves the speed problem, while the master chain provides security.

This will enable a wide range of use cases to operate to the standards we need in order to achieve worldwide adoption. Examples of this include video games that process thousands of micro-transactions per second, media that is shared instantly and at low prices, and money transactions that can be completed in the blink of an eye.

Without a Layer 2 solution, it is likely that the full potential of the blockchain will not be realized for a long time. If we want to gain adoption, we need to provide a layer that allows for easy transactions while allowing for mass adoption - Layer 2 provides that core need.

Layer 2 solutions, such as zkSync, Starknet, Polygon Hermez, Optimism, and Arbitrum, are currently under active development and have substantial progress, and will soon meet the basic requirements needed for adoption.

2. Maturation of DeFi and NFT

Much of the last bull market was driven by two things: DeFi and NFT. Both are very powerful tools, but both are still in their infancy - NFT has the edge over DeFi.

As the market calms down, it's time for these products to refine their capabilities and retest the products for market fit.

So, why will decentralized finance lead to the next bull market?

DeFi is an open financial system where anyone, anywhere, with any amount of money can participate.

Not only does this provide a wealth of opportunities for those who cannot access banking services, but it also allows a variety of new fintechs to grow and mature. The problem is that "decentralized lending is in its early stages. It doesn't offer everything that centralized lending does, but it trumps the inefficiencies of traditional finance and comes close to the creative thinking that is attracted to Web3."

-bankless

The existing centralized financial system (CeFi) is a huge walled garden controlled by banks and governments. They choose who gets in and who gets how much money. Even if you meet all their requirements, they can still easily turn you away, and often do.

The DeFi lending agreement and service bypasses this licensing threshold, offering the same financial services that banks currently offer to everyone.

It is 100% transparent and de-trusted. Each person can view the other's chips (anonymously through their address) as well as assess the financial health of the creditor/debtor based on their own criteria. This means you can peel back the layers as before and have a window into the inner workings of DeFi's new age banking.

This opens up a world of financial innovation, introducing new utility, new opportunities, and clarity around who can make, borrow, or lend money.

But what about NFT? Aren't those just jpegs?

Why will they lead to the next bull market?

If you think so, you are sadly mistaken; NFT is the Trojan horse to the real world of digital ownership.

In the last bull market, pictures of monkeys and pixelated punk ruled the universe. And this only marks the beginning, a simple demonstration of the basic utility of digital ownership.

When we buy a shirt from a brick-and-mortar store, it's yours, and only you own that particular shirt, and you have the receipt to prove it. It's "non-homogeneous" in every sense of the word.

However, until NFT came along, this was not possible in the digital realm. You could certainly buy collections of X, Y or Z online, but they were stored on servers rented by the seller's company. With NFT, the assets exist in a wallet that you control.

Industries that this technology can and likely will disrupt include gaming, music, and home mortgages and money loans. The scope is unimaginable, and some of the other products and solutions outlined below that will lead us into the next bull market use this key technology.

In short, watch for innovation in the NFT space and the teams that are working to realize its full potential. 3.

Adopting Web3 Single Sign-On

Single sign-on web3 authentication allows for a single password and account to be used across millions of new sites and existing major news outlets and platforms, with no personal details attached.

Another huge topic that continues to appear in the news is privacy and data. Companies like Meta, Amazon and Google pretty much own your identity. They know everything about you -- your passwords, date of birth, SSN, and everything you say and do on the Internet.

They say it's secure, but how many times has your data been compromised? This is basically Westworld-level data collection, and most people are just allowing it to happen because there is no better solution available.

The market for data collection is worth billions of dollars, and that's how these companies make their money. According to Datamation data.

"The global data collection market is valued at $1.66 billion in 2021. It is estimated to reach $8.21 billion by 2028, growing at a CAGR of 25.6%."

These trillion-dollar companies are in the business of selling personal data. It's not just random data about a 25-year-old, white woman living in Ohio, it's your name, your email, your location, the products you buy, and the list goes on.

Web3 single sign-on solves this problem. It allows companies to collect data, learn about your preferences, and provide you with personalized information they think you're interested in, while keeping your identity safe.

They can only have this data with your permission. (For more information on personalized data sharing, check out the Brave browser).

In my opinion, the future will look like this: create a web3 wallet/identity and link it to any of a hundred sites where you have an account. When you visit any of those sites, click a button -- "Sign in with web3 Wallet" -- and you're good to go. It's a password that rules all sites while protecting your data and identity and making it easier to surf the web.

1. The Rise of GameFi

Currently, in the traditional gaming environment, players either pay for games up front, pay monthly, or buy digital assets in free-to-play games.

However, no matter what game they play, every action they take and every item/character they acquire is not theirs. It is stored by that game, and if the player stops playing or paying for it, it lies dead in a server they have no control over. Current game studios usually have strict terms of service that prohibit players from making any "real money transactions".

This means that all the time players invest in the game and all the value they add to the game universe does not belong to them. The current system does not allow players to take advantage of it, and if they try to circumvent the rules, they will be permanently banned.

The time is ripe to overturn this market. Allowing players to take ownership of the time and money they put into blockchain-powered games through verifiable NFTs will create opportunities for both the game and the player.

We may soon live in a world where moms stop saying "why waste your time playing games" and instead say "I don't understand what Jimmy is doing with these games, but he can pay for all his stuff."

The gaming industry is currently more profitable than all other media industries combined, but until now, gamers have been left out of the equation. web3 gaming is not some fairy tale fantasy, it is a reality that is already taking shape.

Unfortunately, there is a huge lack of well-developed playable web3 games. But in this bear market, keep an eye out for games that are playable and have a strong community.

These are the games you want to try.

Some of the games I'm watching closely are

Influence: Space strategy massively multiplayer online game Parallel: Sci-fi card game Loot Realms: economics and chivalry massively multiplayer on-chain game Guild of Guardians: Mobile RPG

The road ahead is windy

It's still early days for web3, and a lot of development and user experience design is needed to propel us to the next level.

To support this growing ecosystem, some big things are still needed.

Layer 2 solutions to be fully operational and provide the base layer with the ability to support the number of transactions to support massive adoption and utility A successful merger of Ethernet to shut down Proof of Work (PoW) and move to Proof of Stake (PoS) The user experience of bringing new users into these platforms and products improves to the point where it rivals the web2 experience we enjoy today. We don't know when the next bull market will come. But we are working our way out of the bear market and looking forward to the next bull market that will deliver real utility and mass adoption.

Creators and brands can maximize their revenue by targeting different fans' willingness to pay in three ways.

1. Ads can target regular fans who are not willing to pay anything.

2. Subscriptions can target active fans who are willing to pay a small fee.

3. NFT can target superfans who are willing to pay a lot

   But I now believe that NFT membership is better than a traditional subscription. The reasons are as follows.

   1. Creators and their communities own NFT

   Imagine you're a live stream host on Twitch.

   As a traditional subscription, Twitch sets your subscription price and share of revenue. If Twitch decides to cut creator compensation, then you will have no easy way to move your community to another platform.

   With an NFT membership, on the other hand, you can have NFT in your community. no platform can dictate how you interact with your fans. 2, creators can personalize NFT membership

   With a traditional subscription, the benefits and terms are usually predetermined. For example, on Twitch, you can only offer benefits like custom emojis to paid subscribers.

   With an NFT membership, you can personalize the NFT.

   look and feel. For example, a collection of pfp (profile pictures) can be created that fans can show off to spread the word.
   
   Terms. Can control casting prices, NFT quantities and royalties on secondary sales.
   
   Benefits. Allows NFT holders to access private communities, premium content, IRL events, etc.
   

   Since NFTs are programmable, the content offered is limited only by your creativity: the

   The NFT look and feel may change if fans perform specific tasks. 
   
   NFT may be a bundle that grants access to many creators' content.
   

   1. Creators and their communities share the benefits

   With a traditional subscription, fans who have supported the creator from the beginning don't see any benefits as the creator becomes more and more popular.

   With NFT membership, both creators and fans can share in the benefits as NFT becomes more valuable in the community. Disadvantages of NFT membership

   As the saying goes, "With great power comes great responsibility."

   Because NFT membership gives creators and the community control over its outcome, it's important to understand some common pitfalls.

   1. Traders may snap up your NFT and ruin the atmosphere of your community.

   Traders can come into your community and snap up all the NFTs without giving true fans a chance to share in the revenue at all.

   To avoid this, you can whitelist fans and set parameters so that one person cannot buy too many NFTs at once. 2. Fans can be excluded from NFT membership.

   If all goes well, your NFT collection will increase in value as the community grows. As a result, new fans may be excluded (not to mention Gas fees!) .

   To avoid this, you can issue subsequent NFTs at a lower price for fans who can't afford the OG collection. you can also use L2 and other L1 chains to avoid gas. 3. Fans may react negatively to NFT.

   Unfortunately, many creators and fans have a bad impression of NFT due to scams and people who want to make money fast. Therefore, if you pursue NFT membership without clearly communicating your value proposition, you may alienate some fans. Fans can see right through your true intentions, so ask yourself this question.

   Do you want to make a quick profit or build a sustainable community? How to Practice

   Let's assume again that you are a Twitch anchor.

   When you're just starting out, you can rely on Twitch to grow your audience. 
   
   After reaching a certain size, you decide to invite fans to join an owned community (Discord is not 100% owned, but it is a tight proxy).
   
   Based on the community's input you launch your first collection of NFT members. You decide the mint price, the number of NFTs and the membership benefits. 
   
   Fans who buy your NFT are motivated to spread your content because they share in the benefits. At some point, your OG NFT collection becomes too expensive for new fans to purchase.
   
   You and your community decide to release a new NFT collection to attract more fans to become owners. 
   

   All in all, I think NFT members are the future of subscriptions because they allow fans to share the benefits and allow creators to target multiple fans willing to pay

   I think this is one of the most exciting trends in web3.