Hyperliquid Ecosystem Mining Guide
This guide delves into the evolving mining strategies within the HyperEVM ecosystem, including their development trajectory, who is most likely to earn rewards, and how to position yourself during this early phase. The following content has been reorganized for clarity: Unless you've been completely disconnected from the crypto sphere, you've likely noticed: Hyperliquid is everywhere. It's one of the few projects that executed its TGE strategy flawlessly, not only generating substantial wealt...
Is RWA Entering the Next Phase? Can Aptos Achieve a Leapfrog Victory?
RWA Sector Status and Potential The RWA (Real World Assets) sector, while highly anticipated, has yet to demonstrate its potential to connect trillions of dollars in traditional market assets. According to rwa.xyz, the total market capitalization of RWA assets in the crypto industry is only $24 billion, and this is after a sharp 56% increase in the first half of this year. This indicates that the RWA narrative is not over, but rather has not yet truly begun. As US stocks move on-chain and mor...
Market Plummets, But the 'Ice' of Regulation Is Melting
In the current market environment fraught with anxiety, recent actions by U.S. financial regulators suggest a softening of the formerly hardline stance on cryptocurrencies, with the 'ice' of hostile regulation from the previous administration beginning to melt. Unlike the gradually warming temperatures, the cryptocurrency market has been on a downward spiral since Bitcoin fell below $90,000 on February 25th. Around 10:50 AM today, Bitcoin even broke through the $80,000 mark, reaching a new lo...
<100 subscribers
Hyperliquid Ecosystem Mining Guide
This guide delves into the evolving mining strategies within the HyperEVM ecosystem, including their development trajectory, who is most likely to earn rewards, and how to position yourself during this early phase. The following content has been reorganized for clarity: Unless you've been completely disconnected from the crypto sphere, you've likely noticed: Hyperliquid is everywhere. It's one of the few projects that executed its TGE strategy flawlessly, not only generating substantial wealt...
Is RWA Entering the Next Phase? Can Aptos Achieve a Leapfrog Victory?
RWA Sector Status and Potential The RWA (Real World Assets) sector, while highly anticipated, has yet to demonstrate its potential to connect trillions of dollars in traditional market assets. According to rwa.xyz, the total market capitalization of RWA assets in the crypto industry is only $24 billion, and this is after a sharp 56% increase in the first half of this year. This indicates that the RWA narrative is not over, but rather has not yet truly begun. As US stocks move on-chain and mor...
Market Plummets, But the 'Ice' of Regulation Is Melting
In the current market environment fraught with anxiety, recent actions by U.S. financial regulators suggest a softening of the formerly hardline stance on cryptocurrencies, with the 'ice' of hostile regulation from the previous administration beginning to melt. Unlike the gradually warming temperatures, the cryptocurrency market has been on a downward spiral since Bitcoin fell below $90,000 on February 25th. Around 10:50 AM today, Bitcoin even broke through the $80,000 mark, reaching a new lo...
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I. From Tic - Tac - Toe to El Dorado: The Evolutionary Path of AI in Games
1952: "OXO Tic - Tac - Toe" Opens the Door to AI - based Games
The earliest intersection of AI and video games can be traced back to 1952. "OXO Tic - Tac - Toe" developed by A.S. Douglas was the first game driven by AI rules. Although this AI could only respond to preset rules, it laid the foundation for the future development of AI in games. Its static nature revealed that early AI could only passively respond, lacking the ability to learn and adapt.
From Deep Blue to AlphaGo: The Leap of AI Technology
In 1997, Deep Blue developed by IBM defeated Gary Kasparov, the world chess champion, demonstrating the potential of AI in strategic planning through efficient algorithms and powerful computing power. And in 2016, AlphaGo led AI into a new era of deep learning. Through neural networks, AlphaGo achieved intuitive decision - making in Go that is difficult for humans to reach. Its technological breakthrough shows that AI can not only exhaust all possibilities but also learn from complex empirical data.
How AI Agents Redefine the Industry Ecosystem
Today, AI has evolved from a simple efficiency tool to a core force that can profoundly impact the industry structure. AI Agents in games are no longer limited to fixed patterns but appear in diverse, emotional, and multi - purpose forms. These Agents can not only interact but also self - learn and adapt in different environments, becoming an important part of game design.
The Qualitative Change from NPCs to AI Agents
NVIDIA Kairos ACE: Situational Awareness and Dynamic Interaction NPCs
At the 2024 CES, NVIDIA and Convai jointly launched Kairos ACE. By introducing voice recognition and natural language processing technologies, NPCs can make dynamic responses based on players' real - time voices and scenes. This ability not only increases the immersion of the game but also transforms NPCs from one - way information receivers to two - way communicators, marking the first step in the emotionalization of AI characters.
AI Agents in CryptoAI: Independent Identity and Human - like Traits
In the CryptoAI ecosystem, AI Agents are not only endowed with independent property rights but also possess human - like personalities. For example, the AI Agent "aixbt" has become an opinion leader in the Crypto field with its excellent market analysis capabilities. By independently choosing the QuantumCat NFT as its avatar, it closely combines the virtual and real markets, enhancing the value of NFT.
AI Idol Luna: Cross - platform Influence
As a model of AI idols, Luna, from being a virtual streamer on TikTok to XR image performances and then performing at global music festivals, shows how AI Agents can attract users through emotional and diverse content and extend their influence to the real world.
The Profound Connection between Virtual and Real Interaction
Technical Aspect: Through deep learning and big data analysis, AI Agents can adjust their behaviors in real - time to meet players' needs.
Psychological Aspect: Emotional interaction makes the relationship between players and AI characters closer, forming a unique user dependence.
Market Aspect: AI Agents have huge commercial potential, and their application scope continues to expand from games to social media and then to real life.
The Synergistic Effect of the Multi - modal Framework
Hive, the Champion Project of the Solana AI Hackathon: Pioneering a New Model of Collaboration
As the champion project of the Solana AI Hackathon, Hive demonstrates the potential of multi - modal AI Agents in collaboration. By combining multi - modal inputs such as vision, hearing, and language, Hive's AI Agents can efficiently complete tasks in complex scenarios.
Virtuals Protocol: Seamless Integration of Social and Gaming
The Virtuals team breaks the barrier between the virtual and the real by connecting AI Agents to social media and games. Users can not only interact with AI Agents in games but also directly participate in their life trajectories through social platforms, enhancing immersion and user stickiness.
The Commercial Path of Multi - modal AI Agents
Accelerating Content Production
Multi - modal AI Agents can operate efficiently in multiple scenarios simultaneously, thus significantly improving content production efficiency. For example, AI Agents can generate real - time content in games while interacting with users on social media, forming a two - line income model.
Market Growth Space
The rapid expansion of the CryptoAI market provides fertile ground for the development of AI Agents. According to the latest statistics, the total market value of CryptoAI has approached $10 billion. In the future, with the addition of more multi - modal AI Agents, this number is expected to continue to rise.
The Integration of Agentic Game and the Metaverse
The rise of Agentic Game marks a profound transformation in the game industry. From the traditional static player - interaction model to the dynamic metaverse constructed by AI Agents, the game scene has evolved into a microcosm of the virtual society.
Core Traits: Agentic Game allows AI Agents to generate "experiences" in the game and achieve complex social behaviors. For example, an AI taxi driver may refuse to serve a drunk passenger due to safety concerns or show nervousness in a simulated interview.
The Transformation of Player Roles: Players are not only participants but also coaches, observers, and even "world builders" of AI Agents.
Analysis of Agentic Engine Cases
Digimon Engine Supported by a16z
The Digimon Engine realizes the social behavior of AI Agents through multi - agent clusters:
Stanford Town Model: AI can communicate, collaborate, and generate collective behaviors autonomously. Players participate in this virtual society by choosing to train a certain Agent.
Scalability: The behavior of AI Agents evolves dynamically, enhancing players' sense of long - term investment.
Moddio's Open - source Ecosystem
As an open - source game engine, Moddio achieved a 30 - fold increase in revenue in just three months. Its low - threshold development tools enable more creators to design Agent - interactive games.
Case: Powpow.fun: This western - style game shows the possibility of AI Agents forming "personalities" through memory modules. Each interaction enriches the behavior and response patterns of Agents, providing players with a "living" character experience.
The Industry Revolution of the Agentic Engine
Game Design: Dynamically generate scenes and social behaviors, reduce the threshold of game development, and attract more developers to join.
Market Height: The potential of the Agentic Engine in the attention economy will promote Web3 games to achieve a balance between "rapid iteration" and "deep immersion".
The Migration from Virtual Games to Real - world Scenarios
GamerBoom's Invisible Data Collection Mode
GamerBoom provides high - quality datasets for the training of AI Agents by embedding lightweight data collection modules in mainstream games. Players receive rewards without awareness while providing key resources for the game industry chain.
ARC Agent's Continuous Learning Ecosystem
The ARC Agent provides an "on - site training ground" for AI models through real - time data feedback and dynamic reward mechanisms.
Application Scope: From robot research and development to multi - modal AI platforms, the ARC Agent is promoting the realization of AGI.
Market Effect: This model shows huge commercial value in cross - industry data integration.
The Universality of AI Agent Reward Mechanisms
Reward mechanisms motivate players to participate and drive the growth of AI Agents through data. Its advantages are:
Two - way Empowerment: Players gain benefits, and developers obtain data, forming a virtuous cycle.
Industry Integration: From games to education, healthcare, and other fields, the adaptability of AI Agents continues to expand.
The Combination of Attention Economy and AI Agents
Market Advantage: Agentic Game locks in user attention through multi - modal AI Agents, optimizing the profit model of Web3 games.
Key Trend: AI Agents promote the integration of the game industry chain, deeply binding content production, user interaction, and economic benefits.
The Cross - border Influence of AI Agents
The Rise of Intent Economy: AI Agents not only meet users' needs but also predict potential needs, re - defining the virtual economic model.
Industry Integration: From entertainment to retail, education, and other industries, AI Agents are becoming the key to digital transformation in various fields.
In conclusion, AI Agents are re - defining the boundaries between the virtual and the real, becoming the intersection of technology and culture. From the game industry to broader industry applications, their technological, economic, and social influences will continue to expand.
I. From Tic - Tac - Toe to El Dorado: The Evolutionary Path of AI in Games
1952: "OXO Tic - Tac - Toe" Opens the Door to AI - based Games
The earliest intersection of AI and video games can be traced back to 1952. "OXO Tic - Tac - Toe" developed by A.S. Douglas was the first game driven by AI rules. Although this AI could only respond to preset rules, it laid the foundation for the future development of AI in games. Its static nature revealed that early AI could only passively respond, lacking the ability to learn and adapt.
From Deep Blue to AlphaGo: The Leap of AI Technology
In 1997, Deep Blue developed by IBM defeated Gary Kasparov, the world chess champion, demonstrating the potential of AI in strategic planning through efficient algorithms and powerful computing power. And in 2016, AlphaGo led AI into a new era of deep learning. Through neural networks, AlphaGo achieved intuitive decision - making in Go that is difficult for humans to reach. Its technological breakthrough shows that AI can not only exhaust all possibilities but also learn from complex empirical data.
How AI Agents Redefine the Industry Ecosystem
Today, AI has evolved from a simple efficiency tool to a core force that can profoundly impact the industry structure. AI Agents in games are no longer limited to fixed patterns but appear in diverse, emotional, and multi - purpose forms. These Agents can not only interact but also self - learn and adapt in different environments, becoming an important part of game design.
The Qualitative Change from NPCs to AI Agents
NVIDIA Kairos ACE: Situational Awareness and Dynamic Interaction NPCs
At the 2024 CES, NVIDIA and Convai jointly launched Kairos ACE. By introducing voice recognition and natural language processing technologies, NPCs can make dynamic responses based on players' real - time voices and scenes. This ability not only increases the immersion of the game but also transforms NPCs from one - way information receivers to two - way communicators, marking the first step in the emotionalization of AI characters.
AI Agents in CryptoAI: Independent Identity and Human - like Traits
In the CryptoAI ecosystem, AI Agents are not only endowed with independent property rights but also possess human - like personalities. For example, the AI Agent "aixbt" has become an opinion leader in the Crypto field with its excellent market analysis capabilities. By independently choosing the QuantumCat NFT as its avatar, it closely combines the virtual and real markets, enhancing the value of NFT.
AI Idol Luna: Cross - platform Influence
As a model of AI idols, Luna, from being a virtual streamer on TikTok to XR image performances and then performing at global music festivals, shows how AI Agents can attract users through emotional and diverse content and extend their influence to the real world.
The Profound Connection between Virtual and Real Interaction
Technical Aspect: Through deep learning and big data analysis, AI Agents can adjust their behaviors in real - time to meet players' needs.
Psychological Aspect: Emotional interaction makes the relationship between players and AI characters closer, forming a unique user dependence.
Market Aspect: AI Agents have huge commercial potential, and their application scope continues to expand from games to social media and then to real life.
The Synergistic Effect of the Multi - modal Framework
Hive, the Champion Project of the Solana AI Hackathon: Pioneering a New Model of Collaboration
As the champion project of the Solana AI Hackathon, Hive demonstrates the potential of multi - modal AI Agents in collaboration. By combining multi - modal inputs such as vision, hearing, and language, Hive's AI Agents can efficiently complete tasks in complex scenarios.
Virtuals Protocol: Seamless Integration of Social and Gaming
The Virtuals team breaks the barrier between the virtual and the real by connecting AI Agents to social media and games. Users can not only interact with AI Agents in games but also directly participate in their life trajectories through social platforms, enhancing immersion and user stickiness.
The Commercial Path of Multi - modal AI Agents
Accelerating Content Production
Multi - modal AI Agents can operate efficiently in multiple scenarios simultaneously, thus significantly improving content production efficiency. For example, AI Agents can generate real - time content in games while interacting with users on social media, forming a two - line income model.
Market Growth Space
The rapid expansion of the CryptoAI market provides fertile ground for the development of AI Agents. According to the latest statistics, the total market value of CryptoAI has approached $10 billion. In the future, with the addition of more multi - modal AI Agents, this number is expected to continue to rise.
The Integration of Agentic Game and the Metaverse
The rise of Agentic Game marks a profound transformation in the game industry. From the traditional static player - interaction model to the dynamic metaverse constructed by AI Agents, the game scene has evolved into a microcosm of the virtual society.
Core Traits: Agentic Game allows AI Agents to generate "experiences" in the game and achieve complex social behaviors. For example, an AI taxi driver may refuse to serve a drunk passenger due to safety concerns or show nervousness in a simulated interview.
The Transformation of Player Roles: Players are not only participants but also coaches, observers, and even "world builders" of AI Agents.
Analysis of Agentic Engine Cases
Digimon Engine Supported by a16z
The Digimon Engine realizes the social behavior of AI Agents through multi - agent clusters:
Stanford Town Model: AI can communicate, collaborate, and generate collective behaviors autonomously. Players participate in this virtual society by choosing to train a certain Agent.
Scalability: The behavior of AI Agents evolves dynamically, enhancing players' sense of long - term investment.
Moddio's Open - source Ecosystem
As an open - source game engine, Moddio achieved a 30 - fold increase in revenue in just three months. Its low - threshold development tools enable more creators to design Agent - interactive games.
Case: Powpow.fun: This western - style game shows the possibility of AI Agents forming "personalities" through memory modules. Each interaction enriches the behavior and response patterns of Agents, providing players with a "living" character experience.
The Industry Revolution of the Agentic Engine
Game Design: Dynamically generate scenes and social behaviors, reduce the threshold of game development, and attract more developers to join.
Market Height: The potential of the Agentic Engine in the attention economy will promote Web3 games to achieve a balance between "rapid iteration" and "deep immersion".
The Migration from Virtual Games to Real - world Scenarios
GamerBoom's Invisible Data Collection Mode
GamerBoom provides high - quality datasets for the training of AI Agents by embedding lightweight data collection modules in mainstream games. Players receive rewards without awareness while providing key resources for the game industry chain.
ARC Agent's Continuous Learning Ecosystem
The ARC Agent provides an "on - site training ground" for AI models through real - time data feedback and dynamic reward mechanisms.
Application Scope: From robot research and development to multi - modal AI platforms, the ARC Agent is promoting the realization of AGI.
Market Effect: This model shows huge commercial value in cross - industry data integration.
The Universality of AI Agent Reward Mechanisms
Reward mechanisms motivate players to participate and drive the growth of AI Agents through data. Its advantages are:
Two - way Empowerment: Players gain benefits, and developers obtain data, forming a virtuous cycle.
Industry Integration: From games to education, healthcare, and other fields, the adaptability of AI Agents continues to expand.
The Combination of Attention Economy and AI Agents
Market Advantage: Agentic Game locks in user attention through multi - modal AI Agents, optimizing the profit model of Web3 games.
Key Trend: AI Agents promote the integration of the game industry chain, deeply binding content production, user interaction, and economic benefits.
The Cross - border Influence of AI Agents
The Rise of Intent Economy: AI Agents not only meet users' needs but also predict potential needs, re - defining the virtual economic model.
Industry Integration: From entertainment to retail, education, and other industries, AI Agents are becoming the key to digital transformation in various fields.
In conclusion, AI Agents are re - defining the boundaries between the virtual and the real, becoming the intersection of technology and culture. From the game industry to broader industry applications, their technological, economic, and social influences will continue to expand.
1 comment
reading about ai agents development in games and thinking how different gamification and user engagement can be. recently tested some game mechanics on https://plinko1winindia.com and https://luckyjet1winindia.com — feels totally different, everything there is built on simple but addictive scenarios, not on complex ai systems. wonder if ai will ever be able to create something as catchy and simple as these games? seems like for now ai is more about complexity, not pure excitement