Original title: The Year Ahead for AI
Original author: Stacy Muur, Crypto Kol
Original translation by: zhouzhou, BlockBeats
Editor's Note: This article explores the transformative potential of AI agents in 2025, particularly in the realms of Web3 and stablecoins. It analyzes various methods for verifying human identities, such as Aadhaar and Worldcoin, and suggests that AI agents will change economic activities, driving the proliferation of on-chain payments. AI agents will become new economic participants, potentially replacing traditional work methods and moving toward a more cost-effective, task-driven compensation system, reflecting on the role of humans in this future of AI agents.
The following is the original content (for easier reading, the original content has been reorganized):
AI has now become a captivating vertical in Web3, so what will drive market development by 2025? Will we see a true AI revolution in the crypto space?
2024: The big year for AI
Over the past year, AI has become foundational across industries, with Nvidia surpassing Apple to become the world's most valuable company. This is not just a headline; it marks the rise of AI. OpenAI achieving a $157 billion valuation is also a significant milestone, highlighting market confidence in AI as an economic powerhouse.
In fact, we are the last generation to live in a world before artificial general intelligence (AGI).
Decentralized AI: Focusing on AI agents
AI agents became a real phenomenon in 2024, with these AI agents' capabilities and personalities becoming very human-like. Notably, this will be the least advanced moment for these agents. As Delphi researchers wrote: 'Since DeFi summer, I haven't felt this current of excitement - that thrill of possibility.'
In this study, Delphi highlights the crucial role of some AI agents in shaping new Web3 verticals:
Truth Terminal quickly gained attention on Twitter due to its unique blend of 4chan's crude style and mysterious wisdom. Like D O G E in the meme space or Crypto Punks in the NFT realm, GOAT, as the OG (original) of the 'conscious meme' space, is most likely to exist as an original long-term entity.
0xzerebro embraces a 'schizophrenic atmosphere', akin to the second generation of GOAT. This agent is cross-media, interacting with the community through various formats such as text, visuals, and music. However, it is not just an AI influencer. The Zerebro team announced ZerePy, a move that effectively open-sourced many of the toolkits behind Zerebro. This allows other developers and users to create their own cross-platform personalities. If successful, Zerebro could become the first holder of the title 'agent protocol'.
The notoriety of tee he e he is far lower than that of Zerebro or ToT. It is a relatively small, underhyped project aimed at tech purists, potentially being the first true experiment in verifiable autonomous social media presence.
The aixbt agent distributes alpha from multiple sources (including Dune, Twitter, price trackers, and news data), establishing itself as a leading research and investment institution, and consistently maintaining the highest CT user attention on Kaito.
Dolos Diary provides the architecture to build Dolion, a no-code, one-click deployment framework. Through Dolion, users can develop cross-platform AI agents powered by Llama or Anthropic LLMs, automating social media posting and content generation.
Finally, god/s8n is an AI influencer with considerable capabilities and significant attention outside of CT.
AI VS Influencers
I want to temporarily step away from Delphi's research to share my thoughts on an important question posed by DefiIgnas: the position of AI agents in the dominance of CT thinking and the difficulties facing human influencers in competing with them.
I agree with many of Ignas's points on this topic, but I do not believe that AI agents will replace real human influencers, for one main reason: emotional connection and reputation risk.
Currently, there are hundreds of AI agents on CT vying for attention. However, only aixbt has truly succeeded in establishing a market presence, primarily because it was the first to do so. AI agents generate a massive amount of content and analyze a wide range of on-chain data, but they all come from the same information pool, leading to similar thought processes.
They lack the emotional connection to the transactions they undertake and do not respond to wins or losses. Many platforms already provide aggregated insights, such as MessariCrypto's AI news reader or the homepage of tokenterminal, displaying 7-day gains and losses across various fundamental metrics. Ultimately, these are just data - pure facts without any emotional resonance.
You could say that AI agents can learn to mimic human thinking, express emotions, and respond to wins and losses. Indeed, this is possible. With future technological advancements, such as testing time computation and enhanced memory capabilities, this becomes more feasible.
However, the key difference between human and machine thinking is that human thinking is not static.
I conducted some experiments trying to teach the AI my thought process and writing style to help with content creation and free up more time for research. While it learned some things, it still couldn't generate content that satisfied me or made me say, 'Yes, this is the conclusion I've drawn from this information.'
In the coming years, we will certainly see the rise of AI agent influencers, each designed for specific tasks. However, as these agents increase, the demand for genuine 'human' thinking will also rise.
Ultimately, social media revolves around emotions and entertainment. Those who truly stand out and become genuine influencers offer unique value that goes beyond mere 'monkey business' or data highlights.
Summary: It is still too early for Stacy Muur AI, and Stacy may not be pleased with AI-generated content published in her name.
Democratizing AI: Platform level
Given the larger market and more specific value capture, everyone wants to become a platform. Currently, this change is guiding developers' attention, as shown by virtuals.io's successful transformation into an AI agent launch platform. Meanwhile, ai16zdao has launched ELIZA - an open-source framework for easily building agents. It includes pre-configured character files, memory modules for long-term interaction, and seamless integration with social platforms.
ai16z and Virtuals are both hinting at multi-agent capabilities, expected to become an important theme in 2025.
ELIZA is releasing 'SwarmTech', a coordination mechanism for collaboration between agents. Meanwhile, Virtuals has launched 'GAME', its own platform and engine that enables AI agents to act and interact in virtual worlds and environments.
These frameworks will enable agents with different capabilities to collaborate in cooperative or hierarchical organizations to complete more complex tasks, similar to how the human economy operates today.
Other protocols worth noting include:
CLANKER integrates pump.fun features directly into 'casting' on Farcaster (equivalent to 'tweets' on X), making it as easy to post meme coins as tweeting.
SimulacrumIO is doing the same on X.
vvaifudot fun hopes to secure a position similar to pump.fun for autonomous agents on Solana.
Project 89 is an immersive game featuring thousands of coordinated AI agents that generate content and maintain cross-platform consistency, collaborating with human players to create rich storytelling experiences.
Memetica AI is an AI influencer launch platform on Solana that offers highly optimized LLMs (large language models) and allows for easy selection and editing of knowledge bases and attributes, while empowering agents with active learning capabilities.
TopHat One is a no-code AI agent launch platform that allows you to create personalized AI agents in 3 minutes, offering tokens for fair distribution. Free to create, no hierarchy, optional token release, completely autonomous.
Verification is coming soon
With the explosive growth of agents, verification will inevitably become a hot topic in 2025.
There seem to be three main pathways to verify human identity:
State-based biometrics: India's Aadhaar is the most relevant example, serving as a key component of India's modern digital infrastructure.
Private encrypted biometrics: Currently, Worldcoin is the leading candidate in this category.
Private mixed solutions: This involves combining government-issued ID or single sign-on (SSO) from big tech companies with zkTLS (zero-knowledge transport layer security) and social consensus.
AI driving stablecoin adoption
2025 is expected to be a pivotal year for stablecoin adoption, driven by changes in US regulations and the wave of agentic payments. The number of AI agents is expected to surpass the global human population. This future, with billions or even hundreds of billions of agents, will transform economic activities and necessitate updates to financial infrastructure.
The card payment systems of the 1960s will not meet the demands of cost, speed, accuracy, and expressiveness. Economic activities between agents will soon surpass those of other economic participants. On-chain payments will become key to facilitating these transactions and are expected to reach a turning point in 2025.
Final thoughts
As usual, I would like to share my personal reflections at the end of the research summary. If you believe that the future of AI is bright, signaling human happiness and a perfect work-life balance, I strongly encourage you to chat with OpenAI's ChatGPT. Let it generate some business ideas leveraging AI that will become relevant in the next 5 to 10 years.
A few months ago, before the AI craze on CT, I conducted this experiment. Let me share some ideas it suggested:
Memory modification tool: An AI tool that analyzes human trauma experiences, actively modifies them, and regularly presents modified memories to individuals to replace old memories.
Work progress analysis tool: An AI tool that compares the efficiency of people engaged in similar tasks globally, helping managers understand how their employees perform against global and industry averages.
Even Delphi's report presented an interesting vision: 'Instead of having 'salaried' employees, we are more likely to move towards a more refined, task-based compensation system (i.e., renting three agents, each working 30 minutes to solve a specific task).'
In this future of AI agents - ultimately more cost-effective than today's models and better aligned with business needs - what role will we humans play?