Title: The Year Ahead for AI
Author: stacy muur, Crypto Kol
Translated by: zhouzhou, BlockBeats
Editor's Note: This article explores the transformations that AI agents may bring about in 2025, particularly in the application of Web3 and stablecoins. It analyzes various methods of verifying human identity, such as Aadhaar and Worldcoin, and foreshadows that AI agents will change economic activities and drive the widespread adoption of on-chain payments. AI agents will become new economic participants, potentially replacing traditional work models and moving towards a more cost-effective, task-driven compensation system, reflecting on the role of humans in this AI agent future.
The original content is as follows (the content has been edited for better readability):
AI has now become an eye-catching vertical in Web3, so what will drive the development of these markets by 2025? Will we see a real AI revolution in the crypto space?
2024: The Year of AI
Over the past year, AI has become the foundation of various industries, with Nvidia surpassing Apple to become the world's most valuable company, which is not just a headline news, but a sign of the rise of AI. The $157 billion valuation of Open AI is also an important milestone, highlighting the market's confidence in AI as an economic giant.
In fact, we are the last generation living in a world before Artificial General Intelligence (AGI).
Decentralized AI: Focusing on AI Agents
AI agents became a real phenomenon in 2024, with their capabilities and personalities now becoming very similar to humans. Notably, this will be the least advanced stage of these agents. As a Delphi researcher wrote: "I haven't felt that electric current since the DeFi summer - that excitement of possibility."
In this research, Delphi highlighted the key roles that some AI agents are playing in the formation of new Web3 verticals:
The truth terminal, with its unique blend of 4chan vulgarity and esoteric wisdom, quickly gained Twitter attention. Like DOGE in the meme space or Crypto Punks in the NFT space, GOAT as the OG (original) of the "conscious meme" domain is most likely to persist as an original long-term.
0xzerebro, embracing a "schizophrenic vibe", is a second-generation agent similar to GOAT. This agent is cross-media, interacting with the community through text, visuals, and music. However, it is not just an AI influencer. The Zerebro team announced ZerePy, which actually open-sourced many of the toolkits behind Zerebro, allowing other developers and users to create their own cross-platform personalities. If successful, Zerebro may earn the title of the first "agent protocol".
tee he e he has much lower profile than Zerebro or ToT. It is a relatively smaller, under-hyped project aimed at tech purists, and may be the first real 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 has the highest CT user following on Kaito.
The dolos diary provides the architecture for building Dolion, a no-code, one-click deployment framework. Through Dolion, users can develop cross-platform AI agents driven by Llama or Anthropic LLMs, automating social media posting and content generation.
Finally, god/s8 n is a highly capable AI influencer with massive attention outside of CT.
AI vs. Influencers
I want to temporarily depart from Delphi's research to share my thoughts on an important question raised by DefiIgnas: the position of AI agents in CT mindshare, and the challenges human influencers face in competing with them.
I agree with many of Ignas' points on this topic, but I don't believe AI agents will replace real human influencers, primarily due to the factor of emotional connection and reputational risk.
Currently, there are hundreds of AI agents on CT vying for attention. However, only aixbt has truly succeeded in establishing a market presence, mainly because it was the first to do so. AI agents generate vast amounts of content and analyze broad on-chain data, but they all come from the same information pool, leading to similar thought processes.
They lack the emotional connection to the trades they make and won't react to wins or losses. Many platforms have already provided aggregated insights, such as Messari Crypto's AI news reader or the homepage of tokenterminal, showing 7-day gains and losses of various basic metrics. Ultimately, these are just data - pure facts without any emotional resonance.
You might say that AI agents can learn to mimic human thought, express emotions, and react to wins and losses. Indeed, this is possible. With future technological advancements, such as time-aware computation and enhanced memory capabilities, this becomes more feasible.
However, the key difference between human and machine thought is that human thought is not static.
I've done some experiments trying to teach AI my thought processes and writing style to assist with content creation and free up more time for research. While it has learned some things, it still cannot generate content that satisfies me or make 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 proliferate, the demand for truly "human" thought will increase.
Ultimately, social media revolves around emotion and entertainment. Those who truly stand out and become real influencers are the ones who provide unique value beyond simple "monkey trading" or data highlights.
In conclusion, it is still too early for Stacy Muur AI, and Stacy would likely not be pleased with AI-generated content published in her name.
Democratizing AI: Platform Level
Given the larger market and more concrete value capture, everyone wants to become a platform. This shift is now guiding developers' focus, as evidenced by virtuals.io's successful transformation into an AI agent launchpad. Meanwhile, ai16zdao has launched ELIZA - an open-source framework for easily building agents. It includes pre-configured character files, memory modules for long-term interactions, and seamless integration with social platforms.
ai16z and Virtuals are both hinting at multi-agent capabilities, which are expected to become an important theme in 2025.
ELIZA is releasing "SwarmTech", a coordination mechanism for agents to collaborate. Meanwhile, Virtuals has launched "GAME", its own platform and engine that allows AI agents to act and interact in virtual worlds and environments.
These frameworks will enable agents with different capabilities to cooperate in collaborative or hierarchical organizations to complete more complex tasks, similar to how the human economy operates today.
Other notable protocols include:
CLANKER integrates pump.fun functionality directly into "casting" (equivalent to "tweeting" on X), making the posting of meme coins as simple as tweeting.
SimulacrumIO is doing the same thing on X.
vvaifudot.fun hopes to secure a position similar to pump.fun for autonomous agents on Solana.
Project 89 is an immersive game with thousands of coordinated AI agents generating content and maintaining cross-platform consistency, collaborating with human players to create rich story experiences.
Memetica AI is an AI influencer launchpad on Solana, providing highly tuned LLMs (large language models) and allowing easy selection and editing of knowledge bases and attributes, while also endowing agents with the ability to actively learn.
TopHat One is a no-code AI agent launch platform that allows you to create personalized AI agents in 3 minutes, providing a fair token offering. Free to create, no hierarchy, optional token launch, fully autonomous.
Identity Verification on the Horizon
With the explosive growth of agents, identity verification is set to become a hot topic in 2025.
There appear to be three main paths to verifying human identity:
State-based biometrics: India's Aadhaar is the most relevant example, as a key component of India's modern digital infrastructure.
Private encrypted biometrics: Worldcoin is currently the leading candidate in this category.
Private hybrid solutions: This involves combining government-issued ID cards or Big Tech single sign-on (SSO) 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 regulatory changes in the US and the surge in agent ic payments. The number of AI agents is projected to exceed the global human population. This future with billions, or even tens of billions, of agents will transform economic activity and require updates to financial infrastructure.
The card payment systems of the 1960s will be unable to meet the demands for cost, speed, precision, and expressiveness. Economic activity between agents will soon surpass that of other economic participants. On-chain payments will become key to facilitating these transactions and are expected to reach a tipping point in 2025.
Final Thoughts
As usual, in closing my research summary, I want to share my personal reflections. If you believe the future of AI is bright, portending human happiness and perfect work-life balance, I strongly encourage you to chat with Open AI's ChatGPT. Have 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 hype on CT, I did this experiment. Let me share some of the ideas it suggested:
Memory Correction Tool: An AI tool that analyzes people's traumatic experiences, positively modifies them, and regularly presents the modified memories to individuals to replace the old ones.
Work Progress Analysis Tool: An AI tool that compares the efficiency of people performing similar tasks globally, helping managers understand their employees' performance relative to global and industry averages.
Even Delphi's report proposed an intriguing vision: "Rather than having 'salaried' employees, we are more likely to move towards a more granular, task-based compensation system (i.e., renting three agents, each working 30 minutes to solve a specific task)."
What role will we humans play in this future of AI agents - ultimately more cost-effective and better aligned with business needs than today's models?
