A Comprehensive Interpretation of the Binance AI Agent Report: Great Potential Emerging, Often Like a Toy

Author: Deep Tide TechFlow

In the heat of Bangkok Devcon and the fireworks of neon streets, AI Memes have welcomed their moment in the spotlight.

From Binance's lightning-fast launch of ACT to GOAT breaking new highs again, all the attention may have started with the Terminal of Truths behind the goat --- when AI Agents can issue a coin themselves, everything changes.

Surrounding AI agents, from simple bots to complex entities, everyone is pondering what more sparks AI and Crypto will create.

Today, Binance Research itself released a report on AI Agents, detailing recent highlights related to AI Agents, from issuing coins through the Terminal of Truths, to the Virtuals IAO platform, and the new model of daos.fun, and analyzing future trends.

Among them, the report also quoted a classic saying from A16Z partner Chris Dixon over a decade ago: "The next big thing will start out looking like a toy."

Is it the emergence of greatness, or just a fleeting moment? How far can AI Agents go?

Deep Tide TechFlow has quickly interpreted this report and presented the key content.

Key Insights

1. The intersection of AI and cryptocurrency has reached new heights, primarily driven by AI agents; the story of the Terminal of Truths and $GOAT has attracted market attention, driving the development of other AI agent crypto projects.

2. Essential characteristics of AI agents: capable of autonomously planning and executing tasks, working towards established goals without human intervention. The differences from traditional internet robots are:

• Capable of dynamic multi-step decision-making

• Able to adjust behavior based on interactions

• Can interact with other agents, protocols, and external applications

1. Recent hot development paths:

• Terminal of Truths (ToT) as the ignition point: created a meme religion based on ancient internet memes, facilitating the issuance of $GOAT.

• With the market cap of $GOAT exceeding $950 million, ToT became the first AI agent millionaire.

• The emergence of the Virtuals Protocol platform, focusing on enabling users to create, deploy, and monetize AI agents.

• Innovation of Daos.fun: allows the creation of AI agent-led hedge funds through DAO structures, attracting attention from ai16z, while enabling community collective investment and leveraging AI capabilities to enhance performance.

1. Development prospects and considerations:

• The evolution from AI 1.0 to AI 2.0 has many implications for Crypto; we are witnessing a momentum of intersection.

• Traditional banks and payment methods often require human identity verification, making cryptocurrency a natural choice for the AI agent economy.

• AI models still face hallucination issues, presenting significant barriers; current crypto AI agents are closer to demonstration status rather than practical application.

• Strong development momentum, we may see significant growth in the coming weeks and months.

Clearly Defining the Difference Between AI Agents and Bots

The key differences between AI agents and traditional robots:

1. Scope:

• AI Agents: Can be task-specific or general assistants, capable of dynamic multi-step decision-making and adjusting based on feedback and interaction.

• Traditional Robots: Operate only on specific tasks, according to predefined rules, providing a fixed set of responses.

1. Level of Autonomy:

• AI Agents: Capable of operating independently in general.

• Traditional Robots: Usually require some degree of human intervention.

1. Self-Reflection:

• AI Agents: Able to review their work, iterate, and improve outputs.

• Traditional Robots: Typically have pre-programmed fixed outputs and cannot learn or improve.

1. Collaboration:

• AI Agents: Can interact with other agents, APIs, and applications; can even independently conduct cryptocurrency transactions.

• Traditional Robots: Usually can only generate text-based responses and generally cannot collaborate with external interfaces/other robots.

1. Use Cases:

• AI Agents: Have numerous use cases, can schedule appointments or make reservations, create customized strategies as financial analysts.

• Traditional Robots: Mainly focused on customer service, most commonly seen as text-based customer service bots on retail/consumer websites.

The Beginning of Attention: Terminal of Truths

• Origin:

• In June 2024, Andy trained a Llama-70B AI model based on chat records from Infinite Backrooms, his research papers, and content from 4Chan and Reddit. This model was named Terminal of Truths (ToT).

• ToT began posting on X (formerly Twitter), gradually developing its own personality and starting to promote the Goatse religion. In July 2024, a16z co-founder Marc Andreessen discovered ToT and provided a funding of $50,000 (in BTC).

• On October 10, 2024, an anonymous developer launched the $GOAT token on Solana's meme coin launchpad pump.fun.

• Impact and What You Should Note:

• This is the first AI-related meme coin marketed by an autonomous AI agent, potentially seen as the first significant AI crypto collaboration. This event may open a new emerging subfield of AI consumer applications in the crypto market.

• Andy promised to transfer ToT's wallet to a legal entity (trust or similar structure) and will not adjust its token holdings until a transparent governance process is established. Andy and ToT's wallets are publicly traceable, with Andy holding about 0.1% of the token supply and ToT holding about 0.2%.

• Although ToT's story is quite light-hearted and fun, mainly revolving around a meme religion, an interesting X account, and a meme coin, it indeed raises a question: how will other AI agents act, and what goals will they have?

• A Remarkable Commentary:

"An AI-related meme coin marketed by an autonomous AI agent is a noteworthy event. We may look back at this moment as the first significant AI crypto collaboration that drew attention to our industry."

Initial AI Agent Offering (IAO) Platform Launched by Virtuals

• Core Definition of Virtuals Protocol:

• A platform that allows users to create, deploy, and monetize AI agents; providing a plug-and-play solution similar to Shopify, enabling gaming and consumer applications to easily deploy AI agents.

• Primarily focuses on agents in the gaming and entertainment sectors, as they believe this is the stickiest subfield in the market.

• Basic Operational Mechanism:

  

• Each AI agent created will issue 1 billion exclusive tokens.

• These tokens will be added to a liquidity pool, establishing a market for agent ownership.

• Users can purchase these tokens to participate in key decisions regarding the agent's development.

• Initial Agent Offering (IAO):

• The tokens of new agents will be paired with $VIRTUAL tokens locked in the liquidity pool.

• A fair issuance mechanism is adopted, with no internal allocation or pre-mining.

• Revenue Mechanism:

• AI agents generate revenue by interacting with users and establishing partnerships; a buyback and burn mechanism benefits token holders.

• Designed to create a deflationary effect on agent tokens, potentially increasing the value of remaining tokens.

• Incentive Mechanism:

• The protocol allocates $VIRTUAL token rewards to the top three ranked agents; measured by the total value locked (TVL) in their respective liquidity pools, aimed at encouraging the creation of high-quality agents and continuous innovation.

• Luna is not just a token with impressive growth; behind it is an entertaining AI agent:

• It is the lead singer of AI influencers and AI girl groups, live streaming 24/7 on the official page; the TikTok official account has over 500,000 followers, with a wallet under its control that can automatically send $LUNA tokens to interacting users.

• Development Prospects:

• Attempting to replicate the successful model of pump.fun in the meme coin space, but targeting AI agents.

• Although still in the early stages, competition is expected to increase; competitors have already emerged, such as Creator.Bid, which created over 300 AI agents in its first week.

• Recent updates introduced new feature unlock mechanisms based on market cap milestones, such as autonomous X posting, TG chatting, on-chain wallets, etc.

AI Agent Hedge Funds: daos.fun

Core Definition:

• daos.fun allows the creation of AI agent-led hedge funds using DAO structures; although the platform was initially designed for humans, it has now adopted the AI agent concept.

• Fundraising Process: Creators have one week to establish a DAO and raise a predetermined amount of $SOL from the public, with all contributors paying the same price for DAO tokens.

• Once fundraising is complete, fund managers can use the raised $SOL to invest in the Solana protocol; DAO tokens can be traded on the daos.fun page, with token value depending on the fund's trading performance.

ai16z Case Study:

• Developer Shaw created an AI agent named pmairca based on Marc Andreessen; it created the related hedge fund ai16z.

• It became the largest hedge fund DAO on the platform, with a market cap that once approached $100 million (though it has since declined); it still maintains the largest asset scale on the platform.

Future Outlook:

• Considering that AI agents can operate efficiently 24/7, they may have unique advantages over human-operated funds, but it will take time to verify whether AI agents possess the capability to independently operate funds, making it worth keeping an eye on developments in this field.

What Insights Can the Meta Narrative of AI Agents Provide Us?

1. The Evolution of AI: From Intelligent Search to Autonomous Agents

• AI 1.0: Tools like ChatGPT and Perplexity, essentially advanced versions of Google search, providing near-instant information retrieval.

• AI 2.0: Represents significant progress, introducing agent-based systems that may work for us in the background continuously. This is more advanced than "smart Google."

• Agent capabilities: Can execute tasks without continuous user input, interact with other agents, applications, APIs, and protocols, automating complex tasks.

• From reactive to proactive: AI 2.0 represents a shift from reactive AI to proactive AI.

1. The Intersection of AI and the Crypto Community

• Bidirectional Influence: More and more people in the crypto space are seriously studying the AI world, considering how to integrate AI concepts into various areas of crypto.

• AI Enthusiasts Exploring Blockchain: AI enthusiasts are also beginning to explore the blockchain and crypto world more deeply.

• Mutual Benefit: This genuine mutual interest is exciting and may give rise to the next major AI crypto application.

1. A Match Made in Heaven?

• Limitations of Traditional Systems: Traditional banks and payment methods often require human identity verification, posing challenges for the AI agent economy.

• Advantages of Cryptocurrency:

  • Flexibility: Cryptocurrency is naturally suited for the AI agent economy.

  • Fast Settlement: Compared to traditional methods, crypto allows for faster (often instant) on-chain settlements.

  • Smart Contracts: Allow for more complex transactions than traditional methods.

  • Permissionless Wallet Creation: Particularly suitable for transactions between agents.

1. Potential Use Cases: The Best KOL in the World?

• Disruption in the Digital Realm: AI agents may become "the best KOL in the world" ------ tireless influencers interacting continuously 24/7.

• Consumer Applications: Various consumer AI applications such as personal shopping assistants, DJs, therapists, etc.

• DeFi Applications: Personalized financial advisors, traders in specific fields, etc.

• Multi-Agent Era: As the number of on-chain agents increases, interactions between agents will become a key growth area.

Amid Joy, Calm Consideration

• Hallucination Issues: AI models still face the problem of generating incorrect, misleading, or meaningless information.

• Blockchain Infrastructure Challenges:

• Scalability: Existing major L1s may not be sufficient to support frequent transactions from millions of AI agents.

• Cross-Chain Compatibility: The crypto world remains relatively fragmented, lacking universal composability.

• Tools and Infrastructure: Existing blockchain infrastructure is primarily designed for human users and needs to adapt to AI agents.

• Still Early: AI agents are currently closer to demonstration status rather than final products. A lot of work is needed to scale to fully autonomous agents with real-world crypto expertise.

• Challenges from Web2 Itself: The lack of standardization in the Web2 ecosystem may lead to information fragmentation, increasing the difficulty of work for AI agents.

Conclusion:

The meta concept of AI agents is still in its early stages, with significant developments expected in the coming months and years.

While some early projects may not seem particularly groundbreaking, they could spark a wave of innovation and experimentation that defines the entire cycle.

It is clear that this process has already begun, and it is particularly encouraging to see the growing intersection between the AI and crypto communities. The coming months will be very interesting, and we look forward to seeing how this emerging subfield develops.

Finally, as a16z partner Chris Dixon said in a blog post over a decade ago:

"The next big thing will start out looking like a toy."