Original Text Compilation, Translation: DeepTech TechFlow

Amid the heat of Devcon in Bangkok and the neon lights of the street, AI Memes had their moment to shine.

From Binance's lightning-fast launch of ACT to GOAT breaking new records again, all attention perhaps began with the truth terminal behind the goat --- when an AI Agent can also launch its own coin, everything changed.

Around AI agents, from simple bots to complex intelligent entities, everyone is pondering what other sparks AI and Crypto will create.

Today, Binance Research Institute also released a report on AI Agents, detailing recent highlights related to AI Agents such as coin issuance from the truth terminal, Virtuals' IAO platform, and the new model from daos.fun, and made projections on future trends.

Within the report, a quote from A16Z partner Chris Dixon over 10 years ago is referenced: "The next big thing will start out looking like a toy."

Is it indeed the emergence of the next big thing, or just a flash in the pan? How far can AI Agents go?

DeepTech TechFlow conducted a quick interpretation of the report, presenting the key points.

Key Insights

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

2. Essential characteristics of AI agents: They can autonomously plan and execute tasks, work towards established goals without human intervention. The differences from traditional internet bots are:

· They can make dynamic multi-step decisions

· They can adjust behavior based on interactions

· They can interact with other agents, protocols, and external applications

3. Recent Hot Development Path:

· Terminal of Truths (ToT) as the Trigger: Based on an ancient internet meme, a meme religion was created, leading to the launch of $GOAT

· With $GOAT's market cap surpassing $9.5 billion, ToT becomes the first AI proxy millionaire

· Emergence of Virtuals Protocol's platform, focusing on enabling users to create, deploy, and monetize AI proxies

· Innovation by Daos.fun: Allowing the creation of AI proxy-led hedge funds through a DAO structure, drawing attention from ai16z, enabling community collective investment, and leveraging AI capabilities to enhance performance.

4. Development Prospects and Considerations:

· The evolution from AI 1.0 to AI 2.0 has various implications for Crypto, and we are witnessing a trend of cross-fertilization

· Traditional banks and payment methods often require human identity verification, making cryptocurrencies a natural fit for the AI proxy economy.

· AI models still suffer from the illusion problem, posing significant hurdles; current crypto AI proxies are closer to a proof of concept rather than practical application

· The development momentum is strong, and significant growth may be seen in the coming weeks and months

Definitely Defined: What is the Difference Between AI Agents and Bots?

The key difference between AI agents and traditional bots:

1. Scope:

AI Agent: Can be task-specific or a general assistant, capable of dynamic multi-step decision-making and adjustment based on feedback and interaction

Traditional Bot: Targeted at specific tasks, operates based on predefined rules, and provides a fixed set of responses

2. Level of Autonomy:

AI Agent: Capable of operating autonomously

Traditional Bot: Typically requires some degree of human intervention

3. Self-Reflection Ability:

AI Agent: Capable of reviewing its own work, iterating, and improving output

Traditional Robot: Typically pre-programmed for fixed output, lacks learning and improvement capabilities

4. Collaboration Ability:

AI Agent: Can interact with other agents, APIs, applications; can even autonomously conduct cryptocurrency transactions

Traditional Robot: Usually only capable of generating text-based responses, generally unable to collaborate with external interfaces/other robots

5. Use Cases:

AI Agent: Diverse use cases, can schedule appointments or bookings, act as a financial analyst creating custom strategies

Traditional Robot: Mainly focused on customer service applications, most commonly seen as text-based chatbots on retail/consumer websites

The Genesis of Attention: Terminal of Truths

Origin:

In June 2024, Andy trained a Llama-70B AI model based on the chat logs from the 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), developed its own personality, and started promoting the Goatse religion. In July 2024, Marc Andreessen, co-founder of a16z, discovered ToT and provided a $50,000 grant (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 Know:

This marked the first AI-related meme coin marketed by an autonomous AI agent and may be seen as the first significant AI-crypto collaboration. This event may herald a new subfield of AI consumer applications in the crypto market.

Andy has committed to transferring ToT's wallet to a legal entity (such as a trust) 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 approximately 0.1% of the token supply and ToT holding around 0.2%.

While ToT's story is quite lighthearted and revolves mainly around a meme religion, an interesting X account, and a meme coin, it has indeed raised a question: how will other AI agents act, and what will their objectives be.

An insightful comment:

"A meme coin related to AI being marketed by autonomous AI agents is a noteworthy event. We may look back on this moment as the first significant AI crypto collaboration to capture industry attention."

Initial AI Agent Offering (IAO) Platform, Launched by Virtuals

Virtuals Protocol Core Definition:

A platform that enables users to create, deploy, and monetize AI agents; provides a plug-and-play solution similar to Shopify to allow gaming and consumer apps to easily deploy AI agents

Mainly focuses on agents in the gaming and entertainment sectors, as they see these as the most sticky subdomains in the market

Basic Operation:

· Each AI agent created issues 10 billion exclusive tokens

· These tokens are added to a liquidity pool to establish a market for agent ownership

· Users can purchase these tokens to participate in key decisions for agent development

Initial Agent Offering (IAO):

The tokens for new agents are paired with $VIRTUAL tokens and locked in a liquidity pool

Adopts a fair distribution mechanism with no internal allocation or pre-mining

Revenue Mechanism:

An AI agent generates revenue through interacting with users and forming cooperative relationships; token holders benefit from a buyback and burn mechanism

Designed to induce deflationary effects on the agent token, which may increase the remaining token's value

Incentive Mechanism:

The protocol allocates $VIRTUAL token rewards to the top three agents; measured by the total value locked (TVL) in their respective liquidity pools, aiming to incentivize the creation of high-quality agents and ongoing innovation

Luna is not just a token with impressive gains; it is an entertainment-focused AI agent:

It is the lead singer of an AI influencer and AI girl group, livestreaming 24/7 on the official page; the TikTok official account has over 500,000 followers, possesses a self-controlled wallet, and can automatically send $LUNA tokens to interactive users.

Future Development:

Seeking to replicate the successful model of pump.fun in the meme coin space but focused on AI agents

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

A recent update introduced a new feature unlock mechanism based on market value milestones, such as self X posting, TG chats, on-chain wallets, etc.

AI Agent Hedge Fund: daos.fun

Core Definition:

daos.fun enables the creation of AI agent-led hedge funds using a DAO structure; while the platform was initially designed for humans, it has now embraced the AI agent concept

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

Upon completion of the fundraising, fund managers can use the raised $SOL to invest in the Solana protocol; DAO tokens are tradable on the daos.fun page, and the token's value depends on the fund's trading performance.

a16z Case Study:

Developer Shaw created an AI agent named pmairca modeled after Marc Andreesen; it established the related hedge fund ai16z

Becoming the largest hedge fund DAO on the platform, with a market cap that once approached 100 million USD (although it has since declined); still holding the largest asset under management on the platform

Future Outlook:

Considering that AI agents can operate efficiently 24/7, potentially offering unique advantages compared to human-operated funds, it will still take time to validate whether AI agents are truly capable of independently managing funds. It is worth monitoring the developments in this area.

The Meta-Narrative of AI Agents: What Insights Can It Offer Us?

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

AI 1.0: Tools such as ChatGPT and Perplexity are essentially advanced versions of Google search, providing near-instantaneous information retrieval.

AI 2.0: Represents a significant advancement, introducing agent-based systems that can potentially work for us in the background continuously. This goes beyond being a "smart Google."

Agent Capabilities: Capable of performing tasks without continuous user input, interacting with other agents, applications, APIs, and protocols, and automating complex tasks.

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

2. The Intersection of AI and the Crypto Community

Mutual Influence: More and more individuals in the crypto space are earnestly exploring the world of AI, considering how AI concepts can be integrated into various crypto domains.

AI Enthusiasts Exploring Blockchain: AI enthusiasts are also beginning to delve deeper into the world of blockchain and crypto.

Mutually Beneficial: This genuine mutual interest is exciting and may give rise to the next significant AI-crypto application.

3. A Match Made in Heaven?

Limits of Traditional Systems: Traditional banks and payment methods typically require human identity verification, posing a challenge for the AI agent economy.

Advantages of Cryptocurrency:

· Flexibility: Cryptocurrency naturally lends itself to the AI agent economy.

· Instant Settlement: Compared to traditional methods, blockchain allows for faster (usually instant) on-chain settlement.

· Smart Contract: Enables transactions that are more complex than traditional methods.

· Permissionless Wallet Creation: Particularly suitable for peer-to-peer transactions.

4. Use Case: The World's Best KOL?

Disruption in the Digital Space: AI agents could become the "world's best KOL"—a tireless, 24/7 interactant influencer.

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

DeFi Applications: Personalized financial advisors, specialized traders, and more.

Multi-Agent Era: With the growing number of on-chain agents, inter-agent interaction is poised to be a key growth area.

In Joy and Prudence

Phantom Problem: AI models still face issues generating incorrect, misleading, or meaningless information.

Blockchain Infrastructure Challenges:

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

· Cross-Chain Compatibility: The crypto world is still 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 a demo stage than a finished product. Much work is needed to scale them to fully autonomous agents with real-world crypto expertise.

Challenges from Web2 Itself: The Web2 ecosystem lacks standardization, which could lead to information fragmentation, increasing the work complexity 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 appear particularly groundbreaking, they can set off a wave of innovation and experimentation that defines an entire era.

Clearly, this process is already underway, with the especially exciting development being the growing intersection between the AI and crypto communities. The next few months promise to be very interesting as we look forward to seeing how this emerging subfield evolves.

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

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

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