Bittensor is experiencing a new round of demand growth, and Virtuals and ElizaOS are also worth paying attention to.

Written by: 0xJeff

Translated by: Asher

As global economic uncertainty intensifies and market sentiment remains low, Web3 AI continues to be one of the most reflexive growth sectors.

The rapid advancement of AI innovations (such as the strategies of tech giants like OpenAI, Anthropic, DeepSeek, Nvidia, Alibaba, etc.) has kept it in the spotlight.

Currently, the total market capitalization of the AI sector has rebounded to $6 billion after falling to a low of $4 billion in March. Despite the overall market environment being under pressure, some teams are still exploring AI Agent scenarios applicable to the crypto ecosystem. From the early proliferation of conversational AI assistants to today's more focused solutions addressing real problems, several new trends have emerged:

• Sports analysis and automated betting: AI Agents analyze event data in real-time and autonomously execute betting decisions;

• Trading assistance and execution: Smart assistant AI Agents can analyze market trends and execute complex trades;

• DeFi yield optimization: Agent systems can adjust stablecoin lending strategies in real-time to optimize yields.

The Transformation of DeFAI: From Abstract Layer to "Alpha Discovery Layer"

Earlier this year, the hot trend in DeFAI was to build ChatGPT-style interfaces as an interaction layer between users and DeFi protocols. However, practice has shown that merely providing a conversational interface does not lead to a good user experience. The issue lies in the insufficient investment by most teams in the "reasoning layer" (understanding user intent) and the "execution layer" (optimizing execution paths), resulting in AI Agents still relying on users' additional judgments when providing strategic advice. For example, rather than using an AI Agent to select the optimal trading path, it is often more effective to use established tools like Defillama Aggregator, Across, or Pendle directly.

As a result, many projects are transitioning to the "Alpha Discovery Layer," which helps users discover the most valuable information in the market. In a market environment where information is scarce, finding the best "gold mining points" is key. For example:

• On-chain data analysis: Tracking smart wallets and fund flows to obtain leading signals;

• Social platform information mining: Analyzing trending topics on X, Telegram, and Discord to capture trends;

• Advanced risk management: Such as GigabrainGG, providing institutional-level trading signals.

Currently, it is not yet determined whether existing AI Agents can consistently provide excess Alpha, but some early results have begun to show value.

Multimodal / Multichannel AI Agents

Traditional ChatGPT-style interaction methods are not suitable for all scenarios, and Web3 AI Agents are exploring new interaction methods to integrate more naturally into users' daily workflows.

• Direct interaction on the X platform: Cryptocurrency communities are primarily active on the X platform, so agents like Clanker and Bankr are providing services directly through X, simplifying user operation paths;

• Discord voice commands: AgentTank allows users to directly control AI to execute on-chain tasks via voice within Discord, achieving more efficient collaboration;

• Web3 browsing and execution: Since many crypto websites do not provide APIs, Computer Use Agents can simulate human operations to automatically navigate, scrape data, and execute trades across different websites.

These multimodal / multichannel AI Agents are redefining the user experience in Web3, making AI a true part of the trading and research process.

Virtuals: The Core Platform of the AI Agent Ecosystem

The AI Agent tokenization platform of Virtuals has been running for 6 months. Although the overall ecosystem's market capitalization has decreased due to market fluctuations, the number of agents has grown from 50 to 716, still making it a leader in the AI Agent field. Currently, the most active application scenarios on Virtuals include:

• GambleFAI: Like Billy Bets, it has performed excellently in the AI betting market, even making it into the top eight of the ProphetX prediction competition, with an ROI of up to 30%;

• Sports analysis: Like HeyTracyAI, providing AI-driven analysis and commentary for NBA events;

• Robotics and embodied AI: SAM is promoting the development of Embodied AI, aiming to build a decentralized AI computing ecosystem similar to Bittensor;

• Alpha discovery: Like aixbt and Acolyt, focusing on on-chain data analysis and trading signal provision.

Virtuals is also developing the Agent Commerce Protocol (ACP), aimed at enabling AI agents to work together to create a more efficient economic system. The two earliest application scenarios may be agent hedge funds and agent media centers.

Bittensor as AI Infrastructure

Bittensor, with the token Tao, is experiencing a new round of demand growth. Previously, many users only used TAO for staking on the Root Network, but now more people are willing to invest TAO into specific subnet tokens to support concrete AI applications.

• The dTAO model launched in February: The TAO inflation distribution is determined by the market rather than by validator weight. This means that high-value subnets recognized by the market will receive more TAO incentives;

• Growth in practical applications: Subnets like SN6, 41, and 44 are supporting consumer-grade AI Agents, such as Billy Bets and DKING, expanding Bittensor's practical application scenarios.

ElizaOS V2 Version and New Launchpad Platform Autofun

ElizaOS has been one of the most popular AI agent development frameworks, and its V2 version is about to be released. Meanwhile, the new Launchpad platform Autofun will go live in two weeks, with 15 projects ready to join the ecosystem.

• Current status of ElizaOS: It currently has 15.3k GitHub Stars and 5k Forks, with its market influence continuously expanding;

• The funding management issues of AI Agents: Sentient recently released research revealing security vulnerabilities in funding management for AI Agents like ElizaOS, highlighting the need for stronger security measures in this field.

Despite the challenges, the ecosystem growth of ElizaOS remains rapid, and its decentralized GPU hosting solution Comput3 AI will also debut on the Autofun platform.

Conclusion

AI Agents remain one of the most promising sectors in Web3, as they not only bring together innovations in AI and crypto but also have the potential to reshape the productivity and working methods of the entire industry. From AI trading assistants to cross-chain information capture, from yield optimization to automated execution, AI is bringing a new paradigm to Web3.

All of this is reminiscent of the internet wave of the 1990s, but on a larger scale and with more far-reaching impacts. For early participants, now is the best time to enter.

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