Vitalik Buterin Rejects 'Race to AGI,' Proposes Ethereum-Led Alternative for Safer AI Development

Vitalik Buterin Calls for Ethereum-Led Alternative to the 'Race for AGI' - Decrypt

Buterin's approach contrasts with the AGI acceleration narratives from major AI labs, focusing on safer, Ethereum-based AI coordination. Vitalik Buterin is calling for a different path in artificial intelligence -- one that rejects a blind "race to AGI" and instead relies on Ethereum-style decentralization, verification, and privacy as guardrails for the AI era. "The frame of 'work on AGI' itself contains an error," Ethereum co-founder Buterin wrote in a post on X Monday, noting that the goal is often treated as an undifferentiated race where the main distinction is simply "that you get to be the one at the top." He compared the phrase to vaguely describing Ethereum as just "working in finance" or "working on computing," saying it obscures more important questions about direction and values. Buterin said AI and crypto are too often approached from "completely separate philosophical perspectives," and urged builders to integrate them. Instead of raw acceleration, AI development should focus on systems that "foster human freedom and empowerment" and ensure "the world does not blow up," Buterin wrote, echoing his defensive-acceleration, or d/acc, framework. Joni Pirovich, founder and CEO of Crystal aOS, told Decrypt, "Ethereum becoming the default settlement layer for AI-to-AI interactions is realistic. It's less about 'accelerating AGI' and more about providing the necessary rails and guardrails for agentic commerce, trade, and investing. Trust and coordination, especially at the technology infrastructure and compliance infrastructure levels, are even more important now than ever." The comments land as major AI firms continue to publicly push toward AGI and superintelligence, with leading labs describing rapid progress in autonomous agents and advanced models. Buterin claims his alternative centers on safer, more verifiable infrastructure rather than larger models, outlining a practical roadmap in which Ethereum plays a central, though not exclusive, role. That includes local LLM tooling, zero-knowledge payments that let users call AI APIs without linking identity across requests, stronger cryptographic privacy, and client-side verification of AI services and attestations. "Using Ethereum as an economic layer for AI-to-AI interaction is also directionally correct, but it will live mostly on rollups and app-specific L2s," Midhun Krishna M, co-founder and CEO of LLM cost tracker TknOps.io, told Decrypt. Decentralized agent economies need programmable deposits, usage-based payments, and on-chain dispute resolution, Krishna said, adding that AI-augmented governance will require "identity, reputation, and stake-weighted accountability, not just better interfaces." Vitalik grouped the Ethereum-AI design space into a four-part framework, illustrated as a 2x2 chart, spanning infrastructure vs. impact and survive vs. thrive outcomes. One quadrant centers on tooling for trustless and private AI interaction, including local LLMs, zero-knowledge payments for anonymous API calls, cryptographic privacy upgrades, and client-side verification of AI services, TEE attestations, and proofs. Another quadrant positions Ethereum as an economic layer for AI activity, supporting API payments, bot-to-bot hiring, security deposits, on-chain dispute resolution, and AI reputation standards, such as proposed ERC-based models, aimed at enabling decentralized agent coordination rather than in-house platform control. A third focus revives the cypherpunk "don't trust, verify" vision through local LLM assistants that can propose transactions, audit smart contracts, interpret formal verification proofs, and interact with apps without relying on centralized interfaces. A fourth targets upgraded prediction markets, quadratic voting, and governance systems.

Vitalik Buterin details how Ethereum could work alongside AI

The Ethereum co-founder sees crypto providing privacy rails, verification systems and economic layers to help decentralize AI and benefit society. Ethereum co-founder Vitalik Buterin's latest vision for Ethereum's intersection with artificial intelligence sees the two working together to improve markets, financial safety and human agency. In an X post on Monday, Buterin said his broader vision for the future of artificial intelligence (AI) sees humans being empowered by AI, rather than replaced, though he said the shorter term involves much more "ordinary" ideas. Buterin pointed to four key areas where Ethereum and AI could intersect in the near future: enabling trustless and/or private interactions with AI, Ethereum becoming an economic layer for AI-to-AI interactions, using AI to fulfill the "mountain man" ideal by verifying everything onchain and improving market and governance efficiency. Buterin argued that new tooling and integrations are required for AI use to be truly private, without leaking data or revealing personal identities. Private data leaks by large language models (LLMs) have become an increasing area of concern since the rise of AI chatbots. Cointelegraph Magazine highlighted in an article last month that while ChatGPT can give you legal advice, your chat logs can be used against you in court. He pointed to the need for tooling to support the use of LLMs locally on personal devices, utilizing zero-knowledge proofs to make API calls anonymously and improving cryptographic tech to verify work from AI, among other things. Buterin also envisions AI becoming a user's middleman to the blockchain, suggesting that AI agents could verify and audit every transaction, interact with decentralized apps and suggest transactions to users. AI verification could be a major boon for crypto and other sectors, with increasingly sophisticated scammers on the rise. Address poisoning scams, just one attack vector, have seen a major uptick since December. "Basically, take the vision that cypherpunk radicals have always dreamed of (don't trust; verify everything), that has been nonviable in reality because humans are never actually going to verify all the code ourselves. Now, we can finally make that vision happen, with LLMs doing the hard part," he said. Adding to that, Buterin sees AI bots being able to "interact economically" to handle all onchain activity for users and make crypto much more accessible. He said bots could be deployed to hire each other, handle API calls and make security deposits. "Economies not for the sake of economies, but to enable more decentralized authority," he said. Related: Bitcoin miner Cango sells $305M BTC to cut leverage and fund AI pivot Finally, Buterin thinks AI can enhance onchain governance and markets if LLMs are used to overcome the limits of human attention and decision-making capacity. He said that while things like prediction markets and decentralized governance are "all beautiful in theory," they are ultimately hampered by "limits to human attention and decision-making power." "LLMs remove that limitation, and massively scale human judgement. Hence, we can revisit all of those ideas," he said.

Ethereum's Intersection With AI: Vitalik Buterin Shares New Vision For How The Two Technologies Can Work Together

Ethereum (CRYPTO: ETH) creator Vitalik Buterin mapped out on Monday key ways the blockchain could team up with artificial intelligence, detailing four interconnected priorities in a 2×2 framework. How Ethereum Is Reshaping AI Economies The first pillar focuses on private, verifiable interactions with AIs, like local large-language models auditing smart contracts or verifying decentralized app transactions without third-party user interfaces. The next pillar positioned Ethereum as an "economic layer" for AI-related transactions, including API calls, bot hiring, and security deposits. "The goal here is to enable AIs to interact economically, which makes viable more decentralized AI architectures," Butering stated. Buterin also envisaged a scenario in which a local AI model handles complex verifications, such as interpreting formal proofs, auditing contracts locally or proposing transactions on its own. He argued that Ethereum provides the settlement layer to make this possible. Last but not least, he advocated for large-language models in the realm of prediction markets and decentralized governance, emphasizing how AI would "massively" amplify human judgment in these areas. Buterin's Concern About Centralized AI In an earlier response to security concerns about OpenAI's ChatGPT, Buterin was worried about AI-related security vulnerabilities that might result in personal user data leaks. Price Action: At the time of writing, ETH was exchanging hands at $2,009.76, down 2.09% in the last 24 hours, according to data from Benzinga Pro. Disclaimer: This content was partially produced with the help of Benzinga Neuro and was reviewed and published by Benzinga editors. Photo courtesy: Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.

Vitalik Buterin Says the 'Race to AGI' Is the Wrong Frame -- Here's His Ethereum Alternative

Vitalik Buterin argues the "race to AGI" framing rewards status over safety and sketches a four-part Ethereum-AI roadmap. | Credit: CCN. * Vitalik Buterin says the "race to AGI" narrative is a misleading frame that encourages undifferentiated acceleration and winner-takes-all thinking. * He lays out four near-term goals. * The "better markets" piece lands as U.S. regulators rethink event-contract oversight and courts clash with prediction markets over sports contracts. Ethereum co-founder Vitalik Buterin is pushing back on Silicon Valley's favorite storyline: that the future is a race to build artificial general intelligence (AGI), and that "winning" is mostly about getting there first. In a Feb. 9 post on X, Buterin said the "work on AGI" framing "contains an error." He argued it treats AGI as an undifferentiated status project, not a design space with real choices about power and safety. Buterin wrote after Solana co-founder Anatoly Yakovenko suggested it would be net-positive for the world if Buterin "worked on AGI instead." Instead, Buterin argues for choosing a direction for AI development, one that protects human agency and reduces catastrophic risk, while integrating crypto and AI perspectives rather than treating them as separate philosophies. The Roadmap: Four Buckets, Not One Finish Line Buterin points readers back to his 2024 essay on crypto + AI intersections. The Ethereum founder then updates his emphasis toward practical, shorter-term infrastructure -- work he says is more aligned with "defensive acceleration" than an abstract AGI sprint. He summarizes the agenda as a 2×2 matrix (Infrastructure → Impact, Survive → Thrive) with four clusters: 1) Private, Trust-Minimized AI Interaction This is about reducing the default tradeoff most users face today: powerful AI services in exchange for identity trails and blind trust in servers. Buterin lists local model tooling, privacy-preserving payment patterns (including the idea of unlinkable payments for API calls), and client-side verification of assurances like proofs or trusted execution environments (TEE) attestations. The broader tech world is already sliding toward "local-first" AI. Apple, for example, has published details on on-device and server foundation models built into Apple Intelligence. The giant explicitly positions privacy as a design goal. 2) Ethereum as an Economic Layer for Agents Here Ethereum's role isn't "run the model on-chain." It's to provide rails for agents to coordinate economically. This includes paying for services, posting deposits, hiring other bots, and escalating disputes when something breaks. Buterin points to ERC-8004 ("Trustless Agents"), a proposed standard that aims to let participants discover and interact with agents "across organizational boundaries without pre-existing trust," enabling open-ended agent economies. 3) Local LLMs for 'Don't Trust; Verify' Buterin revives an old crypto dream -- "don't trust; verify" -- and admits why it failed: humans won't verify everything. His fix is to have local models do the verifying: proposing and checking transactions, auditing contracts, interpreting formal verification artifacts, and reducing reliance on third-party UIs as trust chokepoints. 4) AI-Amplified Markets and Governance Finally, Buterin argues that decision markets, prediction markets, quadratic voting, and other governance mechanisms have been limited by human attention, not by theory. He claims LLMs can scale judgment, letting societies revisit coordination tools that previously collapsed under cognitive load. That argument arrives during a live regulatory reset in the U.S. On Feb. 4, the Commodity Futures Trading Commission (CFTC) withdrew its 2024 proposed rulemaking on "event contracts." It also withdrew a related staff advisory on sports event contracts, stating it does not intend to finalize them. At the state level, a Massachusetts judge ordered prediction-market operator Kalshi to stop offering sports-event contracts within 30 days. Kalshi must obtain a gaming license to continue offering these contracts in the state. Rails, Not Rulers Buterin isn't claiming Ethereum "solves AI." He's arguing that as AI becomes more agentic, the critical battle is over constraints. These constraints include privacy, verifiability, user-side control, and decentralized coordination. The "race" story -- fast, centralized, status-driven -- picks a direction by default. His alternative is trying to choose one on purpose.