Ethereum co-founder Vitalik Buterin has firmly dismissed concerns about artificial intelligence breaking cryptocurrency systems, taking the opposite position from recent bearish predictions. In a post on X platform, Buterin responded to Liron Shapira, co-founder and CEO of Relationship Hero, who claimed there was a 50% chance that Bitcoin would crash by more than 50% within two years as AI undermined security features. Buterin argued that AI would strengthen cybersecurity platforms just as much as it enabled new attacks, and that the risk of actual cracks appearing in Bitcoin's consensus mechanism was 'tiny'. He told Shapira he'd 'offer a bet' against his gloomy prediction, but revealed he was 'basically taking this bet with 90% of my net worth already' through his Ether holdings. As per CoinDesk, Buterin has laid out a case for why artificial intelligence, despite its well-documented tendency to hallucinate and produce buggy code, might actually become the most powerful tool the software world has ever seen for preventing hacks.
Buterin has outlined a comprehensive vision for how artificial intelligence can significantly enhance blockchain security through formal verification methods, describing it as potentially the 'final form' of software development. In a blog post published on May 18, Buterin explored how pairing AI's raw code-generation speed with the mathematical rigor of formal verification could dramatically improve the security of software systems, particularly those underpinning Ethereum's infrastructure. According to his proposal, AI models could generate proof outlines, identify gaps in existing proofs, and suggest invariants that human developers might overlook. Buterin specifically pointed to the Lean theorem prover as a key tool, allowing developers to write proofs that can be mechanically checked, creating a layer of mathematical certainty that traditional code review cannot match. The proposal arrives as blockchain networks continue to suffer multimillion-dollar losses from smart contract vulnerabilities, making the case for stronger, machine-assisted assurance methods increasingly urgent. As per CoinDesk, formal verification uses mathematical proofs to demonstrate that code behaves correctly in all possible scenarios, rather than relying on testing, which only checks a program's behavior against specific scenarios.
Despite his bearish predictions, Bitcoin has faced significant outflows while Ethereum ETFs have attracted substantial inflows. According to latest data, ETH ETFs saw inflows exceeding $1 billion by mid-September, with August recording over $3.5 billion in inflows - the highest level since mid-2025. This contrasts sharply with Bitcoin funds recording cumulative outflows of approximately $1.5 billion since the start of the year. The market dynamics have also been supported by technical indicators, with the ETH/BTC ratio chart showing a 'Golden Cross' pattern in mid-August when the 50-day moving average crossed above the 200-day moving average. On the Bitcoin chart, the 'cross' formed on September 8, with crypto market participants largely foreseeing positive scenarios for the coming months.
Market participants are increasingly bullish on Ethereum's prospects, with real-world event betting platform Polymarket showing the majority of traders betting on a range of $2,300–$2,700 for ETH prices by early October. Trading volume for this event has exceeded $2 million, while most analysts expect the price to hold above $2,750. This optimism comes as Buterin has increasingly begun viewing Bitcoin in a positive light, moving away from his previous criticisms of the leading cryptocurrency. The technical indicators support this bullish sentiment, with the 'Golden Cross' pattern typically considered a bullish trading signal that suggests short-term upward momentum may continue to drive sustained growth in the Ethereum ecosystem. As per CoinDesk, Buterin identified two significant limitations: specification risk, where formal verification proves code matches its specification but if the specification itself is wrong, the proof is worthless, and hardware limitations, where software can be formally verified but physical chips running that software cannot be verified with the same level of rigor.
