Ethereum: A Bullish Turnaround Signals Potential Price Recovery

Recent on-chain data and expert analysis suggest that ethereum (ETH) may have reached a critical cyclical bottom, with whale activity surging and key support levels holding firm. According to Fundstrat's Sean Farrell, Ethereum's price could be nearing its trough, with identified support between $1,360 and $1,770. The cryptocurrency recently tested $1,747 on Binance, potentially marking the low point if historical patterns repeat. Historically, ETH bottomed 39% below its realized price in the 2022 cycle, while the 2025 cycle saw a shallower 21% decline before a strong recovery. This current activity, combined with increased whale transactions, indicates growing confidence among large holders. As of February 2026, the market is closely watching these levels for confirmation of a sustained upward trend. The convergence of technical support, historical precedent, and heightened institutional interest paints a promising picture for Ethereum's near-term trajectory, suggesting that the worst may be over and a new phase of growth could be beginning.

Ethereum May Have Found Its Bottom as Whale Activity Surges

Fundstrat's Sean Farrell suggests Ethereum's price could be nearing a cyclical bottom, with key support levels identified between $1,360 and $1,770. Historical patterns show ETH previously bottomed 39% below its realized price in 2022, while the 2025 cycle saw a shallower 21% decline before recovery. The cryptocurrency recently tested $1,747 on Binance, potentially signaling the trough if historical patterns hold.

On-chain metrics reveal aggressive accumulation, with whale inflows spiking 30.7 times above average. Yet U.S. institutional buying—traditionally necessary for sustained rallies—remains conspicuously absent. Ethereum currently trades at $1,957, down 1% over 24 hours amid broader market pressures.

Vitalik Buterin Proposes AI-Driven Governance Overhaul for Ethereum DAOs

Ethereum co-founder Vitalik Buterin has unveiled a radical proposal to address chronic voter apathy in decentralized autonomous organizations. The plan leverages personal AI agents to automate governance participation while preserving privacy through zero-knowledge proofs.

The system WOULD delegate routine decisions to AI models trained on individual users' historical preferences, reserving only major proposals for human review. Buterin's framework integrates prediction markets to incentivize quality proposals and multi-party computation for sensitive votes.

This initiative emerges amid growing concerns about DAO governance failures, where concentrated token holders dominate decision-making while typical participants remain disengaged. The proposal attempts to reconcile scalability with democratic ideals in decentralized systems.