According to @VitalikButerin, he is more excited by open-weights AI models with strong editing functionality than models focused solely on creation from scratch [source: @VitalikButerin on X]. Open-weights models are those whose parameters are publicly released, enabling local control, customization, and reproducible deployment for developers, as outlined by Hugging Face documentation and Meta’s Llama open-weight releases [sources: Hugging Face; Meta AI]. The post contains no mention of ETH, tokens, or roadmap changes, so there is no direct trading signal from this statement alone [source: @VitalikButerin on X]. The focus on editable open-weights aligns with current on-chain AI and zkML experiments that rely on modifiable local models for verifiable inference on Ethereum, as demonstrated by Modulus Labs’ proof-of-inference work, which frames where developer attention may translate into future tooling rather than immediate price action [source: Modulus Labs].