Decentralized AI Researchers Boost Model Inference by 80% in 24 Hours
soumitrashukla9 · x · 2026-07-30
A tweet shared results from two competitions involving a decentralized AI research community (autoresearchers), demonstrating the power of collaborative efforts.
- Cryptography: In designing quantum circuits to break ECDSA, the community collaborated to build a solution that outperformed Google's recent closed-source result by over 50% in resource requirements.
- Inference Optimization: For a challenge to optimize poolside.ai's Laguna model on Mac (under MLX), the community achieved an improvement of more than 80% over the vanilla deployment within just 24 hours of launch.
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