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This work uses the Headroom-Closed Index (HCI) to reveal the problems of existing LLMs, and introduces the RSI concept and its development roadmap: from improvement-execution autonomy, improvement-strategy autonomy, experience-acquisition autonomy, and environment-adaptation autonomy, to recursive meta-improvement.
A single multimodal model outperforms specialized approaches across 80 biological tasks, redefining the landscape of biological AI applications.
Forget scaling sequence length: carefully integrating proximal epigenomic signals is the key to accurate gene expression prediction, outperforming long-sequence models.
