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Omni-modal foundation models achieve self-improvement via RL compute scaled to 1M context, leveraging asynchronous training and agentic grading for enhanced intelligence.
Clover fixes nearly all RTL bugs while covering significantly more cases than traditional and LLM-based methods, showcasing a breakthrough in automated program repair.
LLMs fixing hardware bugs struggle with the complexity of SoCs, where performance drops below 65%, revealing a significant gap compared to simpler core designs.