Ensuring Accuracy in LLM-Generated Hardware Logic Design Automation (IBM Research)


A new technical paper "Mitigating hallucinations and omissions in LLMs for invertible problems: An application to hardware logic design automation" was published by researchers at IBM Research. Abstract "We show for invertible problems that transform data from a source domain (for example, Logic Condition Tables (LCTs)) to a destination domain (for example, Hardware Description Language (... » read more

System Bits: Oct. 2


Computer algorithms exhibit prejudice based on datasets Researchers at Cardiff University and MIT have shown that groups of autonomous machines are capable of demonstrating prejudice by identifying, copying, and learning this behavior from one another. The team noted that while it may seem that prejudice is a human-specific phenomenon that requires human cognition to form an opinion of, or ... » read more