tag: hallucinations

Hallucination And Innovation At DAC
By Brian Bailey - 31 Jul, 2025 - Comments: 0

At DAC this year, I had the pleasure of moderating an intimate chat between Alon Shtepel, senior director for ASIC at Micron, and Abhi Kolpekwar, vice president and general manager for digital verification technology at Siemens EDA. The assigned topic was generative AI in design and verification, with the more provocative subtitle asking if we are hallucinating or innovating? L-R: Brian ... » read more

AI In Chip Design: Tight Control Required
By Ed Sperling - 16 Jul, 2025 - Comments: 0

Executive Outlook: Semiconductor Engineering sat down with a panel of experts to talk about what's needed to effectively leverage AI, who benefits from it, and where software-defined hardware works best, with Bill Mullen, Ansys fellow; John Ferguson, senior director of product management at Siemens EDA; Chris Mueth, senior director of new markets and strategic initiatives at Keysight; Albert Ze... » read more

Iteration And Hallucination
By Brian Bailey - 26 Jun, 2025 - Comments: 0

Iteration loops have been a vital aspect of EDA flows for decades. Ever since gate delays and wire delays became comparable, it became necessary to find out if the result of a given logic synthesis run would yield acceptable timing. Over the years this problem became worse because one decision can affect many others. The ramifications of a decision may not have been obvious to an individual too... » read more

Can Models Created With AI Be Trusted?
By Brian Bailey - 06 May, 2024 - Comments: 0

EDA models that are created using AI need to pass more stringent quality and cost benefit analysis compared to many AI applications in the broader industry. Money is hanging on the line if AI gets it wrong, and all the associated costs must be factored into the equation. Models are some of the most expensive things a development team can create, and it is important to understand the value th... » read more

Dealing With AI/ML Uncertainty
By Karen Heyman - 25 Apr, 2024 - Comments: 0

Despite their widespread popularity, large language models (LLMs) have several well-known design issues, the most notorious being hallucinations, in which an LLM tries to pass off its statistics-based concoctions as real-world facts. Hallucinations are examples of a fundamental, underlying issue with LLMs. The inner workings of LLMs, as well as other deep neural nets (DNNs), are only partly kno... » read more

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