Google's claims of super-human AI chip layout back under the microscope
A Google-led research paper published in Nature, claiming machine-learning software can design better chips faster than humans, has been called into question after a new study disputed its results.for developing a reinforcement-learning-based system capable of automatically generating optimized microchip floorplans.
Producing a floorplan today usually involves a mix of manual work and automation using chip design applications. Google's team sought to demonstrate that its reinforcement-learning approach would produce designs better than those made just by human engineers using industry tools. Not only that, Google said its model completed its work much faster than engineers iterating over layouts.
to prepare a layout for the model to iterate over. It's argued these Synopsys tools may have given the model a decent enough head start that the AI system's true capabilities should be called into question. The use of Synopsys' software to prime Google's software needs to be investigated, he said."We all just want to know the actual algorithm so we can reproduce it. If [Google's] claims are right, then we want to implement it. There should be science, it should all be objective; if it works, it works," he said.it is looking into Google's paper, though it did not say exactly what it was investigating nor why.
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