Google: Google DeepMind refutes criticism of AI chip design platform AlphaChip

Google DeepMind has published a research paper hitting back at criticism of its AI chip design system AlphaChip. That paper claimed that AlphaChip was able to save thousands of hours of human effort for each new generation of Google TPU AI accelerator, and was already being used by the company to help design its tensor chips.

Markov said that the analysis "demonstrated that Google RL lags behind (i) human designers, (ii) a well-known algorithm (Simulated Annealing), and (iii) generally-available commercial software, while being slower; and in a 2023 open research contest, RL methods weren't in top 5." He also cited a Google whistleblower who was concerned about the paper.

As a result of the growing controversy, Nature added an editor's note on Google's paper and said that it was investigating the research. An independent expert who had reviewed Google’s paper retracted his Nature commentary article that had originally praised Google’s work.

Google claims that Chang's paper failed in multiple ways, including not pre-training and using substantially less compute. It also said that "Markov published baseless allegations of fraud," and added that an internal investigator tracked down the whistleblower who admitted that, while he suspected fraud, "he did not have evidence to support his suspicion of fraud."

The tech giant now says that Nature completed its investigation this April and "found entirely in our favor," removing the editor's note in September. That same month, MediaTek announced it would use AlphaChip as part of its chip development.