Google Faces Internal Battle Over Research on AI to Speed Chip Design

The logo of Google is pictured during the Viva Tech start-up and technology summit in Paris, France, May 25, 2018. REUTERS/Charles Platiau
The logo of Google is pictured during the Viva Tech start-up and technology summit in Paris, France, May 25, 2018. REUTERS/Charles Platiau
TT

Google Faces Internal Battle Over Research on AI to Speed Chip Design

The logo of Google is pictured during the Viva Tech start-up and technology summit in Paris, France, May 25, 2018. REUTERS/Charles Platiau
The logo of Google is pictured during the Viva Tech start-up and technology summit in Paris, France, May 25, 2018. REUTERS/Charles Platiau

Alphabet Inc's Google said on Monday it had recently fired a senior engineering manager after colleagues, whose landmark research on artificial intelligence software he had been trying to discredit, accused him of harassing behavior.

The dispute, which stems from efforts to automate chip design, threatens to undermine the reputation of Google's research in the academic community. It also could disrupt the flow of millions of dollars in government grants for research into AI and chips.

Google's research unit has faced scrutiny since late 2020 after workers lodged open critiques about its handling of personnel complaints and publication practices.

The new episode emerged after the scientific journal Nature in June published "A graph placement methodology for fast chip design" led by Google scientists Azalia Mirhoseini and Anna Goldie. They discovered that AI could complete a key step in the design process for chips, known as floorplanning, faster and better than an unspecified human expert, a subjective reference point.

But other Google colleagues in a paper that was anonymously posted online in March - "Stronger Baselines for Evaluating Deep Reinforcement Learning in Chip Placement” found that two alternative approaches based on basic software outperform the AI. One beat it on a well-known test, and the other on a proprietary Google rubric.

Reuters said that Google declined to comment on the leaked draft, but two workers confirmed its authenticity.

The company said it refused to publish Stronger Baselines because it did not meet its standards, and soon after fired Satrajit Chatterjee, a leading driver of the work. It declined to say why it fired him.

"It’s unfortunate that Google has taken this turn," said Laurie Burgess, an attorney for Chatterjee. "It was always his goal to have transparency about the science, and he urged over the course of two years for Google to address this."

Google researcher Goldie told the New York Times, which on Monday first reported the firing, that Chatterjee had harassed her and Mirhoseini for years by spreading misinformation about them.

Burgess denied the allegations, and added that Chatterjee did not leak Stronger Baselines.

Patrick Madden, an associate professor focused on chip design at Binghamton University who has read both papers, said he had never seen a paper before the one in Nature that lacked a good comparison point.

"It's like a reference problem: Everyone gets the same jigsaw puzzle pieces and you can compare how close you come to getting everything right," he said. "If they were to produce results on some standard benchmark and they were stellar, I would sing their praises."

Google said the comparison to a human was more relevant and that software licensing issues had prevented it from mentioning tests.

Studies by big institutions such as Google in well-known journals can have an outsized influence on whether similar projects are funded in the industry. One Google researcher said the leaked paper had unfairly opened the door to questions about the credibility of any work published by the company.

After "Stronger Baselines" emerged online, Zoubin Ghahramani, a vice president at Google Research, wrote on Twitter last month that "Google stands by this work published in Nature on ML for Chip Design, which has been independently replicated, open-sourced, and used in production at Google."

Nature, citing a UK public holiday, did not have immediate comment. Madden said he hoped Nature would revisit the publication, noting that peer reviewer notes show at least one asked for results on benchmarks.
"Somehow, that never happened," he said.



Nvidia Ramps up AI Tech for Games, Robots and Autos

Nvidia CEO Jensen Huang holds a new Nvidia GeForce RTX 5090 graphics card as he gives a keynote address at CES 2025, an annual consumer electronics trade show, in Las Vegas, Nevada, US, January 6, 2025. (Reuters)
Nvidia CEO Jensen Huang holds a new Nvidia GeForce RTX 5090 graphics card as he gives a keynote address at CES 2025, an annual consumer electronics trade show, in Las Vegas, Nevada, US, January 6, 2025. (Reuters)
TT

Nvidia Ramps up AI Tech for Games, Robots and Autos

Nvidia CEO Jensen Huang holds a new Nvidia GeForce RTX 5090 graphics card as he gives a keynote address at CES 2025, an annual consumer electronics trade show, in Las Vegas, Nevada, US, January 6, 2025. (Reuters)
Nvidia CEO Jensen Huang holds a new Nvidia GeForce RTX 5090 graphics card as he gives a keynote address at CES 2025, an annual consumer electronics trade show, in Las Vegas, Nevada, US, January 6, 2025. (Reuters)

Nvidia chief executive Jensen Huang made a rock star appearance at a packed arena late Monday, touting AI chips and software for robots, cars, video games and more.

After years of being on the sidelines at the annual Consumer Electronics Show (CES) in Las Vegas, talk of computer chips was a hot ticket as people queued for hours to fill an arena to hear Huang talk AI.

"When you see application after application that is AI driven, at the core of it is that machine learning has changed how computing will be done," Jensen said during a one-man presentation on stage.

"There are so many things you can't do without AI."

Jensen's keynote came on the eve of the opening of the CES show floor, and on a day that Nvidia shares closed at a new record, giving the Silicon Valley company a market valuation of more than $3.6 trillion.

Nvidia's graphics unit processors (GPUs) for powering AI in datacenters have been snapped up by Google, Microsoft, Meta, OpenAI and others racing to be leaders in the technology.

During a lengthy presentation in Michelob Ultra Arena at Mandalay Bay resort, Huang introduced a GPU for ramping up AI capabilities in personal computers where Nvidia won the loyalty of gamers in the company's early days.

Nvidia touted the new GeForce RTX 50 series for desktop and laptop computers based on Blackwell chip architecture as its most advanced consumer GPUs.

"Blackwell, the engine of AI, has arrived for PC gamers, developers and creatives," Huang said.

PCs enhanced with RTX chips for AI capabilities will be available from an array of manufacturers including Acer, Dell, HP, Lenovo, Razer and Samsung, according to Nvidia.

An AI PC displayed during the presentation was priced at $1,299, built with the $549 RTX chip at the starting point of the new GPU line-up.

Along with rapid rendering of rich gameplay action, Nvidia AI technology will enable the creation of characters that perceive, plan and act like human players, according to Nvidia.

Such autonomous characters are being integrated into games including "PUBG: Battlegrounds", according to Nvidia.

Huang also introduced a family foundation models open to the world for advancing "physical AI" that enables robots to understand and engage in real-world tasks.

Nvidia expanded partnerships and technology for autonomous capabilities in cars as well, with Toyota joining its roster of partners.