Defections from Google DeepMind prompt questions about Alphabet’s efforts to stay at the forefront of AI
With Google's AI models losing leaderboard places and its pace of model releases lagging, some are questioning if the internet giant can stay at AI's cutting edge.
Defections from Google DeepMind prompt questions about Alphabet’s efforts to stay at the forefront of AI
Overview
Welcome to Eye on AI. In today’s issue:
- Google DeepMind loses top AI talent, raising questions about its status in the AI race
- Intelligence chiefs warn about imminent AI-driven cyber risks
- OpenAI expands program for cyber defenders to use AI
- Lab makes RSI progress
That giant sucking sound you hear? That’s the woosh of talent streaming out of Google DeepMind and flowing to OpenAI and Anthropic. There was a time when I can remember DeepMind bragging about how no one ever left the storied AI lab. That’s certainly not the case anymore.
In recent months, a stream of well-known researchers have departed. Some, such as David Silver, one of DeepMind’s earliest employees and one of the top reinforcement learning experts in the world, have decided to launch their own startups (Silver’s is called Ineffable Intelligence). But others have joined DeepMind’s chief rivals.
This past week, two Google DeepMind stars jumped ship in just 48 hours, both departures shocking in their own way for what they may say about Google DeepMind’s prospects in the AI race. That message was not lost on investors. News of their leaving sent Google’s shares tumbling more than 5% on Monday.
A chatbot pioneer and a Nobel laureate exit
First, on Thursday, Noam Shazeer announced he was leaving to go to OpenAI. Shazeer is the famed AI researcher who helped build Google’s earliest LLM-based chatbot system, LaMDA, in 2021, and then left in frustration when the internet giant dragged its feet in commercializing it. Before he left the first time, Shazeer is thought to have authored an anonymous memo, which later leaked, that criticized Google for having become too bureaucratic, slow-moving, and risk-adverse to succeed in AI against nimbler rivals, a critique that was seemingly validated when OpenAI launched the category defining ChatGPT in November 2022 and jumped out in front, at least in the public imagination, as the leading AI lab. Shazeer and Daniel de Freitas, another Google researcher who had helped build LaMDA, cofounded the viral chatbot startup Character.ai. But then they were lured back to Google in 2024 in a deal that saw Google license Character’s technology for a reported $2.7 billion payment. Now Shazeer is leaving again.
Just days after the Shazeer news, Google DeepMind researcher John Jumper announced he too was leaving—in this case, to join Anthropic. Jumper shared the 2024 Nobel Prize in chemistry with Google DeepMind CEO Demis Hassabis for his work creating AlphaFold, the AI system that could predict the shape of proteins from their DNA sequences, solving a 50-year grand challenge in biochemistry. After the Nobel win, Jumper had continued to work at DeepMind on AI models that could predict other properties of proteins—such as how they would bind to one another and how the small molecules often used for pharmaceuticals would likely bind to them—and he was also intrigued by the idea of using large language models, such as those that powered Google’s Gemini AI models, as tools for science.
Details
While Google DeepMind continues to maintain a large team of AI researchers dedicated to applying AI to fundamental science challenges and has recently created a Gemini-powered system that can act as an “AI scientist” assisting researchers across different scientific domains, there is a sense that science is now less of a priority for Google DeepMind than it was in the years just prior to the launch of ChatGPT. (Isomorphic Labs, the AI drug discovery company that was spun out of DeepMind in 2021 and is also led by DeepMind CEO Demis Hassabis, is of course heavily focused on science—but with the aim of applying the research to commercial purposes rather than “blue-sky” scientific research). Meanwhile, Dario Amodei, Anthropic’s CEO, recently told Bloomberg’s Emily Chang that Anthropic intends to do more around biology; Jumper’s hiring is no doubt part of that plan.
Neither Shazeer or Jumper have said publicly why they’re leaving. The simplest explanation, of course, might simply be money, although there is little doubt that both Shazeer and Jumper were already extremely well-compensated. Shazeer is thought to have made hundreds of millions of dollars from the Character.ai licensing deal that brought him back to Google. (Presumably any required earn out period has ended.) And both Shazeer and Jumper were likely among the class of Google DeepMind researchers that have been awarded bushels of a special class of Google stock options that vest on an accelerated schedule, a tactic Google has had to adopt to prevent top talent from being lured away by gargantuan pay packages at places like Meta’s Superintelligence Lab. But, still, there’s a difference between being merely rich and the kind of generational wealth that the two might realize when Anthropic and OpenAI IPO, something both companies are expected to do in the coming months.
That said, money seems an unlikely explanation. I don’t know Shazeer, but as I said, he is likely already a multi-multi-millionaire. As for Jumper, I’ve interviewed him numerous times over the past four years, for both Fortune stories and for my book, Mastering AI. He doesn’t strike me as the kind of person who is primarily motivated by money and I don’t think he’d leave Google DeepMind unless he thought the scientific opportunity at Anthropic was actually better—which is much worse news for Google DeepMind.
Is Google DeepMind dropping out of the lead AI pack?
Industry watchers are wondering aloud whether the AI lab is slipping back from the lead pack in the AI race. Its top AI models, Gemini 3.5 Flash and Gemini 3.1 Pro, are often ranked outside the top five places on various AI benchmark leaderboards, having fallen behind models from Anthropic and OpenAI, as well as Chinese labs such as Zhipu AI and MiniMax. Meanwhile, its pace of model development seems to be lagging. At Google I/O in May, the company announced it was readying Gemini 3.5 Pro for wide release, targeting a June general availability date. But that means Gemini 3.5 Pro will be coming out about four months after Google DeepMind’s last frontier wide release, which was Gemini 3.1 Pro in February. By contrast, Anthropic has released not only two significant Claude Opus updates in that same time period, it also debuted a whole new class of AI models, Mythos, that is world-leading in its ability to complete long range tasks autonomously, particularly in coding and cyber domains.
Talking to both current and former GDM employees as well as others who know the lab well, there’s a sense Shazeer’s previous criticisms of Google remain valid. The place is burdened by its size, with a culture that current and former employees routinely describe as bureaucratic, sometimes bordering on sclerotic, and highly risk-adverse. Alphabet’s defenders say Google, with billions of users, can’t afford to take the same kinds of chances that OpenAI and Anthropic can. Unlike those money-losing, venture-funded startups, Alphabet actually has profits to defend, and it has a fiduciary duty to public market investors not to make risky bets that might needlessly jeopardize their returns.
There may even be some within Google’s upper echelons who believe the company doesn’t need to be particularly bold. The emergency created by ChatGPT’s launch in November 2022, kicked the company into a different gear. But, having seen off what at first seemed like a potentially existential threat to its core search business from ChatGPT, the company may have downshifted back into standard operating mode. Google has shown that as long as it can more or less match the technological advances of other players, its massive distribution advantage will probably carry it through. Recently, writing about Microsoft, I argued that company wasn’t necessarily playing to win the AI race. It was playing not to lose. Alphabet can also afford that kind of strategy. But, of course, that’s not the sort of culture that is likely to attract and retain the world’s leading AI researchers.
It’s also not the way Hassabis ever wants to play. The former child chess prodigy is nothing if not relentlessly competitive. He will likely be smarting from the loss of Shazeer and Jumper. And he will no doubt be doing his utmost to try to make sure Google DeepMind can get back to the front. How he will do that, though, remains to be seen.
With that, here’s more AI news.
Jeremy Kahn
[email protected]
@jeremyakahn
This story was originally featured on Fortune.com
Source
Originally published at fortune.com.
