SAN FRANCISCO, USA, 11 August. - (ANA) - Depending on where you sit, Google either has the most enviable position in artificial intelligence or is bleeding top talent to leading AI labs and other startups on the frontline of innovation.

 

It’s a contrast that’s been on full display over the past two weeks, beginning with the company reporting 82% revenue growth in its cloud division, followed by a shakeup on Wednesday in Google’s AI organization, as chief scientist Jeff Dean announced his departure after 27 years.

 

For Google, home to the famous 2017 transformer paper that paved the way for the generative AI boom, the recent events underscore a central challenge facing the $4 trillion company: where to invest. Building frontier models requires huge upfront costs for compute and research with no guarantee of future returns, while the cloud business is proving to be highly efficient and is growing much faster than rival offerings at Amazon and Microsoft.

 

Alphabet CEO Sundar Pichai said on last month’s earnings call that 90% of Fortune 100 companies are using Gemini Enterprise, underscoring the company’s ability to sell AI services to cloud customers.

 

Tomasz Tunguz, founder of Theory ventures, said it’s becoming clear that top-of-the-line models aren’t required when it comes to meeting most enterprise demand.

 

“I think we are at that place with AI, particularly for a lot of white-collar work, where many of the models that are reasonable are good enough,” Tunguz said. “The next evolution of models are likely to be helpful in domains where you have really fancy computers.”

 

Google’s full-stack approach to AI is a big reason the stock is up 16% this year after jumping 65% in 2025, when it outpaced all of its megacap peers.

 

It’s been a bumpier road of late. Alphabet shares fell after the latest earnings report due to concerns about capital expenditures, and dipped further on Wednesday following the announcement that Dean is departing and Demis Hassabis is stepping down as CEO of Google DeepMind to become chairman of the unit.

 

While the tone on Wall Street has been generally favorable, not everyone is celebrating inside of Google.

 

Some researchers have grown frustrated over access to the computing capacity they need to pursue ambitious projects while watching Google Cloud sell TPUs to outside customers, including Anthropic, according to people familiar with the matter who asked not to be named due to confidentiality. Tensor processing units, or TPUs, are the the company’s homegrown AI chips that compete with Nvidia’s graphics processing units.

 

Google’s bureaucracy is a common source of frustration, with layers of approval required to move research into products. That can make emerging companies like OpenAI, Anthropic or even younger startups more appealing, especially for AI researchers and developers who prefer lab work to balance sheets.

 

Dean is leaving along with Google stars Sanjay Ghemawat, Oriol Vinyals, and Quoc Le to start Discovery Loop. On X, Dean said the startup, backed by Google, will be a public benefit corporation “whose mission is to automate machine learning, science, and engineering to accelerate discoveries and progress.”

 

Their exit follows the departures of other prominent researchers, including Noam Shazeer, one of the authors of the landmark 2017 paper “Attention Is All You Need,” which provided the foundation for generative AI. All eight authors have now left Google. Shazeer left for OpenAI in June, less than two years after Google paid nearly $3 billion to bring him back through an acquihire. His exit came shortly before Nobel laureate John Jumper left DeepMind for Anthropic.

 

At Google, Dean was one of the very few high-profile voices willing to criticize the Trump administration, and earlier this year he was vocal in opposing the Pentagon’s decision to designate Anthropic as a supply-chain risk, warning that the move could damage the broader U.S. AI industry.

 

More importantly, from a technical perspective, he helped build the computing infrastructure and neural network systems that established the company as an early leader in modern AI. 

 

One of the biggest points of friction inside Google is compute. - (ANA) -

 

AB/ANA/11 August 2026 - - -