Written by: Vivi

When a top AI researcher leaves Google, people say: it's a career choice. But when three high-profile AI talents leave in succession, many start writing Google's "obituary."

Noam Shazeer, Google VP of Engineering and co-lead of Gemini, announced he is leaving Google to join OpenAI. Noam is not an ordinary AI researcher. He is one of the authors of the legendary 2017 paper "Attention Is All You Need." It was this paper that proposed the Transformer architecture, laying the foundation for today's era of large language models.

Image source: Noam Shazeer's LinkedIn profile

John Jumper, VP at Google DeepMind, is leaving Google DeepMind to join Anthropic. Jumper helped create AlphaFold, the protein structure prediction system that has transformed biology and drug discovery. In 2024, he won the Nobel Prize in Chemistry alongside Google DeepMind co-founder and CEO Demis Hassabis.

Image source: The Gairdner Foundation

Daniel De Freitas, a long-time collaborator of Noam Shazeer and co-founder of Character.AI, is also part of this talent migration story. He is not as widely known as Noam, but is very important in the history of conversational AI. He and Noam both initially worked on conversational AI at Google, later leaving in 2021 to found Character.AI, creating one of the earliest viral consumer AI chatbots. In 2024, Google brought them and part of the Character.AI team back in a deal worth up to around $2.7 billion. Now, their names are once again linked to the question of "whether Google can retain the talent that defined the era of conversational AI."

Image source: Business Insider

So, yes, the market's concern is understandable, because these are not ordinary employee departures. These three individuals touch upon the three most important threads of modern AI: Transformer, conversational AI, and AlphaFold.

For a Google that is striving to prove to the world that Gemini can compete with OpenAI and Anthropic, this is undoubtedly painful.

But an "obituary" is not the right framework. Talent drain is a warning sign, not a death certificate.

Interpret it from another angle - Google is being poached not because it has become irrelevant. On the contrary, it is precisely because it remains very important.

OpenAI and Anthropic are young, hungry AI giants on the eve of their IPOs. They are competing for talent, credibility, and market momentum. When they want the world's top AI talent, where do they go?

They go to Google.

Looking at it from another perspective, this in itself illustrates one thing: Google remains one of the deepest AI talent pools in the world.

These departures are certainly not trivial. Losing talents like Noam Shazeer, John Jumper, and Daniel De Freitas is painful. They are not easily replaceable names.

But the real question shouldn't just be: "What exactly is going wrong at Google?"

It should be: "What does Google possess beyond any single genius?"

I prefer to see it as a stress test, and Google might still be one of the few companies capable of weathering this stress test.

Let me elaborate.

1. First, look at the context: This is a classic pre-IPO talent war

First, understand that this isn't just a Google story. It's also a classic Silicon Valley pre-IPO talent war.

OpenAI and Anthropic are no longer the small research labs they were a few years ago; they are already AI giants, entering the eve of capital market scrutiny.

Image source: TechCrunch

They need capital, customers, computing power, enterprise trust, regulatory credibility, and, most importantly, top-tier talent.

At this stage, top AI talent itself becomes part of the valuation narrative.

Noam Shazeer joining OpenAI sends the signal: OpenAI can still attract the people who invented the foundational technology of the LLM era.

John Jumper joining Anthropic sends the signal: Anthropic is not just about Claude; it also wants to be seen as a serious frontier AI and AI for Science institution.

These hires tell investors, employees, customers, and the entire AI community: the best people still believe in our mission.

This is why this talent war looks so dramatic.

But simply interpreting it as "Google must have major problems, so talent is leaving" is too hasty.

Silicon Valley has never operated that way. Talent flows. It's normal for excellent people to leave excellent companies. They might be seeking a new mission, greater equity returns, faster decision-making speed, more autonomy, or simply entering a different stage of life.

This is not necessarily a scandal.

In fact, a key reason Silicon Valley can be an innovation engine is precisely its high talent mobility. Especially in California, where non-compete agreements are strictly limited, people can freely move, start companies, compete, and start anew.

This freedom is certainly uncomfortable for many companies. But for the ecosystem, it is very important.

2. Now look at Google's real advantage: It's not just a model company

Another common misconception is reducing the AI race to model leaderboards.

But Google's advantage is much larger than benchmarks.

Of course, benchmarks are important.

Heavy users will care whether Claude is better at coding, whether GPT has stronger reasoning, whether Gemini performs better on long context, multimodality, or tool use, or which model has a stronger personality, usability, or agentic workflow.

Gemini indeed still needs to prove itself further in certain areas where OpenAI and Anthropic have established strong mindshare.

But the AI market is much larger than benchmarks.

Most ordinary users don't wake up every day thinking, "Which model should I use today?"

What they want is: emails summarized; schedules organized; photos searchable; YouTube videos interpretable; Docs, Gmail, Search, Maps, Android becoming smarter.

This is precisely Google's massive advantage.

OpenAI and Anthropic are excellent model companies. But Google's positioning is completely different: it is a full-stack AI company.

It has infrastructure: TPUs, data centers, Google Cloud, AI Hypercomputer.

It has models: Gemini, Gemma, Veo, Imagen, AlphaFold, and a deep research tradition from Google Brain and DeepMind.

It has products: Search, YouTube, Android, Chrome, Gmail, Workspace, Maps, Photos, Pixel.

It has revenue engines: Search ads, YouTube ads, subscriptions, Cloud, enterprise products.

Most importantly, it has distribution: billions of users are already in its ecosystem.

Most AI startups have to spend heavily to acquire users, while Google already has a massive existing user base. Most AI startups have to build user habits from scratch, while Google is already embedded in many people's daily routines.

Similarly, most AI startups have to persuade enterprises to trust them, while Google is already selling Cloud, Workspace, security, productivity, and infrastructure services to enterprises globally.

This is why the "Google doomsday" narrative doesn't hold water.

Public opinion easily stirs up panic, but looking calmly, you'll find Google has an advantage most companies lack: an invisible AI intelligence layer.

The most successful consumer AI might not make users feel like they are "using AI."

OpenAI and Anthropic need to pull users into their products, while Google can push AI into the products users already use every day.

This is a very deep distribution advantage.

Search is also part of this advantage, although it is often portrayed as Google's biggest weakness.

The bearish logic on Google is obvious: if AI changes how people access information, Google's core search business could be disrupted.

This risk is real.

Google's search advertising business is one of the most profitable in tech history. It has funded AI research, YouTube infrastructure, Cloud expansion, moonshots, and massive capital expenditures.

So Google's moves in this area will be particularly cautious. But Search is not just Google's weakness; it is also Google's super weapon.

Search contributes distribution, user intent data, advertiser relationships, billions of daily user interactions, and a direct entry point to push AI to mainstream users.

If Google can handle this transition well, Search won't simply be replaced by AI, but will become AI-native.

There will certainly be chaotic scenarios in this process - publishers will complain, advertisers will have issues, regulators will watch closely, and users will need time to build trust in AI-generated answers.

But if Google can evolve Search from a list of links into a personalized, multimodal, agentic answer engine, it will remain one of the most important entry points on the internet.

The question now is: Can Google change itself before others change Search?

Google has another severely underestimated advantage: Google can win even when its competitors succeed.

Anthropic is not just Google's competitor. It is also its strategic partner.

Let's look at the data:

Google's parent company Alphabet has committed up to $40 billion to Anthropic, including a $10 billion cash investment at a reported valuation of $350 billion, with another $30 billion tied to performance targets.

Meanwhile, Anthropic has reportedly committed to spending $200 billion on Google Cloud over five years.

This is not just a financial investment. Anthropic also announced plans to use up to 1 million Google TPUs, worth tens of billions of dollars, and expects to bring over 1GW of computing capacity.

This means one of Google's most important AI rivals could also become one of Google Cloud's most important AI infrastructure customers.

OpenAI has reportedly also turned to Google Cloud for additional computing power.

So Google isn't just participating in the AI model race — it's also becoming part of the underlying infrastructure for other frontier AI companies.

In the AI gold rush, Google isn't just trying to dig for gold itself.

It's also selling shovels, roads, electricity, and cloud infrastructure.

That's an extremely strong position.

The model race is incredibly expensive. Training and serving frontier models requires enormous computing power. Even the most successful AI companies need infrastructure partners.

Google has spent years building its own custom chips, cloud capacity, and AI infrastructure. Today, even its competitors may have to rely on parts of its technology stack. That's its foundational strength.

Finally, it's worth mentioning that Google's AI ambitions go beyond chatbots — they also include AI for Science.

The Nobel Prize-winning AlphaFold is the best example. AlphaFold transformed scientists' understanding of protein structure prediction, accelerated biological research, and proved that AI isn't just for generating text — it can also solve truly difficult scientific problems.

This is crucial for the long-term AI race, because ultimately the biggest AI winners may not just be the companies with the strongest consumer chatbots; they may also be the companies that can apply AI to science, medicine, climate, education, robotics, and deep-tech infrastructure.

Google DeepMind has always had this larger ambition.

Indeed, John Jumper's departure may be a "lingering regret" for Google, because he represented one of Google's most important victories in AI for Science.

But AlphaFold wasn't the product of any single genius working alone. It came from a team, and from a research culture: a determination to invest long-term in the world's hardest problems, even before the market was fully paying attention.

That kind of culture is rare, and Google still has it.

3. The Real Innovator's Dilemma

So, does Google face the innovator's dilemma?

Of course — no company is immune.

Google's core Search business is both its greatest asset and its biggest constraint.

A startup can charge forward with pure hunger. Google, on the other hand, has to protect a global business, a brand, regulatory risks, advertisers, publishers, enterprise clients, and billions of users.

This slows down decision-making; makes product launches more cautious; and makes internal coordination more complex — that's the part many people criticize.

Google has certainly made mistakes — for example, Bard's debut didn't go well.

Gemini's own growth has also gone through quite a few public setbacks.

But the important question isn't whether Google has weaknesses — it's: Is Google adapting and adjusting?

I believe it is.

The Character.AI story illustrates this decisiveness well.

Noam Shazeer and Daniel De Freitas left Google in 2021 to found Character.AI, which grew quickly. Later, Google made a bold, massive deal to bring them and part of the Character.AI team back to Google.

That's the core tension in Google's AI story: Google was too cautious early on and indeed seemed slow-footed compared to startups; but later Google reorganized, refocused, and began pushing Gemini across its entire ecosystem, turning it into an intelligence layer spanning Search, Workspace, Android, Cloud, and consumer products.

That doesn't mean Google can act like a 200-person startup. That's unrealistic.

But when the organization is aligned, it can act like a full-stack AI empire.

This distinction is very important — the innovator's dilemma is real, but Google isn't ignoring it.

From revolutionizing Search to integrating Gemini and a series of other moves, what we're seeing is a tech giant's effort during a period of transformation.

4. Summary: This Is a Stress Test, Not an Obituary

The departure of top talent is more like a stress test for Google than an obituary.

The company is facing one of the most difficult transformations in its history, but it's also one of the few with enough resources, technology stack, and distribution power to navigate this transformation.

In the AI era, the flashiest model may win a news cycle; the most aggressive startup may grab headlines in the talent war.

But the best integrated system may win the next decade.

That's why I remain confident in Google — not because Google is perfect, but because Google is one of the few companies that can compete at every layer of AI's future.

The AI race is far from over, and Google is playing a long game.