Why Google Is Your Best AI Bet

COMPANY DEEP DIVES

Here’s Why Google Will Win

A few months ago, we covered Google and discussed how its internal structure and ways of working were killing its chances of success in the AI race.

Today, the state of AI shows a totally different picture for them. From hardware that goes toe-to-toe with NVIDIA, to models that humiliate some of the most hyped AI incumbents, to sitting on top of the biggest data pile in the history of capitalism.

Heck, Google even has the time to publish AI that decodes dolphin language. Here’s all that you are going to learn today:

Build intuition on AI hardware, understand the key metrics, and also comprehend the uniqueness of the data centers business (notably, answers to questions such as ‘why the cloud?’ and ‘why are accelerated clouds different?’), while also comparing Google’s Ironwood and NVIDIA’s B200. This is crucial to understanding not only Google’s future but also that of NVIDIA/AMD and other Hyperscalers.

Learn what makes Google’s AI model strategy unique, pointing out vital insights (Pareto graphs, unbiased usage rates, etc.) that I assure you will change your perspective on frontier AI.

How Google is correcting its path of self-destruction and it’s finally assembling a robust set of AI products (and even has the time to publish new protocols for agents),

Discuss how they are even hitting it out of the park in M&A.

This piece is aimed at the following cohorts:

Investors who want to understand Google like experts do,

Tech enthusiasts who want to learn about AI hardware and software in great detail without jargon,

and AI practitioners who wish to familiarize themselves with Google’s stack at a deep level.

When PEs hire me to discuss a company’s future, this is what I tell them. Let’s dive in.

This piece turned out very long (+8,000 words). To shorten it, some of the most technical parts have been offloaded to Notion articles you can click if they are of interest to you (you must be a Premium subscriber).

Hardware - Ironwood & the Drums of Liberation

For years, all Hyperscalers (Amazon, Microsoft, Google, Meta, and their Chinese counterparts) found themselves in a very unfamiliar situation. Accustomed to having great power over their suppliers, they all found themselves barking at the same tree: NVIDIA.

NVIDIA found itself with what was essentially a blank check from several cash-rich companies all fighting for every single GPU NVIDIA could deliver. This was—is—a very uncomfortable situation for these companies, who have all independently initiated their own chip ambitions.

But one company saw this need coming from a mile away: from 2018, actually. And that was Google.

And this week, this grand vision of being chip-independent reached its ‘it moment’ as Google announced the newest version of its Tensor Processing Unit (TPU) hardware, v7, codenamed ‘Ironwood.’

And while this is the seventh version of this accelerated chip (more on what that means in a second), based on the paper results we could confidently say that Google has become…

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