The Silicon Valley ‘AI factory’ at the heart of the tech race

Google’s ultra-private CEO Sundar Pichai is exhibiting me round Googleplex, its California headquarters. A walkway runs alongside the size of it, passing by an enormous dinosaur skeleton, a seaside volleyball pitch and dozens of Googlers lunching underneath the hazy November solar.

But it surely’s a laboratory, hidden away in the back of the campus behind some timber, that he’s most excited for me to see.

That is the place the invention that Google believes is its secret weapon is being developed.

Often called a Tensor Processing Unit (or TPU), it seems like an unassuming little chip however, says Mr Pichai, it can in the future energy each AI question that goes by means of Google. This makes it probably probably the most essential objects on this planet economic system proper now.

“AI is probably the most profound expertise humanity [has ever worked] on,” he insists. “It has potential for extraordinary advantages – we should work by means of societal disruptions.”

However the complicated query lingering over the AI hype is whether or not it’s a bubble liable to bursting – as, in that case, it could be a spectacular burst akin to the dotcom crash initially of the century, with penalties for us all.

The Financial institution of England has already warned of a “sudden correction” in world monetary markets, saying “market valuations seem stretched” for tech AI companies. In the meantime. OpenAI boss Sam Altman has speculated that “there are lots of elements of AI that I believe are form of bubbly proper now”.

Requested whether or not Google would be immune from a possible bubble burst, Mr Pichai stated it might climate that potential storm – however for all his starry-eyed pleasure across the potentialities of AI, he additionally issued a warning: “I believe no firm goes to be immune, together with us.”

So why, then, is Google investing greater than $90bn a yr within the AI build-out, a three-fold improve in simply 4 years, on the very second these solutions are being mentioned?

The AI surge – of which Google is only one half – is, in money phrases, the most important market increase the world has seen.

Its numbers are extraordinary – there may be $15 trillion of market worth at Google and 4 different tech giants whose headquarters are all inside a brief drive of each other.

Chipmaker turned AI methods pioneer Nvidia in Santa Clara is now value greater than $5 trillion. A ten-minute drive south, in Cupertino, is Apple HQ, hovering round $4 trillion; whereas quarter-hour west is $1.9 trillion Meta (beforehand Fb). And within the centre of San Francisco, OpenAI was not too long ago valued at $500bn.

The purely monetary penalties of this development are important sufficient.

The worth of the shares in these corporations (and some others outdoors Silicon Valley, akin to Microsoft in Seattle) have helped cushion the US economic system from the affect of commerce wars, and stored retirement plans and investments buoyant – and never simply within the US.

But it comes with a giant danger. That’s, the unbelievable dependence of US inventory market progress on the efficiency of a handful of tech giants. The Magnificent 7 – Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla – collectively comprise one third of the valuation of America’s total S&P 500.

And that market worth is now extra extremely concentrated in a couple of companies than it was through the dotcom bubble in 1999, in keeping with the IMF.

Mr Pichai factors out that each decade or so come these “inflection factors”: the non-public laptop, then the web within the late Nineteen Nineties, adopted by cellular and cloud. “Now it is clearly the period of Synthetic Intelligence.”

However as for the massive query – is it a bubble?

Mr Pichai argues there are two methods of excited about it. First, there may be “palpably thrilling” progress of providers that folks and firms are utilizing.

However he concedes: “It is also true once we undergo these funding cycles, there are moments we overshoot collectively as an trade…

“So I believe it is each rational and there are components of irrationality by means of a second like this.”

Now, a distinction is rising within the markets between these companies that depend on typically borrowed cash and difficult offers to entry the chips that energy their AI, and the most important tech corporations, akin to Google, Microsoft and Amazon, which might fund funding in chips and knowledge from their very own pockets.

Which brings us to Google’s personal silicon chips, or their prized TPUs.

The lab, the place they’re examined, is the scale of a five-a-side soccer pitch with a mesh of multi-coloured wires and deep blue blinking lights. Indicators throughout learn: “restricted”.

What’s placing is the sheer noise – that is right down to the cooling methods, that are wanted to assist management the temperature of the chips, which might get extremely scorching when crunching trillions of calculations.

The TPUs are designed to assist energy AI machines. And so they work in another way from different sorts of chips.

The CPU (central processing unit) is the first element of a pc – primarily its mind – that performs a lot of the processing and management features, whereas GPUs (graphics processing items) carry out extra specialised processing, executing many parallel duties directly – this could embrace AI.

Nonetheless Asics (application-specific built-in circuits), are chips custom-built for a particular objective, for instance, a particular AI algorithm. And the TPU is a specialist Google-designed sort of Asic.

A core side of the AI increase has been the mad sprint to amass a lot of top-performing chips and put them into knowledge centres (or the bodily amenities that retailer, course of and run giant quantities of information and software program).

Nvidia’s boss Jensen Huang as soon as coined the time period “AI factories” to explain the large knowledge centres filled with pods and racks of tremendous chips, linked to very large power and cooling methods.

(Tech bosses akin to Mark Zuckerberg have referred to some being the scale of Manhattan. The Google TPU lab is considerably extra modest, testing out the expertise for deployment elsewhere.)

Tales abound of tech bros begging chip makers for a whole bunch of hundreds of those extremely engineered items of silicon. Take the current dinner at Nobu in Palo Alto, the place Elon Musk and Larry Ellison, the founder and head of Oracle, tried to woo Nvidia’s Jensen Huang, to promote them extra of them.

As Mr Ellison put it: “I’d describe the dinner as me and Elon begging Jensen for GPUs. Please take our cash – no, no take extra. You are not taking sufficient. We want you to take extra, please!”

It’s exactly the race to entry the facility of as many as attainable of those excessive efficiency chips, and to scale them up into huge knowledge centres, that’s driving an AI increase – and there is a notion that the one method to win is to maintain spending.

The terrace of the Rosewood Sand Hill resort, a sprawling 16-acre property close to the Santa Cruz mountains that serves crab rolls and $35 signature vodka martinis, is the place the massive Silicon Valley deal-making will get performed. It is near Stanford College and Meta’s HQ, in addition to the headquarters of main enterprise capital companies.

There are whispered rumours about who might be subsequent to announce customised AI chips – Asics – to compete with Google and Nvidia.

Simply earlier than I visited, one thing of a storm was brewing concerning the funding plans of OpenAI, which Elon Musk co-founded.

The agency, which began as a not-for-profit however has since established a business construction, has been the main focus of an internet of cross-investments involving shopping for up chips and different laptop {hardware} wanted for AI processing.

Few within the trade doubt OpenAI’s phenomenal consumer progress – particularly the recognition of its chatbot, ChatGPT. It has ambitions to design its personal {custom} AI chips, however some have speculated about whether or not it’d want authorities help to attain this.

In a podcast episode that aired final month, an OpenAI investor questioned how the corporate’s spending commitments tallied with its revenues, to which co-founder Sam Altman shot again, difficult the income figures quoted, and including: “If you wish to promote your shares, I am going to discover you a purchaser. Sufficient.”

He has since shared a prolonged publish on X, explaining, amongst different issues, that OpenAI is taking a look at commitments of about $1.4 trillion over the following eight years and why he believes now could be the time to put money into scaling up their expertise.

“I don’t suppose the federal government needs to be writing insurance coverage insurance policies for AI corporations,” he stated.

However he additionally stated: “What we do suppose would possibly make sense is governments constructing (and proudly owning) their very own AI infrastructure.”

Elsewhere, there have been notable very current falls in share costs of AI infrastructure corporations – Coreweave, a start-up that provides OpenAI, noticed its shares lose 26% of their worth earlier this month.

Plus, there have been some reactions in markets for perceived credit score danger amongst different companies. And whereas most of those tech share costs have typically climbed increased over the course of 2025, there was a gentle dip extra typically previously few days.

None of this has dampened the joy over AI’s potential inside the trade. Google’s client AI mannequin, Gemini 3.0, launched to nice fanfare earlier this week — it will pitch Google in a direct battle with OpenAI and its still-dominant ChatGPT for the market share.

What we do not but know is whether or not it marks an finish to the times of chatbots going rogue and recommending glue as a pizza ingredient. So, is the tip results of all this implausible funding is that data is much less dependable, I requested Mr Pichai.

“I believe when you solely assemble methods standalone and also you solely depend on that, [that] could be true,” he advised me. “Which is why I believe we’ve got to make the data ecosystem needs to be a lot richer than simply having AI expertise being the only product in it.”

However I put it to him that fact issues. His response: “fact issues”.

Neither is the opposite large query going through tech right now dampening the passion round advancing AI’s potential. That’s: how on Earth to energy it?

By 2030, knowledge centres around the globe will use about as a lot electrical energy as India did in 2023, in keeping with the IMF. But that is additionally an age the place power provide is underneath strain by governments committing to local weather change targets.

I put this to Google’s Mr Pichai, asking whether it is coherent to have ambitions to generate 95% of electrical energy from low-carbon sources by 2030 – because the UK authorities does – and in addition be an AI superpower?

“I believe it is attainable. However I believe for each authorities, together with the UK, it is essential to determine tips on how to scale up infrastructure, together with power infrastructure.

“You do not wish to constrain an economic system primarily based on power,” he provides. “I believe that can have penalties.”

Years in the past, as a fledgling reporter I lower my enamel within the 2000 dotcom bubble. It adopted a well-known speech by Federal Reserve Governor Alan Greenspan about “irrational exuberance”.

In that point I interviewed Steve Jobs twice, and some years later questioned Mr Pichai’s predecessor Larry Web page, and commentated stay on the collapse of WorldOfFruit.com.

By means of all of it, one lesson turned clear: that even within the worst-case eventualities and the hardest of crashes, disaster is not assured for all.

Take Amazon – its share value slumped to $6 and its market capitalisation fell to $4bn throughout that crash, but some 25 years on Jeff Bezos and his firm are very a lot going sturdy. At this time Amazon is value $2.4 trillion.

The identical would, inevitably, be true of corporations shaken by a possible AI bubble burst.

Plus there may be one other looming issue which will properly clarify why so many in Silicon Valley – and past – are blind to, or maybe selecting to not, acknowledge this danger, and pushing on regardless.

That’s, the attraction of the glittering prize on the finish: attaining synthetic common intelligence (AGI).

That is the purpose at which machines match human intelligence, one thing many imagine is inside attain. Or past that, reaching synthetic super-intelligence (ASI), the purpose at which machines surpass our intelligence.

However I used to be additionally advised one thing else that was thought-provoking by a Silicon Valley determine – that it does not matter whether or not there actually is a bubble or if it bursts. Step again and what’s going on within the larger image is a world battle for AI supremacy, with the US in opposition to China taking centre stage.

And whereas Beijing funds these developments centrally, within the US it’s a messy however productive free market free for all, which suggests trial and error on an epic scale.

For now, the US has superiority in silicon over China – corporations like Nvidia with their GPUs and Google with their TPUs can afford to speed up into the storm.

Others will certainly fail, and spectacularly so, affecting markets, client sentiment and the world economic system. The bodily footprint left behind, nonetheless, containing sheer computing firepower for the deployment of mass AI applied sciences, will inevitably form our economic system and will properly additionally form how we work and study – and who dominates the world for the remainder of the twenty first Century.

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