Silicon Valley is coming to grips this week with the realization that creating an advanced artificial intelligence model may no longer be as specialized a task as was once believed.

The wake-up call came in the form of DeepSeek, a year-old Chinese start-up whose free, open-source AI model, R1, is more or less on par with advanced models from American tech giants. And it was built for a fraction of the cost, apparently using less advanced chips and demanding far less data centre power to run.

Until now, the widely accepted wisdom in the US tech world was that American tech giants could stay ahead by spending billions of dollars, amassing advanced chips, and building out huge data centres (despite the environmental cost). Essentially, because they’re among the richest companies in the world, they believed they could throw more resources at the problem than anyone else and come out on top.

Now, all of that has been called into question, and tech giants are facing tough scrutiny from Wall Street.

The name of the AI game may no longer be winning with the most expensive, ever-more-powerful models.

“The paradigm is shifting,” said Zack Kass, an AI consultant and former OpenAI go-to-market lead.

“It’s so hard to own a scientific breakthrough,” Kass said, such as an AI model advancement, and prevent competitors from catching up. Instead, tech companies may now find themselves competing to lower costs and build more helpful applications for consumers and corporate customers—while also minimizing power and natural resource consumption.

Silicon Valley Reacts

At least one American tech leader has already promised to respond to DeepSeek by speeding up the release of more powerful models.

OpenAI CEO Sam Altman called DeepSeek’s R1 model “impressive” in an X post-Monday, adding that “we will pull up some releases” of new models in response. OpenAI Chief Product Officer Kevin Weil also said the company’s upcoming o3 model, set to launch in the coming weeks, would “be another major step up.”

“It’s a super competitive industry, right? And this shows that it’s competitive globally, not just within the US,” Weil said on a call with reporters about OpenAI’s new ChatGPT offering for government agencies. “We’re committed to moving quickly here. We want to stay ahead.”

However, analysts expect big tech companies to scale back their data centre spending plans and potentially rethink how much they charge consumers. DeepSeek has proven it’s possible to provide the technology at a lesser cost. However, some industry experts have raised eyebrows at the startup’s claims of spending just under $6 million to build its model.

Bloomberg reported that OpenAI’s largest investor, Microsoft, is investigating whether DeepSeek trained its model using stolen OpenAI data. Even if the company achieved its efficiency breakthrough with some malfeasance, DeepSeek’s achievements have lit a fire under Silicon Valley’s AI industry.

“All those other frontier model labs—OpenAI, Anthropic, Google—are going to build far more efficient models based on what they’re learning from DeepSeek,” said Gil Luria, head of technology research at investment firm D.A. Davidson. “And you’ll be able to use those at a fraction of the price that you can now because it’s going to be a fraction of the cost to run those models.”

The industry was almost certainly going to eventually shift its focus to efficiency—working to add AI capabilities using a set amount of computing power rather than continuously adding more servers to boost performance. Only so many computers can be built, and only so much electricity is available. An AI tool can only get so proficient at writing emails or planning trips before further improvements become marginally beneficial.

But DeepSeek appears to have accelerated that timeline. And in Silicon Valley, unwinding spending on data centres could be tricky.

Just last week, OpenAI, Oracle, and SoftBank visited the White House to announce the creation of a new company and a $500 million investment in US AI infrastructure. Microsoft CEO Sundar Pichai affirmed that he was “good for” his company’s planned $80 billion investment in AI development and infrastructure this year. Meanwhile, Meta CEO Mark Zuckerberg said his company’s AI spending could reach as much as $65 billion this year.

“That crazy AI data centre build-out we’ve discussed for the last couple of years? They don’t need to do that anymore. They can build a lot less because they can provide many more services at a much lower price,” Luria said. He added that investors will likely expect to hear about those plans in the American tech companies’ earnings calls over the next two weeks.

Of course, suppose tech giants cut data centre costs for training AI models and charge customers less. In that case, their tools will get used more, increasing inference strain (or the number of user queries) on the data centres, Bloomberg Intelligence analysts wrote Tuesday. So, just how dramatic that pullback on data centre spending might be remains to be seen.

DeepSeek’s Upside

Some tech leaders say they view DeepSeek as validation rather than a threat.

Proponents of open-source AI—where the model’s underlying architecture is publicly available rather than locked behind paywalls—say the Chinese model proves that American companies should share their innovations rather than gatekeeping them. That way, the US field could advance quickly and remain the global technology standard.

“The United States already has the best-closed models in the world. To remain competitive, we must also support the development of a vibrant open-source ecosystem,” former Google CEO Eric Schmidt wrote in a Washington Post op-ed Tuesday.

Meta, which has championed open-source AI with its Llama model, also stated that such models “are driving a significant shift in the industry, and that’s going to bring the benefits of AI to everyone faster.”

And even if DeepSeek forces a short-term rethinking of Silicon Valley’s AI business model, people who believe in the technology’s transformative potential should be glad for the progress, Kass said.

“We are freaked out fairly, I suppose, because we thought we had global AI supremacy when, in fact, we should be celebrating,” Kass said. “This is evidence that the AI revolution will democratize technology and be fairly distributed.”