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DeepSeek’s $6 million AI model just blew a $1 trillion hole in the market. Here’s the only explainer you’ll need on this “Sputnik moment”

A fast-moving story is shaking up the AI industry in many different ways.

Over the weekend, the DeepSeek AI story really exploded. There are a lot of different aspects to this story that strike right at the heart of the moment of this AI frenzy from the biggest tech companies in the world. Let’s break this complicated but fascinating story down.

To catch you up, Chinese startup DeepSeek released a group of new “DeepSeek R1” AI models, which have burst onto the scene and caused the entire AI industry (and the investors giving them billions to spend freely) to freak out in different ways. These models are free, mostly open-source, and appear to be beating the latest state-of-the-art models from OpenAI and Meta.

Faster, cheaper, better

What makes these models so noteworthy? Unlike OpenAI and Anthropic’s AI models, they are free for anyone to download, refine, and use for any purpose. Meta did a similar thing with its Llama 3 AI model, making it free for anyone to download, modify, and use. DeepSeek’s latest models were actually based off Llama. But there are lots of free models you can use today that are all pretty good.

The big thing that makes DeepSeek’s latest R1 models special is that they use multistep “reasoning,” just like OpenAI’s o1 models, which up until last week were considered best in class. The reasoning process is a bit slower, but it leads to better responses and reveals a “chain of thought” that shows the steps it takes.

DeepSeek is offering up models with the same secret sauce that OpenAI is charging a significant amount for. And OpenAI offers its models only on its own hosted platform, meaning companies can’t just download and host their own AI servers and control the data that flows to the model. With DeepSeek, you can host this on your own hardware and control your own stack, which obviously appeals to a lot of industries with sensitive data.

DeepSeek does offer hosted access to its models, too, but at a fraction of the cost of OpenAI. For example, OpenAI charges $15 per 1 million input “tokens” (pieces of text that get entered into a chat, which could be a word or letter in a sentence). But DeepSeek’s hosted model charges just $0.14 for 1 million input tokens. That’s a jaw-dropping difference if you’re running any kind of volume of AI queries.

Another crazy part of this story — and the one that’s likely moving the market today — is how this Chinese startup built this model. DeepSeek’s researchers said it cost only $5.6 million to train their foundational DeepSeek-V3 model, using just 2,048 Nvidia H800 GPUs (which were apparently acquired before the US slapped export restrictions on them).

For comparison, Meta has been hoarding more than 600,000 of the more powerful Nvidia H100 GPUs, and plans on ending the year with more than 1.3 million GPUs. DeepSeek’s V3 model was trained using 2.78 million GPU hours (a sum of the computing time required for training) while Meta’s Llama 3 took 30.8 million GPU hours.

And this faster, cheaper approach didn’t just result in a model that matched the leaders’ models; in some cases, it beat them. DeepSeek’s R1 models are beating OpenAI o1 in some math and coding benchmarks.

Did we bet on the wrong horse?

So a better, faster, cheaper Chinese AI model just dropped, and it could upend the industry’s big plans for the next generation of AI models. The biggest tech companies (Meta, Microsoft, Amazon, and Google) have been bracing their investors for years of massive capital expenditures because of the consensus that more GPUs and more data leads to exponential leaps in AI model capabilities. Recently, there are signs that this “AI scaling law” may have reached a plateau, and Nvidia’s place at the top of the AI food chain may be in peril.

A lot of the success DeepSeek had was a result of its using other AI models to generate “synthetic data” to train its models, rather than hunting for new stores of human-written texts.

If that bet on zillions of GPUs, Manhattan-size data centers, and hundreds of billions in AI infrastructure investment is wrong, what are we doing here? Cue the massive freak-out in the market today.

Top of the App Store

As if this story couldn’t get any crazier, this weekend the DeepSeek chatbot app soared to the top of the iOS App Store “Free Apps” list. Observers are calling this a “Sputnik moment” in the global race for AI dominance, but there are a lot of things we don’t know.

One thing we do know is that for all of Washington’s freak-out over TikTok leaking Americans’ personal data to China, this AI chatbot is absolutely sending your data to China, and is even subject to Chinese censorship policies. So don’t go asking DeepSeek about Tiananmen Square, the plight of Uyghurs in China, or Taiwan’s pro-democracy movement, and who knows what else.

Fallout

This weekend, The Information reported that inside Meta they’re indeed freaking out, setting up war rooms and rethinking AI strategy.

The new Trump administration is not going to like this, either, as it’s highlighted a vision of American domination of AI and plans to expedite approvals for new power plants and infrastructure to build massive data centers.

It’s unclear how the admin and lawmakers will react to these developments, but events are moving much faster than any branch of government can.

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Google testing Gemini app for Mac, aims to compete with Claude Cowork and Codex

Bloomberg reports that Google is testing a new version of its Gemini AI app that runs on Apple’s Mac computers.

Currently both OpenAI’s Codex and Anthropic’s Claude have Mac apps, which allow for deeper AI automation with files on the computer.

Google is testing a feature called Desktop Intelligence, which grants Gemini access to the items on the user’s screen, according to the report. The app is currently in beta testing.

Google is testing a feature called Desktop Intelligence, which grants Gemini access to the items on the user’s screen, according to the report. The app is currently in beta testing.

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Bezos seeks $100 billion for AI-enhanced manufacturing fund, WSJ reports

Amazon founder Jeff Bezos is seeking to raise a $100 billion fund that would purchase manufacturing companies and use AI to automate their work processes, according to a new report from The Wall Street Journal.

The fund would use technology from Project Prometheus, where Bezos was recently named co-CEO. The startup aims to apply the latest generative-AI breakthroughs to reinvent industrial manufacturing.

The $100 billion fund would be used to buy existing manufacturing businesses to transform, per the report.

Bezos has reportedly met with the heads of sovereign wealth funds in the Middle East and recently traveled to Singapore as part of the fundraising effort.

The $100 billion fund would be used to buy existing manufacturing businesses to transform, per the report.

Bezos has reportedly met with the heads of sovereign wealth funds in the Middle East and recently traveled to Singapore as part of the fundraising effort.

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OpenAI acquires Astral, adding talent to Codex team

OpenAI has acquired open-source Python tool developer Astral, bringing aboard additional coding talent for its Codex team.

The company said the acquisition will help Codex “expand beyond coding” by helping address a wider range of development tasks, such as planning, testing, and code maintenance.

OpenAI said Codex has seen “3x user growth and 5x usage increase” since the start of 2026, and has over 2 million weekly active users.

Software development is emerging as one of the key battlegrounds where OpenAI is competing for market share with Anthropic, which has been enjoying success with its Claude Code product.

OpenAI said it will continue to support Astral’s open-source software projects.

OpenAI said Codex has seen “3x user growth and 5x usage increase” since the start of 2026, and has over 2 million weekly active users.

Software development is emerging as one of the key battlegrounds where OpenAI is competing for market share with Anthropic, which has been enjoying success with its Claude Code product.

OpenAI said it will continue to support Astral’s open-source software projects.

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Elon Musk gives an estimate for Tesla’s AI6 chip timeline... while the AI5 is still unfinished

Tesla CEO Elon Musk said yesterday that the company’s AI6 chip could, with “some luck and acceleration using AI,” be finalized and sent to manufacturing by December. For those paying attention, Tesla hasn’t confirmed that its previous chip, the AI5, has reached tape-out, with Musk saying only that the design is in “good shape” and “almost done.” Still, Musk is already talking about subsequent chips AI6, AI7, AI8, and beyond.

Here’s a roundup of when these chips are expected, what they’re supposed to do, and what Musk himself has said about them.

While the AI5 and AI6 will be made by TSMC and Samsung, respectively, Musk has said Tesla eventually aims to manufacture its future AI chips at Tesla’s upcoming Terafab factory in Austin.

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NHTSA expands Tesla FSD probe, focusing on whether system can detect when cameras can’t see the road

The National Highway Traffic Safety Administration said it is expanding its probe into Tesla’s Full Self-Driving system into an engineering analysis covering about 3.2 million Teslas, a majority of its vehicles that are on the road in the US, Reuters reports.

The agency is focusing on Tesla’s “degradation detection system,” which is meant to recognize when its camera-based technology cannot reliably perceive the road and prompt drivers to intervene:

“Available incident data raise concerns that Tesla’s degradation detection system, both as originally deployed and later updated, fails to detect and/or warn the driver appropriately under degraded visibility conditions such as glare and airborne obscurants. In the crashes that ODI has reviewed, the system did not detect common roadway conditions that impaired camera visibility and/or provide alerts when camera performance had deteriorated until immediately before the crash occurred.”

Tesla CEO Elon Musk has long argued that the company’s self-driving approach does not require the expensive lidar sensors used by rivals such as Waymo.

The agency is focusing on Tesla’s “degradation detection system,” which is meant to recognize when its camera-based technology cannot reliably perceive the road and prompt drivers to intervene:

“Available incident data raise concerns that Tesla’s degradation detection system, both as originally deployed and later updated, fails to detect and/or warn the driver appropriately under degraded visibility conditions such as glare and airborne obscurants. In the crashes that ODI has reviewed, the system did not detect common roadway conditions that impaired camera visibility and/or provide alerts when camera performance had deteriorated until immediately before the crash occurred.”

Tesla CEO Elon Musk has long argued that the company’s self-driving approach does not require the expensive lidar sensors used by rivals such as Waymo.

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