tech

Jon Keegan2/23/26

Report: OpenAI’s Stargate has been a chaotic mess

Just over a year ago, OpenAI CEO Sam Altman stood alongside President Trump, Oracle’s Larry Ellison, and SoftBank CEO Masayoshi Son to announce an ambitious $500 billion plan to build massive data centers in the US — Project Stargate.

While today an actual Stargate 1-gigawatt data center is certainly well under construction in Abilene, Texas, it turns out there wasn’t much of a plan in place at the time of the announcement, according to a new report from The Information.

The past year has been full of partner disputes, debt problems, and scuttled plans as the loosely defined project races to build the AI computing infrastructure that OpenAI is craving as competition heats up.

Per the report, OpenAI tried to build its own data centers as the project stalled, but lenders balked at funding the risky project. They eventually settled on the current plan, in which partner Oracle borrows the money and leases capacity back to OpenAI. OpenAI was still able to control the design of the facility.

The slow start for the project resulted in OpenAI missing its own goal of 10 gigawatts of AI computing capacity from Oracle and SoftBank by the end of 2025.

Inside OpenAI’s Scramble to Get Computing Power After Stargate Stalled

Inside OpenAI’s Scramble to Get Computing Power After Stargate Stalled

The past year has been full of partner disputes, debt problems, and scuttled plans as the loosely defined project races to build the AI computing infrastructure that OpenAI is craving as competition heats up.

Per the report, OpenAI tried to build its own data centers as the project stalled, but lenders balked at funding the risky project. They eventually settled on the current plan, in which partner Oracle borrows the money and leases capacity back to OpenAI. OpenAI was still able to control the design of the facility.

The slow start for the project resulted in OpenAI missing its own goal of 10 gigawatts of AI computing capacity from Oracle and SoftBank by the end of 2025.

More Tech

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12th Breakthrough Prize Ceremony - Arrivals

Apple is on its way to becoming the biggest smartphone seller in China

The memory crunch has made iPhones a more popular alternative as competitors’ prices rise.

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tech

Microsoft loses exclusive access to OpenAI’s models and tools while ending revenue-sharing deal with ChatGPT maker

Microsoft shares dropped as it announced a revised agreement with OpenAI.

The amended agreement ends revenue-sharing payments from Microsoft to OpenAI, and also ends Microsoft’s exclusive access to OpenAI’s intellectual property (i.e. models and products).

OpenAI’s revenue sharing with Microsoft will end in 2030, is subject to a total cap, and is no longer dependent on its achieving artificial general intelligence.

Amazon, a likely beneficiary of this lack of exclusivity, initially popped on the news but erased those gains.

This is a developing story.

The next phase of the Microsoft-OpenAI partnership - The Official Microsoft Blog

The next phase of the Microsoft-OpenAI partnership - The Official Microsoft Blog

tech

China just blew up one of Meta’s key AI bets

China has ordered Meta to unwind its $2 billion acquisition of Manus, a Chinese startup (since relocated to Singapore) that makes AI agents and was central to Meta’s push to turn its massive AI investments into a real business. The move is part of the Chinese government’s effort to stop US firms from gaining access to Chinese talent and intellectual property, as Washington continues to restrict sales of advanced AI chips to Chinese companies.

Unlike its tech peers, which can sell AI through cloud services, Meta mainly uses AI to improve its existing ad business rather than as a stand-alone revenue driver. The decision strips away one of Meta’s clearest paths to monetizing AI — leaving it spending like a hyperscaler, without a hyperscaler business model.

China blocks Meta's $2 billion acquisition of AI startup Manus

China blocks Meta's $2 billion acquisition of AI startup Manus

Unlike its tech peers, which can sell AI through cloud services, Meta mainly uses AI to improve its existing ad business rather than as a stand-alone revenue driver. The decision strips away one of Meta’s clearest paths to monetizing AI — leaving it spending like a hyperscaler, without a hyperscaler business model.

tech

Jon Keegan4/24/26

DeepSeek releases new V4 series models highlighting efficiency and long context

Chinese AI lab DeepSeek has released a major new version of its eponymous open-source AI models that are nipping at the heels of leading frontier models in some areas.

The most significant DeepSeek-V4 Pro and DeepSeek-V4 Flash both have a 1 million-token context — the amount of information the model can actively work with in a single session — which is a crucial feature for complex, long-running coding tasks.

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

The authors of the model acknowledge some of V4’s shortcomings, such as its lower scores on reasoning benchmarks, saying that V4 “trails state-of-the-art frontier models by approximately 3 to 6 months.”

As open-weight models, V4 can be run on any user’s own hardware, making the V4 models among the top-performing open-source models out there. V4’s large context and token efficiency are especially significant among open-source models.

But like with earlier DeepSeek models, don’t ask it about Tiananmen Square.

DeepSeek Unveils Flagship AI Model a Year After Breakthrough

DeepSeek Unveils Flagship AI Model a Year After Breakthrough

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

The authors of the model acknowledge some of V4’s shortcomings, such as its lower scores on reasoning benchmarks, saying that V4 “trails state-of-the-art frontier models by approximately 3 to 6 months.”

As open-weight models, V4 can be run on any user’s own hardware, making the V4 models among the top-performing open-source models out there. V4’s large context and token efficiency are especially significant among open-source models.

But like with earlier DeepSeek models, don’t ask it about Tiananmen Square.

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