Google Makes Nvidia Dance
Research Rundown #163, plus new memos on Mach Industries, Zepto and more.
Research Rundown
Just four months after ChatGPT’s launch, Satya Nadella explained his ambitions for Microsoft in the rapidly accelerating AI race: “I want people to know that we made them dance.” Google was clearly caught off guard by the rise of LLMs. The company’s rushed launch of Bard was criticized as emblematic of a broader “bureaucratic lag” at Google. But now Google has most certainly come out to dance. The recent launch of Gemini 3 Pro reportedly “tops the leaderboard on reasoning, coding, multimodal reasoning, and tool-use benchmarks,” outperforming most rival models. Now, it’s Google’s turn to make Nvidia dance.
News broke this week that Meta is considering using Google TPUs in its own data centers beginning in 2027, and may rent TPUs from Google starting in 2026. Google has not previously sold or leased TPUs to other companies. In response to this news, Alphabet stock rallied over 6% on Monday, and Nvidia shares fell as much as 7% before partially retracing. Nvidia responded in an X post saying, “We’re delighted by Google’s success — they’ve made great advances in AI and we continue to supply to Google… NVIDIA is a generation ahead of the industry — it’s the only platform that runs every AI model and does it everywhere computing is done.”
Google’s TPU offering positions it as the first serious merchant-silicon competitor to Nvidia in frontier-scale AI compute. One report from SemiAnalysis explains how, in particular, Google’s system-level design (scale-up networking, liquid cooling, optical circuit switching, compiler efficiency, and internal software tooling) allows TPUv7 to achieve lower cost per effective FLOP than Nvidia Blackwell.
Beyond the broader system-level improvements, Google has made important positions around its software ecosystem. Google has begun shifting its TPU software stack from an internally focused system built around JAX and XLA to a more open, externally usable model that adds native PyTorch support and integrations. Google is attempting to reduce the friction of adopting TPUs for large-scale training and inference. In contrast, Nvidia’s CUDA ecosystem remains the most mature and widely adopted accelerator software stack, offering first-class PyTorch integration, highly optimized libraries, and broad community support built over more than a decade. While CUDA still provides a more complete and battle-tested environment, Google’s new software investments are designed to narrow that usability gap and make TPUs a feasible alternative for labs with the engineering capability to extract high utilization.
However, SemiAnalysis argues that, while TPUv7 represents Google’s first true Nvidia-competitive platform, with superior TCO, massive scale, and enough ecosystem support to win deals from Anthropic, Meta, and others, TPUv8 is only incrementally better, while Nvidia Rubin is aggressively better, meaning TPU’s window of advantage may narrow beyond 2027. The key questions going forward will be around the TPU ecosystem’s success software openness, external adoption, and Google’s ability to accelerate silicon cycles as fast as Nvidia.
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On Monday, Anthropic announced Opus 4.5, the first model to score over 80% on the coding benchmark SWE-bench. The model also achieved new high scores on tool use and general problem-solving benchmarks, outperforming previous Anthropic models and Google’s newly released Gemini 3 Pro.
Prediction market Polymarket was granted CFTC approval this week, allowing Polymarket contracts to be traded via Futures Commission Merchants (FCMs) and brokerages. The terms of the approval require Polymarket to increase trade activity tracking and Part 16 reporting, including daily trading volume and open interest.
In other prediction market news, a Nevada judge ruled this week that Kalshi is subject to Nevada state gaming regulation, following a cease-and-desist letter issued in March that accused the platform of violating multiple state laws. The Nevada Gaming Commission and Gaming Control Board were blocked from regulating the platform in April by a district judge, a ban that was lifted this week to allow regulation going forward. Kalshi filed an emergency motion to prevent the decision from taking effect while the company files an appeal.
The US Department of Energy (DOE) announced the Genesis Mission this week, an initiative launched via executive order to mobilize research, data, and resources towards US AI dominance. The initiative has been compared to the Manhattan Project and the Apollo Mission of the 20th century. Frontier AI model developers will have access to National Laboratory data, among other resources and data, via the program.
Last month, the federal government signed a partnership with Westinghouse Electric to invest $80 billion in AP1000 nuclear reactors, pressurized water reactors (PWRs) constructed by Westinghouse to be safer, more efficient, and more cost-effective than traditional reactors. Concerns about this plan have surfaced in the weeks since, primarily surrounding the costs and construction timelines of AP1000s relative to expectations; Only two reactors were finished in the last decade, completed 7 years behind schedule and over double the expected budget.
Google DeepMind hired Aaron Saunders, the former CTO of Boston Dynamics, last week in a push to expand its robotics division. DeepMind’s CEO, Demis Hassabis, said of the initiative, “We want to build an AI system, a Gemini base, that can work almost out-of-the-box, across any body configuration.” Prior to becoming CTO of Boston Dynamics, Saunders worked on four- and six-legged robots and served as VP of engineering.
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