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Bridgewater Research - Google's Gemini 3
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A macroeconomic and investment perspective from Bridgewater Associates on the resource competition dynamics triggered by frontier AI development, relevant to understanding compute governance and concentration-of-power risks.
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Importance: 42/100blog postanalysis
Summary
Bridgewater Associates analyzes how Google's Gemini 3 announcement signals a new phase of aggressive resource acquisition in AI development, with major players racing to secure compute, energy, and infrastructure. The piece examines the macroeconomic and geopolitical implications of AI's escalating capital demands and what this competitive dynamic means for the broader economy.
Key Points
- •Google's Gemini 3 marks a inflection point where AI development has entered an intensive resource acquisition phase involving compute, energy, and infrastructure.
- •Major AI players are engaging in large-scale capital deployment to secure competitive advantages, reshaping investment and industrial landscapes.
- •The resource race has significant macroeconomic implications, including effects on energy markets, semiconductor supply chains, and sovereign competition.
- •Bridgewater frames this as a structural shift rather than a cyclical trend, suggesting sustained demand for AI-related resources.
- •The analysis raises questions about concentration of power among well-resourced incumbents and the geopolitical dimensions of AI infrastructure control.
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| Page | Type | Quality |
|---|---|---|
| Bridgewater AIA Labs | Organization | 66.0 |
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Google’s Gemini 3 Means AI’s “Resource Grab” Phase Is On
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Google’s Gemini 3 Means AI’s “Resource Grab” Phase Is On
November 26, 2025
By Greg Jensen , Jas Sekhon
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Quick thoughts from co-CIO Greg Jensen and AIA Labs Chief Scientist Jas Sekhon on the release of Google’s Gemini 3 model and its implications for economies and markets.
Editor's Note: This article was updated on December 2, 2025 to include new information.
Progress in artificial intelligence continues at a rapid pace. We have described how this rapid technological advancement has driven the industry into a “resource grab” phase, which is more dangerous than earlier stages of the AI boom and has major implications for capital markets. In today’s report , we focus on a timely development in the technological progress that underpins AI’s economic impact—Google’s release of its latest model, Gemini 3—and share some of the key takeaways for the AI ecosystem, economies, and markets. As we see it:
Both external testing and our own internal testing indicates that Gemini 3 is the best publicly available model in terms of raw intelligence and reflects the biggest jump in frontier model capabilities we’ve seen in a while. The model is strongly multimodal—performing well in text, image, and video generation and interpretation. Across a range of text-based assessments, like coding, “ humanity’s last exam ,” mathematical reasoning, as well as vision-based assessments, Gemini 3 outperforms previous models by a substantial margin. On our own internal tests, Gemini 3 is the largest jump in performance since at least OpenAI’s o3 more than half a year ago, and possibly since o1, which was released in late 2024. The charts below show Gemini 3 versus previous models, using the Center for AI Safety’s aggregation of different AI benchmarks.
(It’s worth noting that, following Gemi
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