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Summary:

A report by Bridgewater Associates’ co-CIO Greg Jensen and AIA Labs Chief Scientist Jas Sekhon analyzes the implications of Google’s Gemini 3 AI model release. The key takeaway is that Gemini 3 demonstrates continued progress in pre-training scaling, a crucial factor in AI model development. It appears to have used significantly more pre-training compute than previous models like GPT-4o and GPT-5, resulting in notable capability improvements. This signals a renewed push in the industry to overcome pre-training challenges and further scale AI models. While Anthropic’s Claude Opus 4.5 is strong in agentic coding tasks, Gemini 3 appears superior in general intelligence. The report anticipates other AI labs will follow Google’s lead in scaling pre-training as more data centers become available.

News Article:

Google’s Gemini 3 Sparks New AI Arms Race: Bridgewater Analysts See Resurgence in Pre-Training Scaling

December 2, 2025 – Google’s release of Gemini 3 has sent ripples through the artificial intelligence community, signaling a renewed focus on pre-training scaling as the key to unlocking further AI advancements, according to analysis from Bridgewater Associates.

In a new report, co-CIO Greg Jensen and AIA Labs Chief Scientist Jas Sekhon highlight that Gemini 3 represents the first major model release to demonstrate a significant leap in pre-training compute in recent memory. Pre-training, the foundational phase of AI model development, has faced challenges in recent years, leading to speculation that progress might stall.

“Gemini 3 shows that pre-training scaling will continue. It appears to have used at least 2-3 times more compute than GPT-4o and GPT-5 in its pre-training, and possibly an order of magnitude more,” Jensen and Sekhon write.

The analysts believe this breakthrough will spur other AI labs to invest heavily in scaling their pre-training capabilities, especially as new, large-scale data centers come online next year. DeepSeek has already acknowledged the gap between its V3.2 model and Gemini 3, citing its comparatively smaller pre-training compute and stating plans to scale.

While Anthropic’s recently released Claude Opus 4.5 model shows strength in agentic coding tasks, the Bridgewater report suggests Gemini 3 currently holds an edge in general intelligence. The paper also points out that Gemini 3 likely went through less post-training than GPT-5, suggesting that Google has substantial room to further improve Gemini 3’s capabilities.

The report underscores that the rapid advancement in AI continues to drive a “resource grab” phase within the industry, with major implications for capital markets. The competition for compute resources and talent is expected to intensify as companies race to develop increasingly powerful AI models.

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