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Google DeepMind trains Gemini 3.1 Flash-Lite on simulated patients to sharpen psychiatric intake

Google DeepMind trains Gemini 3.1 Flash-Lite on simulated patients to sharpen psychiatric intake

Photo: Crypto Briefing

Reinforcement learning cut missed acute-risk escalations from 30.5% to 12.9% in adversarial safety tests, according to a new preprint Google DeepMind researchers have put a small Gemini model through something like a psychiatry residency. In a preprint published October 29, 2026, they report that training Gemini 3.1 Flash-Lite against simulated patients meaningfully improved how it conducts psychiatric intake interviews. The headline safety number is the one that matters most. In adversarial tests, the share of acute safety risks the model failed to escalate fell from 30.5% to 12.9% .

Source: Crypto Briefing

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