Google AI: Release Notes Developing Google DeepMind's Thinking Models
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Feb 24, 2025 
Jack Rae, Principal Scientist at Google DeepMind, shares insights on advancing reasoning models like Gemini. He discusses how increased 'thinking time' enhances model performance and the significance of long context in language modeling. Rae also highlights the evolution from gaming memory systems to real-world AI applications, emphasizing the need for developer feedback and user interaction. The conversation delves into practical uses, the future of AI reasoning, and innovative evaluation methods that reflect real-world scenarios.
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Reasoning Model Definition & Use Cases
- Reasoning models plan and think before acting, composing knowledge for novel scenarios.
- They excel in complex tasks like coding or financial analysis where latency is acceptable.
Reasoning Models Enhance User Experience
- Reasoning models unlock increased capability by spending more inference time computing.
- Users gain higher certainty and more sophisticated answers, even for everyday tasks.
Thinking Time Improves Accuracy
- Increased "thinking time" allows models to catch mistakes, revise initial conditions, and explore solutions.
- This mimics human thought processes, leading to better accuracy.