TechCrunch Startup News Improvements in ‘reasoning’ AI models may slow down soon, analysis finds
May 15, 2025
A recent analysis reveals that significant advancements in reasoning AI models may soon slow down. The report from a nonprofit research institute highlights the challenges of scaling these models, especially focusing on OpenAI's O3. Increased computational demands could put a damper on performance gains. Are we nearing the limits of what these models can achieve? Tune in for insights into the future of reasoning AI.
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Potential Slowdown in Reasoning AI Progress
- Reasoning AI models have shown strong recent gains but may soon face a slow down in progress within about a year.
- This is due to limits in how much computing and reinforcement learning can further improve their performance.
Reinforcement Learning Drives Gains
- Reasoning models improve by applying more computing especially in reinforcement learning stages after initial training.
- OpenAI plans to increase computing dedicated to reinforcement learning even more than for the initial model training.
Scaling Limits in Reasoning Models
- Performance gains from reinforcement learning grow faster than standard model training but will converge by 2026.
- Research overhead and cost may limit how far reasoning models can scale despite compute increases.