18 August 2026
Smaller AI models gain reasoning ability through new memory techniques
- Researchers found that smaller models, including one with 150 million parameters (basic building blocks), can solve harder problems by using latent-space reasoning and memory, which lets them work through problems internally.
- A system called GPT-5.6 Sol demonstrated that compressing reasoning steps into memory acts as a capability multiplier, meaning it makes models substantially more capable without making them physically larger.
