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13 Jan 2026

AI models fall for the same optical illusions as humans, revealing how both brains work

Researchers discovered that AI models experience optical illusions the same way humans do when shown the rotating snakes illusion. The breakthrough suggests both artificial and biological vision systems rely on predictive coding—a mechanism that anticipates future visual input rather than passively processing images. This finding could finally explain why our brains get tricked by certain patterns.

2 Sources

08 Jan 2026

Stanford's SleepFM AI predicts 130+ diseases from a single night's sleep data

Researchers at Stanford Medicine developed SleepFM, an AI foundation model that analyzes overnight sleep study data to predict risk for more than 130 medical conditions years before diagnosis. Trained on 585,000 hours of polysomnography recordings from 65,000 individuals, the system excels at forecasting cancers, pregnancy complications, circulatory diseases, and mental health disorders by detecting hidden physiological patterns during sleep.

4 Sources

07 Jan 2026

MIT and Microsoft develop AI system CleaveNet to design sensors for early cancer detection

Researchers from MIT and Microsoft created CleaveNet, an AI model that designs peptide-based molecular sensors to detect cancer in its earliest stages. The system generates peptides targeted by cancer-linked proteases, enabling diagnosis through a simple urine test that could be performed at home.

2 Sources

02 Jan 2026

DeepSeek unveils mHC architecture that could reshape how developers train advanced AI models

Chinese AI firm DeepSeek has released research on Manifold-Constrained Hyper-Connections (mHC), a new AI training method that addresses signal degradation in neural networks. The framework could enable smaller developers to build frontier models without massive computational costs, potentially previewing the architecture behind the anticipated DeepSeek R2 model expected around February's Spring Festival.

7 Sources

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