Machine learning redesigns microscopic web sensors to be five times more flexible than nature-inspired versions, enabling detection of masses as small as trillionths of a gram.

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, ...

What if vaccine development didn’t have to take a decade? This piece looks at how AI is helping scientists ask better ...

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A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...

The global spatial biology market is projected to grow at a compound annual growth rate (CAGR) of approximately 15% over the ...

Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease, affecting more than ...

Gene regulation is far more predictable than previously believed, scientists conclude after developing the deep learning ...

A research team has successfully demonstrated the world's first gene-editing treatment for Leber's hereditary optic ...

Google DeepMind released AlphaGenome on January 28, an AI model that predicts how DNA sequences translate into biological functions, processing up to one million base-pairs at once and outperforming ...

Brain imaging technologies (e.g., MRI, PET, advanced microscopy) are foundational tools for deciphering the brain's ...