Mechanistic interpretability is emerging as a strategic advantage for businesses looking to deploy AI responsibly.

Humanoid robots will soon be common, says Brett Adcock, founder of robot company Figure AI. In time, "the humanoid robot will ...

Using this information, the model can then tell us the probability of a drug-protein interaction that we did not previously ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

Learn how to build your own GPT-style AI model with this step-by-step guide. Demystify large language models and unlock their ...

A new study utilizes compact neural networks to uncover the underlying mechanisms behind human decision-making. Scientists have long studied how people and animals make decisions, often looking at how ...

Researchers have uncovered how primate brains transform flat, 2D visual inputs into rich, 3D mental representations of ...

Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

The starting point of a FlexOlmo project is a so-called anchor AI model. Every organization that participates in the project ...

Scientists at UCSF combined advanced brain-network modeling, genetics, and imaging to reveal how tau protein travels through ...

Implantable bioelectronics are vital to neuroscience, neurological therapies, and brain-machine interfaces. They serve as ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.