Deep learning is driving the rapid evolution of algorithms that can automatically find and trace cells in a wide range of microscopy experiments.

Blockchain technologies are digital systems that work by distributing copies of information across several computers, also ...

It doesn’t take much to make machine-learning algorithms go awry The rise of large-language models could make the problem worse ...

For artificial intelligence to realize its potential — to relieve humans from mundane tasks and eventually invent new solutions to our problems — computers will need to get better at seeing the world ...

Continual learning is when a computer is trained to continuously learn a sequence of tasks, using its accumulated knowledge from old tasks to better learn new tasks. Yet one major hurdle ...

The intersection of machine learning and mathematical logic — spanning computer science, pure mathematics, and statistics — has catalyzed recent advances in artificial intelligence and deep learning ...

Having machines learn from experience was once considered a dead end. It’s now critical to artificial intelligence, and work in the field has won two men the highest honor in computer science.

A new AI algorithm can associate brain activity with certain behaviors, an advancement that can help improve brain-computer interfaces and find new patterns in neural activity.

Computer vision algorithms can check the identity of users, preventing identity theft and providing secure access to cryptocurrency accounts by examining facial features and ID papers.

As our artificial intelligence algorithms continue to struggle with metacognition and causal inference, it is essential that we feed them the right data.