Artificial intelligence

Computer scientist Lance Fortnow writes that by embracing the computations that surround us, we can begin to understand and tame our seemingly random world.

Optical neural networks, which use photons instead of electrons, have advantages over traditional systems. They also face major obstacles.

Researchers are drawing on ideas from game theory to improve large language models and make them more consistent.

Google DeepMind’s AlphaFold3 and other deep learning algorithms can now predict the shapes of interacting complexes of protein, DNA, RNA and other molecules, better capturing cells’ biological landscapes.

The computer scientist Ellie Pavlick is translating philosophical concepts such as “meaning” into concrete, testable ideas.

By apparently overtraining them, researchers have seen neural networks discover novel solutions to problems.

Large language models do better at solving problems when they show their work. Researchers are beginning to understand why.

Mathematicians are working to fully explain unusual behaviors uncovered using artificial intelligence.

Erasing key information during training results in machine learning models that can learn new languages faster and more easily.