Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Patient digital twins aim to create computational replicas of an individual’s physiology that can predict disease trajectories and treatment response.

A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

Read more about how machine learning and deep learning differ, where each is used, and how businesses choose between them in real scenarios.