Machine LearningAI Research4 min reading time

Looking beyond natural sequences

MIT AI News
Read full post
Researchers at MIT developed PottsMPNN, a machine-learning framework that improves protein sequence design by understanding the relationship between amino acid sequences and protein stability, enabling design of novel proteins beyond natural sequences. This approach moves beyond replicating natural sequences, focusing instead on the likelihood that sequences fold into desired structures and predicting mutation effects.

More in Machine Learning

Machine Learning4 min read

Arlequin AI raises €28M to build novel AI models that learn complex relationships at scale

SiliconANGLE
Machine Learning4 min read

DeepSeek launches V4.1-Flash and retires V4-Pro, its flagship model

The Next Web
Machine Learning3 min read

Nvidia and Palantir fine-tune a 30B Nemotron model for Nvidia’s supply chain. It beats a model 18 times its size.

Covered by 3 sources