Swift Transformers Reaches 1.0 – and Looks to the Future

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

3 Questions: Neural transparency and the future of AI design

Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.