AI Research

TL; DR: Introducing CodeT5 — the first code-aware, encoder-decoder-based pre-trained programming language model, which enables a wide range of code intelligence applications including code understanding and generation tasks. CodeT5 achieves state-of-the-art performance on…

TL; DR: We propose a new vision-language representation learning framework which achieves state-of-the-art performance by first aligning the unimodal representations before fusing them. Vision and language are two of the most fundamental channels…

AI can learn the language of biology to create artificial proteins across multiple protein types that are functional and unseen in nature.

An AI model can generate sequences across natural language and proteins with attributes that go beyond the training distribution

With data rapidly being generated by millions of people, it's not feasible to label all of it. Learn about the recent advancements in ML for how to train vision models with unlabelled data using self-supervised learning.

How many emails and working-related conversations do you have every day? The average office worker receives about 121 emails daily and uncountable messages on platforms such as Slack, Team, or iMessage. With the…

The empirical success of deep learning has posed significant challenges to machine learning theory: Why can we efficiently train neural networks with gradient descent despite its highly non-convex optimization landscape? Why do over-parametrized…