Open-Ended Learning Leads to Generally Capable Agents | Results Showreel

This is the accompanying video for the paper "Open-Ended Learning Leads to Generally Capable Agents" (DeepMind 2021). All results shown are with the same agent and on hand-authored probe tasks that were held out of training. Further reading blog: https://deepmind.com/blog/article/generally-capable-agents-emerge-from-open-ended-play Paper: https://deepmind.com/research/publications/open-ended-learning-leads-to-generally-capable-agents...

22h

AlphaFold Protein Structure Database

With EMBL-EBI, we're proud to launch the AlphaFold Protein Structure Database, which offers the most complete and accurate picture of the human proteome, doubling humanity’s accumulated knowledge of high-accuracy human protein structures - for free. Try it today: dpmd.ai/alphafolddb

5d

NeurIPS 2020: JAX Ecosystem Meetup

Learn more about JAX and why it's effective for research in reinforcement learning, GANs, meta-gradients and more. Date: 09/12/20 Slides: https://bit.ly/3pQB0vl

Jan 2021

AlphaFold: The making of a scientific breakthrough

The inside story of the DeepMind team of scientists and engineers who created AlphaFold, an AI system that is recognised as a solution to "protein folding", a grand scientific challenge for more than 50 years. Find out more: deepmind.com/alphafold Protein references: TBP = To be published 1BYI: Sandalova, T., et al. (1999) Structure of...

Nov 2020

Protein folding explained

Join DeepMind Science Engineer Kathryn Tunyasuvunakool to explore the hidden world of proteins. These tiny molecular machines underpin every biological process in every living thing and each one has a unique 3D shape that determines how it works and what it does. But figuring out the exact structure of a protein is an expensive and often time-consuming...

Nov 2020

DeepMind Scholars: Benedetta's story

The DeepMind Scholars programme gives talented students from underrepresented backgrounds the support they need to study at leading universities, and connect with our researchers and engineers. Scholars get their Masters' fees paid in full, as well as guidance and support from personal DeepMind mentors. Find out more on our website: https://deepmind.com/scholarships

Nov 2020

DeepMind x UCL | Deep Learning Lectures | 12/12 | Responsible Innovation

What can we do to build algorithms that are safe, reliable and robust? And what are the responsibilities of technologists who work in this area? In this talk, Chongli Qin and Iason Gabriel explore these questions — connected through the lens of responsible innovation — in two parts. In the first part, Chongli explores the question of why and how we...

Jul 2020

DeepMind x UCL | Deep Learning Lectures | 11/12 | Modern Latent Variable Models

This lecture, by DeepMind Research Scientist Andriy Mnih, explores latent variable models, a powerful and flexible framework for generative modelling. After introducing this framework along with the concept of inference, which is central to it, Andriy focuses on two types of modern latent variable models: invertible models and intractable models. Special...

Jul 2020

Women at DeepMind | Applying for Technical Roles

It’s no secret that the gender gap still exists within STEM. Despite a slight increase in recent years, studies show that women only make up about a quarter of the overall STEM workforce in the UK, for example. While the reasons vary, many women report feeling held back by a lack of representation, clear opportunities and information on what working...

Jun 2020

DeepMind x UCL | Deep Learning Lectures | 10/12 | Unsupervised Representation Learning

Unsupervised learning is one of the three major branches of machine learning (along with supervised learning and reinforcement learning). It is also arguably the least developed branch. Its goal is to find a parsimonious description of the input data by uncovering and exploiting its hidden structures. This is presumed to be more reminiscent of how the...

Jun 2020