Google DeepMind, AI/ML and ALPHA-fold

[Astronuc]

I came across a video regarding the use of AI/ML to work through complex datasets to determine complicated protein structures. It is a promising and beneficial use of AI/ML.

AlphaFold - The Most Useful Thing AI Has Ever Done​

AlphaFold is Google DeepMind’s contribution to the long-standing problem of protein structure prediction. It predicts the 3D structures of proteins with a high degree of accuracy and is now widely used by researchers.

https://www.ebi.ac.uk/training/onli...-strengths-and-limitations/what-is-alphafold/
https://en.wikipedia.org/wiki/AlphaFold

AI has the potential to be one of the most important and beneficial technologies ever invented.


Google DeepMind brings together two of the world’s leading AI labs — Google Brain and DeepMind — into a single, focused team led by our CEO Demis Hassabis. Over the last decade, the two teams were responsible for some of the biggest research breakthroughs in AI, many of which underpin the flourishing AI industry we see today.

DeepMind started in 2010, with an interdisciplinary approach to building general AI systems. The research lab brought together new ideas and advances in machine learning, neuroscience, engineering, mathematics, simulation and computing infrastructure, along with new ways of organizing scientific endeavors.

https://deepmind.google/about/


Edit/update: The AlphaFold article in Nature
John Jumper, Highly accurate protein structure prediction with AlphaFold, published 15 July 2021
https://www.nature.com/articles/s41586-021-03819-2

 

[Greg Bernhardt]

We talk a lot about the utility of AI, but I think it's pretty clear the applications for the medical/biology fields are numerous and exciting!

 

[BWV]

Alpha genome is the latest

https://deepmind.google/discover/blog/alphagenome-ai-for-better-understanding-the-genome/

Today, we introduce AlphaGenome, a new artificial intelligence (AI) tool that more comprehensively and accurately predicts how single variants or mutations in human DNA sequences impact a wide range of biological processes regulating genes. This was enabled, among other factors, by technical advances allowing the model to process long DNA sequences and output high-resolution predictions.