TheSequence

Share this post
🧬 DeepMind’s AlphaFold Database
thesequence.substack.com

🧬 DeepMind’s AlphaFold Database

Weekly news digest curated by the industry insiders

Jul 31
21
Share this post
🧬 DeepMind’s AlphaFold Database
thesequence.substack.com

📝 Editorial 

It’s hard to think that it has been an entire year since DeepMind open-sourced AlphaFold, the model that astonished the machine learning (ML) world by predicting the structure of proteins based on a sequence of amino acids. AlphaFold can easily be considered the most relevant ML contribution to the world of science in the last decade. The initial release of AlphaFold was accompanied by a less promoted project known as  AlphaFold Protein Structure Database (AlphaFold DB). This project aimed to provide an open dataset with the structure of proteins. Last week, DeepMind doubled down in AlphaFold DB with a new and incredibly impressive release.  

In collaboration with EMBL’s European Bioinformatics Institute (EMBL-EBI), DeepMind upgraded AlphaFold DB with the structure of nearly all catalogued proteins known to science. The number is about 200 million protein structures from plants, animals, bacteria, fungi, and other organisms. The dataset has also been released as part of Google Cloud Public Datasets making it even more accessible to researchers. By providing access to the structure of proteins in a data-structured, searchable format, AlphaFold DB can drastically advance research across different scientific areas ranging from biology, pharmaceuticals or food safety. Another impressive open source contribution by DeepMind.    


🔺🔻TheSequence Scope – our Sunday edition with the industry’s development overview – is free. To receive high-quality content about the most relevant developments in the ML world every Tuesday and Thursday, please subscribe to TheSequence Edge 🔺🔻

🗓 Next week in TheSequence Edge:

Edge#213: we overview the fundamental types of tests to be applied on trained models; explain how Meta uses Bayesian Optimization to conduct better experiments in ML models; explore TensorFlow’s What-If Tool. 

Edge#214: we deep dive into NLLB-200, Meta AI’s new super model that achieved new milestones in machine translations across 200 languages.


Now, let’s review the most important developments in the AI industry this week

🔎 ML Research

AlphaFold DB vNext 

DeepMind expanded AlphaFold DB with predicted structures of all proteins known to science →read more on the DeepMind blog

ML Code Completion 

Google Research published an insightful blog post about the use of large language models and semantic rules engines to improve developer productivity →read more on the Google Research blog

Causal Inference and ML 

Amazon Research published a paper proposing a technique to apply causal inference to scenarios with continuous variables →read more on the Amazon Research blog


💬 Useful Tweet

Twitter avatar for @AiInfraai-infra-alliance @AiInfra
With hundreds of AI/ML infrastructure tools on the market, how do you make sense of it all? The AI Infrastructure Ecosystem of 2022 report delivers the first comprehensive/clear overview of the entire AI/ML infrastructure landscape. Get it now FREE.
AI Infrastructure Ecosystem of 2022With hundreds of AI/ML infrastructure tools on the market, how do you make sense of it all? Our first annual AI Infrastructure Ecosystem report gives team leads, technical executives and architects the keys they need to build or expand their infrastructure by providing a comprehensive and clear over…ai-infrastructure.org

July 14th 2022

2 Retweets6 Likes

Follow us on Twitter


🤖 Cool AI Tech Releases

Theseus  

Meta AI open-sourced Theseus, a library for incorporating domain knowledge in ML models →read more on the Meta AI blog

Giga-Scale MPM

ML monitoring platform Fiddler announced major improvements to its Model Performance Management (MPM) platform, achieving enhanced scalability and a deeper understanding of unstructured model behavior and performance →read more on the Fiddler’s blog


🛠 Real World ML 

ML Education at Uber 

Uber discusses some principles about its internal ML education program →read more on the Uber Engineering blog

Load Testing TensorFlow Serving 

The TensorFlow team details the techniques and results used to load test the TensorFlow Serving REST interface →read more on the TensorFlow blog


💸 Money in AI

  • AI triage and clinical-predictions platform Diagnostic Robotics raised $45 million Series B funding round led by StageOne investors. Hiring in Tel Aviv/Israel.

  • Postgres-as-a-service startup Neon raised $30 million in a Series A-1 round led by GGV. Hiring remote.

  • AI-powered rental price analytics startup PriceLabs raised a $30 million minority growth investment round led by Summit Partners. Hiring remote.

  • AI-powered voice assistants developer Datch raised $10 million in a Series A round led by Blackhorn Ventures. Hiring in the US (remote).

  • AI startup FeatureByte raised a $5.7 million seed round led by Glasswing Ventures and Tola Capital.

Share this post
🧬 DeepMind’s AlphaFold Database
thesequence.substack.com
Comments

Create your profile

0 subscriptions will be displayed on your profile (edit)

Skip for now

Only paid subscribers can comment on this post

Already a paid subscriber? Sign in

Check your email

For your security, we need to re-authenticate you.

Click the link we sent to , or click here to sign in.

TopNewCommunity

No posts

Ready for more?

© 2022 Jesus Rodriguez, Ksenia Semenova
Privacy ∙ Terms ∙ Collection notice
Publish on Substack Get the app
Substack is the home for great writing