this post was submitted on 29 Nov 2023
38 points (100.0% liked)

Actually Useful AI

2007 readers
7 users here now

Welcome! ๐Ÿค–

Our community focuses on programming-oriented, hype-free discussion of Artificial Intelligence (AI) topics. We aim to curate content that truly contributes to the understanding and practical application of AI, making it, as the name suggests, "actually useful" for developers and enthusiasts alike.

Be an active member! ๐Ÿ””

We highly value participation in our community. Whether it's asking questions, sharing insights, or sparking new discussions, your engagement helps us all grow.

What can I post? ๐Ÿ“

In general, anything related to AI is acceptable. However, we encourage you to strive for high-quality content.

What is not allowed? ๐Ÿšซ

General Rules ๐Ÿ“œ

Members are expected to engage in on-topic discussions, and exhibit mature, respectful behavior. Those who fail to uphold these standards may find their posts or comments removed, with repeat offenders potentially facing a permanent ban.

While we appreciate focus, a little humor and off-topic banter, when tasteful and relevant, can also add flavor to our discussions.

Related Communities ๐ŸŒ

General

Chat

Image

Open Source

Please message @sisyphean@programming.dev if you would like us to add a community to this list.

Icon base by Lord Berandas under CC BY 3.0 with modifications to add a gradient

founded 1 year ago
MODERATORS
 

Trove of combos is >45 times larger than number unearthed in entire history of science.

you are viewing a single comment's thread
view the rest of the comments
[โ€“] autotldr@lemmings.world 6 points 1 year ago

This is the best summary I could come up with:


The trove of theoretically stable but experimentally unrealized combinations identified using an AI tool known as GNoME is more than 45 times larger than the number of such substances unearthed in the history of science, according to a paper published in Nature on Wednesday.

The number of substances found is equivalent to almost 800 years of previous experimentally acquired knowledge, DeepMind estimated, based on 28,000 stable materials being discovered during the past decade.

Two potential applications of the new compounds include inventing versatile layered materials and developing neuromorphic computing, which uses chips to mirror the workings of the human brain, Cubuk said.

The team deployed computation, historical data, and machine learning to guide an autonomous laboratory, known as the A-lab, to create 41 novel compounds from a target list of 58โ€”a success rate of more than 70 percent.

The key to the improvements was how AI techniques were combined with existing sources such as a large data set of past synthesis reactions, he added.

The techniques outlined in the two Nature papers would enable new materials to be identified โ€œwith the speeds necessary to address the grand challenges of the world,โ€ said Bilge Yildiz, a Massachusetts Institute of Technology professor who was not involved in either piece of research.


The original article contains 592 words, the summary contains 209 words. Saved 65%. I'm a bot and I'm open source!