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Title    Google DeepMind’s Game-Playing AI Just Found Another Way to Make Code Faster
Date    Sunday June 11, @05:00AM
Author    martyb
Topic   
from the cure-for-the-common-code? dept.
https://soylentnews.org/article.pl?sid=23/06/10/0053235

Google DeepMind's Game-Playing AI Just Found Another Way to Make Code Faster

upstart writes:

Google DeepMind's game-playing AI just found another way to make code faster:

It has also found a way to speed up a key algorithm used in cryptography by 30%. These algorithms are among the most common building blocks in software. Small speed-ups can make a huge difference, cutting costs and saving energy.

"Moore's Law is coming to an end, where chips are approaching their fundamental physical limits," says Daniel Mankowitz, a research scientist at Google DeepMind. "We need to find new and innovative ways of optimizing computing."

"It's an interesting new approach," says Peter Sanders, who studies the design and implementation of efficient algorithms at the Karlsruhe Institute of Technology in Germany and who was not involved in the work. "Sorting is still one of the most widely used subroutines in computing," he says.

DeepMind published its results in Nature today. But the techniques that AlphaDev discovered are already being used by millions of software developers. In January 2022, DeepMind submitted its new sorting algorithms to the organization that manages C++, one of the most popular programming languages in the world, and after two months of rigorous independent vetting, AlphaDev's algorithms were added to the language. This was the first change to C++'s sorting algorithms in more than a decade and the first update ever to involve an algorithm discovered using AI.

DeepMind added its other new algorithms to Abseil, an open-source collection of prewritten C++ algorithms that can be used by anybody coding with C++. These cryptography algorithms compute numbers called hashes that can be used as unique IDs for any kind of data. DeepMind estimates that its new algorithms are now being used trillions of times a day.

[...] DeepMind chose to work with assembly, a programming language that can be used to give specific instructions for how to move numbers around on a computer chip. Few humans write in assembly; it is the language that code written in languages like C++ gets translated into before it is run. The advantage of assembly is that it allows algorithms to be broken down into fine-grained steps—a good starting point if you're looking for shortcuts.

Journal Reference:
Daniel J. Mankowitz, Andrea Michi, Anton Zhernov, et al. Faster sorting algorithms discovered using deep reinforcement learning [open], Nature (DOI: 10.1038/s41586-023-06004-9)


Original Submission

Links

  1. "upstart" - https://soylentnews.org/~upstart/
  2. "Google DeepMind's game-playing AI just found another way to make code faster" - https://www.technologyreview.com/2023/06/07/1074184/google-deepmind-game-ai-alphadev-algorithm-code-faster/
  3. "published its results in Nature" - https://nlcontent.springernature.com/d-redirect/TIDP2085296XC4355335148545A394FD77DAE9043F50YI4/?url=https://www.nature.com/articles/s41586-023-06004-9&linksource=https://nemo-mail-monkey-live.springernature.app/15589138/pressReleases/[dossier-id]?editorialDomain=https://press.springernature.com&publicationDomain=https://dx.doi.org
  4. "10.1038/s41586-023-06004-9" - https://doi.org/10.1038/s41586-023-06004-9
  5. "Original Submission" - https://soylentnews.org/submit.pl?op=viewsub&subid=59900

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printed from SoylentNews, Google DeepMind’s Game-Playing AI Just Found Another Way to Make Code Faster on 2023-06-30 05:38:14