When ever I see a cool new result in #ComputationalMath, I like to see if I can replicate it. So, last month when that Nature article came out about #MatrixMultiplication formulas from #AlphaTensor I set out see if I could get their formulas and verify them symbolically.
I was able to do that and of course they were right. But I was excited to see Kauers and Moosbauer publish a response a couple days later. So, here's their results replicated in a Maple Jupyter notebook https://github.com/johnpmay/MapleSnippets/blob/main/KMtoFFM.ipynb

La multiplication de matrices gagne en vitesse grâce à l’intelligence artificielle

👉 Il y a un enjeu réel à optimiser les méthodes de calcul de ce type d’opération, fréquent dans les programmes informatiques. L’algorithme d’apprentissage profond #AlphaTensor de #DeepMind enclenche la vitesse supérieure.

https://www.pourlascience.fr/sd/mathematiques/la-multiplication-de-matrices-gagne-en-vitesse-grace-a-l-intelligence-artificielle-24383.php

#mathematiques #ia #google #matrice #pourlascience

RT @DeepMind@twitter.com

Today in @Nature@twitter.com: #AlphaTensor, an AI system for discovering novel, efficient, and exact algorithms for matrix multiplication - a building block of modern computations. AlphaTensor finds faster algorithms for many matrix sizes: https://dpmd.ai/dm-alpha-tensor & https://dpmd.ai/nature-alpha-tensor 1/

🐦🔗: https://twitter.com/DeepMind/status/1577677899108421633

Since 1969 Strassen’s algorithm has famously stood as the fastest way to multiply 2 matrices - but with #AlphaTensor we’ve found a new algorithm that’s faster, with potential to improve efficiency by 10-20% across trillions of calculations per day! https://dpmd.ai/dm-alpha-tensor
https://twitter.com/i/web/status/1577705369425543169