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We also applied AlphaEvolve to over 50 open problems in analysis ✍️, geometry 📐, combinatorics ➕ and number theory 🔂, including the kissing number problem. 🔵 In 75% of cases, it rediscovered the best solution known so far. 🔵 In 20% of cases, it improved upon the previously best...

95,738 Aufrufe • vor 1 Jahr •via X (Twitter)

14 Kommentare

Profilbild von Google DeepMind
Google DeepMindvor 1 Jahr

Introducing AlphaEvolve: a Gemini-powered coding agent for algorithm discovery. It’s able to: 🔘 Design faster matrix multiplication algorithms 🔘 Find new solutions to open math problems 🔘 Make data centers, chip design and AI training more efficient across @Google. 🧵

Profilbild von Google DeepMind
Google DeepMindvor 1 Jahr

Our system uses: 🔵 LLMs: To synthesize information about problems as well as previous attempts to solve them - and to propose new versions of algorithms 🔵 Automated evaluation: To address the broad class of problems where progress can be clearly and systematically measured. 🔵 Evolution: Iteratively improving the best algorithms found, and re-combining ideas from different solutions to find even better ones.

Profilbild von Google DeepMind
Google DeepMindvor 1 Jahr

Over the past year, we’ve deployed algorithms discovered by AlphaEvolve across @Google’s computing ecosystem, including data centers, software and hardware. It’s been able to: 🔧 Optimize data center scheduling 🔧 Assist in hardware design 🔧 Enhance AI training and inference

Profilbild von Google DeepMind
Google DeepMindvor 1 Jahr

We applied AlphaEvolve to a fundamental problem in computer science: discovering algorithms for matrix multiplication. It managed to identify multiple new algorithms. This significantly advances our previous model AlphaTensor, which AlphaEvolve outperforms using its better and more generalist approach. ↓

Profilbild von Google DeepMind
Google DeepMindvor 1 Jahr

We’re excited to keep developing AlphaEvolve. This system and its general approach has potential to impact material sciences, drug discovery, sustainability and wider technological and business applications. Find out more ↓

Profilbild von GC
GCvor 1 Jahr

@kevinsekniqi does this count

Profilbild von Hashir Omer Farooqi
Hashir Omer Farooqivor 1 Jahr

*In 75% of cases, it rediscovered the best solution known so far.* If we don't have a proof that our best solutions are optimal, this 75% is a good evidence of memorization or training bias.

Profilbild von tumin~
tumin~vor 1 Jahr

I'm feeling insecure

Profilbild von Roman Leventov
Roman Leventovvor 1 Jahr

This NotebookLM style is unbearable. Please don't use it for public posts like this

Profilbild von 3THER_
3THER_vor 1 Jahr

Nice touch using notebookLM podcast for the explanation - I see what you did there ;D

Profilbild von Ciprianii
Ciprianiivor 1 Jahr

applause

Profilbild von Achesui
Achesuivor 1 Jahr

@grok explain this for a simple human being with low self-steem and with around 70 IQ, why is this important?

Profilbild von Oded Ben Dov 🧬
Oded Ben Dov 🧬vor 1 Jahr

I need this for a missing piece of an P=NP proof. PLEASE

Profilbild von bry257
bry257vor 1 Jahr

@gork holy shit look at this

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