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... known solutions, thus yielding new discoveries.show more

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. 🧵

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.

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

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. ↓

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 ↓

@kevinsekniqi does this count

*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.

I'm feeling insecure

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

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

applause

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

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

@gork holy shit look at this