Reusability Report: Optimizing T-count in General Quantum Circuits with AlphaTensor-Quantum.

forget alphatensor, how many kernels can be ultra sped up by magic numbers?

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

Quantum circuit optimization with AlphaTensor Fault-tolerant quantum computers aim to run powerful algorithms by using quantum bits (qubits), but they have to deal with hardware errors. Scientists handle these errors using special error-correction techniques, which make some

So it's strictly better than AlphaTensor on the domain that AlphaTensor was RL'd on, without using RL...

Congrats to @GoogleDeepMind for the breakthrough achieved with AlphaEvolve. Earlier AlphaTensor lowered the tensor rank of matrix multiplication of 4x4 matrices over Z2 from 49=7^2 (Strassen) to 47. AlphaEvolve does the job for standard arithmetic: 49 -> 48

🧠 AI Outpacing Humans: Proof in the Code Here’s where recent studies and breakthroughs show AI already eclipsing human capability:1. Mathematical Problem Solving DeepMind’s AlphaTensor and cap set solution cracked a 132-year-old open math problem — a feat no human had

Básicamente han seguido una receta similar que con AlphaTensor. Coger un problema fundamental de computación y poner a la IA a jugar para resolverlo de forma más eficiente que los métodos actuales.

Matej Balog @matejbalog (DeepMind) "AlphaTensor: Discovering faster matrix multiplication algorithms with RL"

AI is coming for you! While "AlphaTensor-Quantum" might indeed be able to "save hundreds of hours of research by optimizing relevant quantum circuits in a fully automated way", it also robs us the opportunity to do it manually and get paid for it. https://t.co/bdQntX3JIZ

If you though AlphaTensor was a big deal (if you heard me in spaces — it’s a massive deal for multiplying the impact of existing dedicated ASICS for models). Check this out: https://t.co/z4OQFM7C1m Deepmind sped up sorting algorithm implementations.. has anyone done this since

Our team at @GoogleDeepMind is looking for a Student Researcher to work on AI for maths and algorithmic discovery (we did AlphaTensor and FunSearch before); if you've been accepted to the program and are looking for a team please reach out at anovikov@google.com

First Open Source Implementation of DeepMind’s AlphaTensor https://t.co/k0yMlQzXUE

Data science's new focus is finding faster arithmetic algorithms: On Oct. 5, 2022, a team from DeepMind, Alphabet's UK-based subsidiary, reported in 'Nature' a way of uncovering better algorithms through its AlphaTensor reinforcement learning framework. https://t.co/jyEBksE3P7

#キャルちゃんのquantphチェック 耐故障量子計算において最も計算量が高価なゲートであるTゲートのカウントの最適化と、テンソル分解の関係を利用した、深層強化学習ベースの量子回路最適化手法 AlphaTensor-Quantum を開発。Google DeepMind, Quantinuumなどの研究。 https://t.co/o2nAUDqiRO

🔥🔥 ¡NUEVO VÍDEO! 🔥🔥 IA + CIENCIA = ¡Explosión de Inteligencia! La verdadera revolución de la IA se vivirá cuando empecemos a ver cómo se usa para acelerar los descubrimientos científicos... Y DeepMind lo sabe. ¿Conocéis a AlphaTensor? 😏 👉 LINK: https://t.co/reRTbSa9BO

From its name, I thought AlphaEvolve would be a fancy self-play mcts thing, like AlphaTensor (left). Turns out it's much more like a small #dspy program (right)

One type of quantum gate, known as a T gate, makes it challenging to build fault-tolerant quantum computers at scale as they are expensive to run. Our system helps minimize the number of T gates used in circuits - and is an extension of AlphaTensor, the first AI to discover

In @NatMachIntell, we show how our AI system AlphaTensor-Quantum can make quantum computing more efficient. 🖥️⚡ By optimizing quantum circuits, it’s helping run calculations faster to save resources and accelerate discoveries. ↓ https://t.co/6U4ZUABxhe