Abstract: Matrix multiplication is a commonly used operation in various graphics, imaging, robotics, and signal processing applications. In connection with the increase in the growth of the ...

High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

With AlphaTensor, DeepMind Technologies has presented an AI system that is supposed to independently find novel, efficient and provably correct algorithms for complex mathematical tasks. AlphaTensor ...

AlphaTensor, builds upon AlphaZero, an agent that has shown superhuman performance on board games, like chess, Go and shogi, and this work shows the journey of AlphaZero from playing games to tackling ...

What do encrypted messages, recognizing speech commands and running simulations to predict the weather have in common? They all rely on matrix multiplication for accurate calculations. DeepMind, an ...

Abstract: In this paper, we propose three modular multiplication algorithms that use only the IEEE 754 binary floatingpoint operations. Several previous studies have used floatingpoint operations to ...

Alphabet Inc.’s DeepMind unit today detailed AlphaTensor, an artificial intelligence system capable of discovering new algorithms that can be used to solve mathematical problems. DeepMind researchers ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...