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 ...
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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 ...
Researchers at MIT's Computer Science & Artificial Intelligence Lab (CSAIL) have open-sourced Multiply-ADDitioN-lESS (MADDNESS), an algorithm that speeds up machine learning using approximate matrix ...
Algorithms have been used throughout the world’s civilizations to perform fundamental operations for thousands of years. However, discovering algorithms is highly challenging. Matrix multiplication is ...
High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...
Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...
In this paper, we have proved that the lower bound of the number of real multiplications for computing a length 2t real GFT(a,b) (a = ±1/2, b = 0 or b = ±1/2, a = 0) is 2t+1 – 2t - 2 and that for ...
A Hong Kong-based Matrix AI Network is developing a prototype of a new hybrid PoS/PoW consensus algorithm. This update was shared with Cointelegraph by Owen Tao, the company’s CEO. Tao described ...
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