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Mohammadamin Barekatain on Muck Rack

Mohammadamin Barekatain

As seen in: Nature, arXiv, Flipboard
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Articles

Mathematical discoveries from program search with large language models - Nature

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By Bernardino Romera-Paredes, Mohammadamin Barekatain, Pushmeet Kohli, Matej Balog, Pengming Wang
| Nature Verified
Abstract Large Language Models (LLMs) have demonstrated tremendous capabilities in solving complex tasks, from quantitative reasoning to understanding natural language. However, LLMs sometimes suffer from confabulations (or hallucinations) which can result in them making plausible but incorrect statements [1,2]. This hinders the use of current large models in scientific discovery.
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Faster sorting algorithms discovered using deep reinforcement learning

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By Daniel J. Mankowitz, Cosmin Marian Paduraru, Shariq Iqbal, Jean-Baptiste Lespiau, Kevin Millikin, Stephen Gaffney, Chris Gamble, Mohammadamin Barekatain, Yujia Li, Amol Mandhane, Thomas Hubert Verified, Julian Schrittwieser, Pushmeet Kohli, Martin Riedmiller, Oriol Vinyals, DAVID SILVER, Andrea Michi, Anton Zhernov, Marco Gelmi, Marco Selvi, Edouard Leurent, Alex Ahern, Thomas Köppe, Sophie Elster, Jackson Broshear, Kieran Milan, Robert Tung, Minjae Hwang, Taylan Cemgil
| Flipboard
Say What? AI Doesn’t Understand Anything Whenever I look at AI generated content, whether it be pictures or text, they all have the same flaw. The AI cannot comprehend what it is making. Let …
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Discovering faster matrix multiplication algorithms with reinforcement learning - Nature

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By DAVID SILVER, Alhussein Fawzi, Mohammadamin Barekatain
| Nature Verified
Abstract Improving the efficiency of algorithms for fundamental computations can have a widespread impact, as it can affect the overall speed of a large amount of computations. Matrix multiplication is one such primitive task, occurring in many systems—from neural networks to scientific computing routines. The automatic discovery of algorithms using machine learning offers the prospect of reaching beyond human intuition and outperforming the current best human-designed algorithms.
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