Can symbolic regression be the key to transforming opaque deep learning models into interpretable, closed-form mathematical equations? or Say you have trained your deep learning model. It works. But do you know what it has actually learned? A team of University of Cambridge researchers propose ‘SymTorch’, a library designed to integrate symbolic regression (SR) into deep learning workflows. It enables researchers to approximate neural network components with closed-form mathematical expressions, facilitating functional interpretability and potential inference acceleration. https://arxiv.org/pdf/2602.21307 […]

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[Crossposted on LessWrong] Throughout history, technological and scientific advances have had both good and ill effects, but their overall impact has been overwhelmingly positive. Thanks to scientific progress, most people on earth live longer, healthier, and better than they did centuries or even decades ago.  I believe that AI (including AGI and ASI) can do the same and be a positive force for humanity. I also believe that it is possible to solve the “technical alignment” problem and […]

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arXiv:2407.02700v4 Announce Type: replace-cross Abstract: This paper presents a novel approach for the output range estimation problem in Deep Neural Networks (DNNs) by integrating a Simulated Annealing (SA) algorithm tailored to operate within constrained domains and ensure convergence towards global optima. The method effectively addresses the challenges posed by the lack of local geometric information and the high non-linearity inherent to DNNs, making it applicable to a wide variety of architectures, with a special focus on Residual Networks […]

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arXiv:2602.06139v1 Announce Type: new Abstract: Understanding egocentric videos plays a vital role for embodied intelligence. Recent multi-modal large language models (MLLMs) can accept both visual and audio inputs. However, due to the challenge of obtaining text labels with coherent joint-modality information, whether MLLMs can jointly understand both modalities in egocentric videos remains under-explored. To address this problem, we introduce EgoAVU, a scalable data engine to automatically generate egocentric audio-visual narrations, questions, and answers. EgoAVU enriches human narrations with […]

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How ChatGPT defends against prompt injection and social engineering by constraining risky actions and protecting sensitive data in agent workflows.

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arXiv:2505.13770v2 Announce Type: replace-cross Abstract: Reliable causal inference is essential for making decisions in high-stakes areas like medicine, economics, and public policy. However, it remains unclear whether large language models (LLMs) can handle rigorous and trustworthy statistical causal inference. Current benchmarks usually involve simplified tasks. For example, these tasks might only ask LLMs to identify semantic causal relationships or draw conclusions directly from raw data. As a result, models may overlook important statistical pitfalls, such as Simpson’s paradox […]

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Six months ago I implemented a NumPy environment for generals.io and trained an agent that hit top 20 on human leaderboards. I reached 5k fps with that setup. In the last couple of days I rewrote everything in JAX with help from opus4.5 (here we go again) and got 1.4M FPS on single H200, which is a 300x speedup! I’m confident that with so much more fps going super-human is much more attainable! For those interested in coding […]

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What separates a cryptocurrency that endures for over a decade from the thousands that vanish within their first year? January 18, 2025 marks twelve years since Dash launched as a fork of Bitcoin, making it one of the oldest active blockchain networks still operating with its original vision intact. While data from CoinGecko shows that over 90% of cryptocurrencies launched since 2017 no longer maintain active development or trading volume, Dash continues processing transactions daily across 158 countries. […]

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