Retraction-Free Optimization over the Stiefel Manifold for the LoRA Fine-Tuning

arXiv:2607.25299v1 Announce Type: cross Abstract: Optimization over the Stiefel manifold plays a significant role in various machine learning tasks. Existing methods either use the retraction operators, requiring costly orthonormalization for large-scale matrices, or employ landing methods that rely on careful step size selection and penalty…

Source: cs.AI updates on arXiv.org

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Siobahn Day Grady Wants Everyone to Be AI Literate

Artificial intelligence is reshaping the skills employers expect from new graduates. In response, universities are scrambling to launch new courses, research centers, and industry partnerships that prepare students for today’s workforce. But building a cutting-edge AI curriculum demands funding and access to industry networks, resources…

Source: IEEE Spectrum

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How a medical database developed at MIT evolved into a global standard of data-sharing

The visionary PhysioNet platform launched 25 years ago, based on a system developed at MIT in the 1970s. It has become one of the most comprehensive biomedical and clinical data repositories in existence.

Source: MIT News – Artificial intelligence

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The Download: a chip talent battle, and deflating AI hype

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Samsung’s chip workers are jumping ship to rival SK Hynix   Lee, an engineer at Samsung’s semiconductor division, used to work late.…

Source: MIT Technology Review

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AI Is Hyper-Scaling Digital Inequality

Artificial intelligence is rapidly becoming part of everyday infrastructure–in some places. It helps write emails and software code, filters job applications, powers recommendation systems, and is increasingly being integrated into education, health care, finance, and public administration. Industry leaders talk about “AI for everyone,” while…

Source: IEEE Spectrum

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From CUDA to MLX: How K-Search Brings Decades of Kernel Expertise to Apple Silicon

Figure 1: CUDA-to-MLX optimization translation map. CUDA optimization knowledge can be translated into architecture-native MLX strategies rather than copied instruction-for-instruction. We face a new epoch in computing. Hardware is changing rapidly — not just faster GPUs, but a growing range of chips from different vendors,…

Source: The Berkeley Artificial Intelligence Research Blog

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The AI Hype Index: Unsexy AI

It feels bad enough when an open letter signed by leading economists warns that AI might steal your job. The fact it may soon be better than you at making dinner? Insult to injury. But that’s exactly what the company 1X promised when it showed…

Source: MIT Technology Review

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A Machine-Learning-Based Gas Lift Optimization Workflow for Unconventional Fields

arXiv:2607.25885v1 Announce Type: cross Abstract: In this paper, we present an automated data-driven workflow using Machine Learning (ML) for gas lift optimization in unconventional fields. This workflow integrates a ML model that accurately forecasts the Gas Lift Performance Curve, and a Bayesian Optimization Framework to…

Source: cs.AI updates on arXiv.org

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