mlbwhf@yahoo.com Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.
Source: MIT News – Artificial intelligence
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MIT students designed, built, and tested a jet engine with AI copilots, assessing AI’s usefulness in developing high-performance aerospace systems.
Source: MIT News – Artificial intelligence
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Google Images is turning 25. Here’s a look back at some major milestones — and new ways to explore and create visual content.
Source: AI
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Summary Researcher Dave Kuszmar discovered multiple systemic vulnerabilities that let him bypass LLM safety and obtain dangerous instructions. These exploits worked across nearly all major LLMs revealing an industry-wide security problem. Kuszmar calls for slowing deployment, increasing transparency, and large-scale research into LLM safety before…
Source: IEEE Spectrum
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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. What Anthropic’s latest AI discovery does—and doesn’t—show —James O’Donnell When Anthropic announced last week that it had found a new window…
Source: MIT Technology Review
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Learn how enterprises can manage AI investments in the agentic era by measuring useful work per dollar, improving efficiency, and scaling high-value workflows.
Source: OpenAI News
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The machine that could change the world will be housed in a room that looks like a data center crossed with an ice cream factory. Inside will be some 100 stainless-steel cabinets, each about six feet tall and connected to a supply of liquid helium…
Source: MIT Technology Review
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arXiv:2502.20681v3 Announce Type: replace-cross Abstract: Transformers may exhibit two-stage training dynamics during the real-world training process. For instance, when training GPT-2 on the Counterfact dataset, the answers progress from syntactically incorrect to syntactically correct to semantically correct. However, existing theoretical analyses hardly account for this…
Source: cs.AI updates on arXiv.org
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arXiv:2607.08783v2 Announce Type: replace-cross Abstract: Manifold-valued measurements are prevalent in various machine learning tasks. Recent advances have extended Deep Neural Networks (DNNs) to operate on manifolds, accompanied by normalization techniques tailored to different geometries, collectively referred to as Riemannian normalization. However, most existing Riemannian normalization…
Source: cs.AI updates on arXiv.org
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arXiv:2604.26578v3 Announce Type: replace-cross Abstract: Reusing verification artefacts requires identifying structural and semantic similarities across programs and their specifications. In this paper, we focus on graph construction as a foundational step toward this goal. We present a pipeline that converts imperative programs and their annotations…
Source: cs.AI updates on arXiv.org
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