National Academy of Sciences
PulseAugur coverage of National Academy of Sciences — every cluster mentioning National Academy of Sciences across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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Experts call for new cyber safety engineering discipline to prevent future disasters
A recent Cyber Safety Summit highlighted the urgent need for a dedicated cyber safety engineering discipline to address the growing risks posed by interconnected physical systems. Experts debated accountability for fail…
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STEM evolves to STHEAM, emphasizing humanities for societal challenges
The concept of STEM (Science, Technology, Engineering, and Mathematics) is evolving, with a growing emphasis on integrating humanities and arts. The author proposes STHEAM (Science, Technology, Humanities, Engineering, …
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Cyber threats increasingly target physical infrastructure, posing life-safety risks
A recent Cyber Safety Summit in Washington, D.C., highlighted the escalating threat of cyber-physical risks, where cyber incidents directly impact physical systems and public safety. Leaders from government, engineering…
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Tech entrepreneur uses AI to manage home data migration and smart devices
A tech enthusiast and entrepreneur detailed his experience integrating AI into his home, starting with migrating his digital life to a new MacBook Pro. He utilized Claude Code, an AI assistant, to manage the complex tra…
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Norm Anchors Stabilize LLM Edits, Extending Usable Horizon by 4x
Researchers have developed a new technique called Norm-Anchor Scaling (NAS) to improve the longevity of model edits in large language models. Existing methods for sequential model editing can degrade performance over ti…
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LLMs accelerate neural architecture search with novel delta-based code generation
Researchers are exploring novel methods for Neural Architecture Search (NAS) using Large Language Models (LLMs). One approach, SPARK, aims to improve LLM knowledge integration by explicitly selecting functional factors …
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LLMs aid neural architecture search by generating and refining code for vision models
Researchers have developed a novel framework that utilizes large language models (LLMs) to automate the search for optimal channel configurations in vision models. This approach treats neural architecture search as a co…
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Researchers explore vector quantization for efficient neural network compression
Researchers have developed three techniques for compressing neural network weights using vector quantization (VQ). Their approach uses cosine similarity for assignment and top-1 sampling with a straight-through estimato…