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Building a practical path to post-quantum cryptography

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Quantum computing has alternated between breakthrough darling and overhyped promise in technology circles. Its powerful new capabilities come with a threat to break current cryptography, but for business leaders navigating the noise, the signal should be clear: post-quantum cryptography (PQC) is a manageable evolution, not…

Source: MIT Technology Review

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Flock is tightening its rules in response to a growing surveillance backlash

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The police-tech giant Flock is announcing today that it will change officers’ access to its nationwide network of license plate readers, in an apparent effort to quell a growing backlash and win back contracts lost amid concerns about mass surveillance and police abuse. Several changes…

Source: MIT Technology Review

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The Download: kids’ thoughts on AI, and female clones of male mice

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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. How kids feel about AI, in their own words —Jen Swetzoff and Keeley McNamara, the founding editors of Anyway, an independent…

Source: MIT Technology Review

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What’s behind this summer’s heat, and why 2027 could be worse

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This summer has been a scorcher for much of the Northern Hemisphere. June and July marked the hottest two-month stretch in Europe since record-keeping began. The contiguous US endured its hottest month on record in July. South Korea saw its highest-ever recorded temperature.   The heat…

Source: MIT Technology Review

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RedditPersona: A Modular Framework for Community-Conditioned LLM Adaptation from Reddit

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arXiv:2606.06027v2 Announce Type: replace Abstract: Community-conditioned language model adaptation needs choices about data collection, community definition, and evaluation that are currently made independently in each study, making it hard to compare assumptions or reuse artifacts. We present RedditPersona, a modular framework that standardizes these choices:…

Source: cs.AI updates on arXiv.org

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Redistribution-based Cost Inference Improves Sparse Safe Offline RL

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arXiv:2608.12306v1 Announce Type: cross Abstract: Safe offline RL typically assumes access to dense per-step cost annotations, but in practice supervisors provide only trajectory-level stop-feedback: a binary signal at the first unsafe transition, with no per-step attribution. We frame this as a temporal credit assignment problem…

Source: cs.AI updates on arXiv.org

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