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arXiv:2605.12505v1 Announce Type: new Abstract: Autonomous AI systems generate responsibility gaps: consequential actions that cannot be satisfactorily attributed to developers, operators, or users under existing legal frameworks. The prevailing subject-object dichotomy fails to accommodate entities that exhibit autonomous, goal-directed behavior without recognized consciousness. Given irreducible epistemic uncertainty regarding artificial consciousness and the prospect of high-impact harms, the precautionary principle supports institutional design rather than regulatory inaction. This article advances limited legal personhood as a functional governance instrument for […]

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arXiv:2605.12504v1 Announce Type: new Abstract: We develop conjectures and theorems expressing the idea that the prime sequence exhibits computational irreducibility in the transition from one prime to its successor. Informally, given a prime pp p, no general algorithm can compute the least prime greater than pp p substantially faster than sequentially testing candidates for primality, except possibly on sparse input sets. Our framework proceeds along complementary lines. First, we formalize Prime Successor Irreducibility in a Turing-machine complexity model […]

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Neural models get the hype. But that lightning-fast word suggestion as you type? That’s not a neural model. It’s a lookup table. And it’s beating transformers on the metric that matters. I’ve spent a lot of time thinking about prediction under pressure. When I was working on Indian-language typing for early Kindle devices, we had a problem that no amount of ML enthusiasm could solve: the hardware simply didn’t care about our ambitions. We had roughly 512 MB […]

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In this tutorial, we build a realistic Zero-Trust network simulation by modeling a micro-segmented environment as a directed graph and forcing every request to earn access through continuous verification. We implement a dynamic policy engine that blends ABAC-style permissions with device posture, MFA, path reachability, zone sensitivity, and live risk signals such as anomaly and data-volume indicators. We then operationalize the model through a Flask API and run mixed traffic, including insider-lateral movement and exfiltration attempts, to show […]

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Welcome to the Datasette blog We have a bunch of neat Datasette announcements in the pipeline so we decided it was time the project grew an official blog. I built this using OpenAI Codex desktop, which turns out to have the Markdown session transcript export feature I’ve always wanted. Here’s the session that built the blog. See also issue 179. Tags: ai, datasette, generative-ai, llms, ai-assisted-programming, codex

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By the time a company’s legal team finishes drafting its generative AI acceptable use policy, a meaningful percentage of its engineers, analysts, and product managers have already moved past it. Not deliberately. Not maliciously. Just practically. This is the core dynamic of what the industry now calls shadow AI: the unauthorized, ungoverned use of AI tools across enterprise organizations, running parallel to — and often far ahead of — whatever governance frameworks IT and compliance teams have managed […]

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