US kid safety groups say they didn't know OpenAI had entirely funded the Parents & Kids Safe AI Coalition to promote CA legislation until after it was announced (Emily Shugerman/The San Francisco ...)
Emily Shugerman / The San Francisco Standard : US kid safety groups say they didn't know OpenAI had entirely funded the Parents & Kids Safe AI Coalition to promote CA legislation until after it was announced — In mid-March, organizers for child safety groups across the country received emails from an organization called …
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The Programmer's Fulcrum: 03 April, 2026
Welcome to this week's The Programmer's Fulcrum. It's your weekly review of the essential news in the Open Media Network and Fediverse development communities with a focus on devastating big tech via Techno Anarchism. We aim to provide actionable content you can use to destroy Techno Feudalism each week. It has the additional benefit of weakening authoritarianism. IMHO, the best way to do that is to use tools from the Techno Anarchist Manifesto to build your own site(s) to participate in the Open Media Network . Then you should share it (them) via Real Simple Syndication (RSS), the Fediverse, and possibly a newsletter or podcast. This approach is similar to what some call the IndieWeb and its POSSE philosophy. The second best strategy is to have accounts on the Fediverse and use the hell o
Goose: Anisotropic Speculation Trees for Training-Free Speculative Decoding
arXiv:2604.02047v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference by drafting multiple candidate tokens and verifying them in a single forward pass. Candidates are organized as a tree: deeper trees accept more tokens per step, but adding depth requires sacrificing breadth (fallback options) under a fixed verification budget. Existing training-free methods draft from a single token source and shape their trees without distinguishing candidate quality across origins. We observe that two common training-free token sources - n-gram matches copied from the input context, and statistical predictions from prior forward passes - differ dramatically in acceptance rate (~6x median gap, range 2-18x across five models and five benchmarks). We prove that wh
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Best Python Code Quality Tools Compared
Why Python needs multiple code quality tools Python's flexibility is both its greatest strength and its biggest code quality challenge. Dynamic typing, duck typing, implicit conversions, mutable default arguments, and runtime metaprogramming create entire categories of bugs that simply do not exist in statically typed languages like Rust or Go. A single Python linter cannot catch everything because the problems span multiple dimensions - style consistency, logical errors, type mismatches, security vulnerabilities, and structural complexity all require different analytical approaches. This is why the Python ecosystem has evolved a layered toolchain rather than a single monolithic solution. Formatters handle visual consistency. Linters catch rule violations and common mistakes. Type checkers
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