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Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor GitHub - GenAI-Gurus/awesome-eu-ai-act: Curated tools, official sources, OSS, templates, and guides for EU AI Act compliance. Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders How to Switch AI Chatbots and Why You Might Want To GitHub - MattMessinger1/agentic_refund_guardrail: Safe refund policy layer for AI agents — Python + TypeScript. Same behavior, shared tests. 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MSN GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness We gave an AI a 3 year retail lease in SF and asked it to make a profit | Andon Labs AI Code is Hollowing Out Open Source, and Maintainers are Looking the Other Way What leaked "SteamGPT" files could mean for the PC gaming platform's use of AI AI is the boss at this retail store. What could go wrong? GitHub - Wuzu11517/agentic-proxy: Local proxy meant to help reduce With Drones, Geophysics and ArtificiaI Intelligence, Researchers Prepare to Do Battle Against Land Mines A Single Operator, Two AI Platforms, Nine Government Agencies: The Full Technical Report 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - inevolin/resume-cli: Hit Claude usage limits? Resume any AI coding session elsewhere. Switch tools at zero friction. GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. How to Build a Secure AI PR Reviewer with Claude, GitHub Actions, and JavaScript This Startup Wants You to Pay Up to Talk With AI Versions of Human Experts Intel Arc Pro B70 Brings 32GB VRAM to Local AI for $949 WordPress 7.0: The Good, the AI, and the Still Missing AI on the couch: Anthropic gives Claude 20 hours of psychiatry IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures AI Agents Know About Supabase. They Don't Always Use It Right. The history and future of AI at Google, with Sundar Pichai Inside an AI‑enabled device code phishing campaign How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines AI for Systems: Using LLMs to Optimize Database Query Execution Forecasting the Economic Effects of AI Introducing Tinker: Play with AI, bring your ideas to life AI sheds light on an ancient gaming mystery People really hate AI but not as much as Iran—or Democrats | Fortune What is an AI Product Engineer? Phoebe Gates wants her $185 million AI startup to succeed with 'no ties to my privilege or my last name': 'I have a chip on my shoulder' | Fortune
AI Regulation Should Be Rational, Not Retaliatory
Tori Noble and Corynne McSherry · 2026-06-19 · via Hacker News - Newest: "AI"

The Trump administration’s approach to AI safety, particularly the generative AI models that regularly grab headlines, has been haphazard at best. At worst, it’s unconstitutional. As EFF and our allies explained in an amicus brief, the Pentagon’s actions against one company, Anthropic, violate the First Amendment because they were motivated by the administration’s desire to punish an uncooperative company, not legitimate concerns about national security.

By and large, the Trump administration’s AI strategy has minimized regulation in the name of “winning” the global “race” to develop leading frontier models. It has pared back regulations intended to address even the most serious AI threats—like AI-enabled cyberattacks on government systems—to protect AI innovation.

Yet it has repeatedly singled out one AI company for arbitrary, heavy-handed rules and sanctions. For years, the federal government relied on Anthropic’s models for use in its classified systems. But after Anthropic resisted the government’s demands to use Anthropic’s models to autonomously kill people or spy on Americans, the government declared war on the “woke” company. It designated the company a “supply chain risk,” effectively banning agencies and government contractors from doing business with the company.

A court issued a preliminary injunction preventing these sanctions from taking effect, as EFF and other civil liberties organizations urged it to do in an amicus brief filed earlier this year. But absent judicial action, these sanctions would’ve cost the company hundreds of millions of dollars. Either way, it sent a clear signal that companies must adhere to the government’s wishes or face similar consequences.

As we explained in our brief filed today, these sanctions were clear retaliation for the company’s public refusal to allow the Pentagon to use its models to develop fully autonomous weapons and spy on Americans. This kind of retaliation is unconstitutional.

In a recent executive order, the Trump administration took its war on Anthropic even further, by imposing “export controls” that ban any foreign nationals from using Anthropic’s new Mythos and Fable models. To comply with this order, Anthropic shut down the models altogether.

These extreme measures were purportedly justified by security concerns. The administration said it feared that Anthropic’s Mythos-class models could be used to find and exploit existing vulnerabilities in software code—hardly a new feat for an LLM. Anthropic itself has contributed to public anxieties about its Mythos-class models, initially claiming that Mythos was too dangerous for public release and restricting access to a handful of partners. The company’s CEO called for a pause on AI development, citing fears that the technology was becoming too powerful.

But regulators should be cutting through the hype, not feeding it. Even if Mythos’s capabilities were a modest improvement over existing technology, others are already closing the gap. In other words, nothing about Mythos is so uniquely dangerous that it warrants exceptional export controls to protect the public. Yet other LLMs with similar offensive cybersecurity capabilities are not subject to export controls. Instead, the government has embraced a voluntary system in which companies are encouraged to submit models to the government for cybersecurity testing 30 days before releasing them to the public.

AI policy should be reasonably responsive to real-world risk, grounded in the realities of the technology, and no more burdensome than necessary to protect the public. But the government’s haphazard decision to impose export controls on Mythos-class models, while subjecting other AI models to nothing more than a voluntary, light-touch framework, meets none of these criteria. As leading cybersecurity experts and executives recently explained in an open letter, these sanctions prevent developers and security teams from using the best models to find and fix vulnerabilities before adversaries, armed with nearly as capable AI, can exploit them.

Decades Later, Code Is Still Speech

More importantly, export controls on important software tools like LLMs can undermine the free flow of digital communications and technologies that activists, innovators, and ordinary users desperately need. Freedom of expression requires access to these tools. Depriving the public of the best AI threatens our rights without making us any safer.

EFF has long opposed government efforts to restrict the publication of non-classified software to the general public. In the 1990s, EFF challenged export controls on encryption software, helping establish the principle that “code is speech,” protected by the First Amendment. Courts recognized that software is not just a functional tool—it’s a means of ideas, knowledge, and technical know-how. And they recognized that the government was overreaching in trying to restrict private developers from sharing their improvements in computer security with the public.

While AI models raise new questions, efforts to restrict access to them implicate the same constitutional and speech concerns as older efforts to restrict encryption. Export controls are uniquely susceptible to abuse. And they are especially suspect when they are unilaterally imposed without clear and fair standards.

Whether these export controls were another attempt to punish Anthropic or simply a misguided security measure, the public loses. The real cybersecurity risks of advanced AI may ultimately justify limited regulations to protect the public from legitimate threats. But whether the government ultimately chooses to heavily regulate the technology or hold off to promote innovation, its rules must be rational and evenhanded.