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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. Adam/papers/emergent_values_whitepaper.md at master · strangeadvancedmarketing/Adam Ask HN: How do you stop playing 20 questions with your AI coding tools How far can automation and AI support psychotherapy? - @theU GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits A Mac Studio for Local AI — 6 Months Later A History of the Early Years of AI at the University of Edinburgh Why AI Coding Tools Still Feel Stuck on Localhost MSN AI Datacenters Are Becoming Strategic Targets twitter.com Penn Researchers Use AI to Surface Unreported GLP-1 Side Effects in Reddit Posts Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 AI models are terrible at betting on soccer—especially xAI Grok GitHub - xialeistudio/echoic GitHub - HimashaHerath/github-dev-wrapped: AI-powered weekly GitHub activity reports deployed to GitHub Pages GitHub - alejandrobalderas/claude-code-from-source: Architecture, patterns & internals of Anthropic's AI coding agent — reverse-engineered from source maps AI and Tech brief: Ireland ascendant GitHub - Titovilal/context0: Context0 - Never Surrender Training for a Marathon with an AI Coach: What Worked and What Didn't Cyber Pulse: Agentic Intel - Apps on Google Play I Built an AI PR Reviewer That Catches Bugs by Not Looking for Bugs Gen Z workers are so fearful AI will take their job they’re intentionally sabotaging their company’s AI rollout | Fortune How AI Is Reimagining the Game of Golf–For Both Players and Courses GitHub - nattergabriel/reseed: A CLI tool for managing and distributing agent skills across projects Is SVG the final frontier? 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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
'Too Dangerous to Release' Is Becoming AI's New Normal
Nikita Ostrovsky · 2026-04-24 · via Hacker News - Newest: "AI"

On April 16, OpenAI announced GPT-Rosalind, a new AI model targeted at the life sciences. It significantly outperforms their current publicly available models in chemistry and biology tasks, as well as experimental design. As with Anthropic’s Claude Mythos and OpenAI’s GPT-5.4-Cyber, also released this month, the model is not available to the general public—reserved, at least initially, for “qualified customers” through a “trusted access program.” 

The releases signal a new and concerning trend of AI companies deeming their most capable models too powerful to entrust to the general public. “I think frontier developers are restricting access to their most capable models because they are genuinely worried about some of the capabilities these models have,” says Peter Wildeford, head of policy at the AI Policy Network, an advocacy group. 

It is unclear why OpenAI decided to restrict access to GPT-Rosalind in particular. An OpenAI spokesperson said in an email that giving access to trusted partners allows the company to “make more capable systems available sooner to verified users, while still managing risk thoughtfully.”

Who decides? 

The rapid advance of AI capabilities raises the question of whether private companies should be making the increasingly weighty decisions about whether and how potentially dangerous AI models should be built, and who should be allowed to use them. “I think the federal government has a role to play,” says Rep. Mark DeSaulnier, a California Democrat. 

Anthropic’s Mythos release appears to have improved its previously fraught relationship with the White House, which said last week that it had held a “productive and constructive” meeting with Anthropic CEO Dario Amodei. The NSA has also reportedly begun using Claude Mythos. In February, President Trump ordered federal agencies to stop working with the “radical left, woke company,” after a contract dispute with the Pentagon. 

The restrictions on access to the recent series of models were voluntary on the part of Anthropic and OpenAI. But as the risks posed by AI models become more severe and complex, some are calling for stricter external oversight. 

“We don't allow companies to decide how much toxic pollutant they're allowed to put in my child's drinking water—this is the government's decision,” says Connor Leahy, U.S. director of ControlAI, an AI regulation advocacy group. “We can argue [whether] the government is doing a bad job or a good job, but it's about the separation of powers.”

‘Science research and making a bioweapon look very similar’

Dual-use capabilities, such as biological and cybersecurity research, pose a challenge to AI companies. The same tools that help a cybersecurity researcher find and patch vulnerabilities in software can assist a would-be attacker. An AI that helps study viruses could, hypothetically, help a bioterrorist design a more lethal strain. “Cyber defense and cyber offense look very similar,” says Wildeford. “Science research and making a bioweapon look very similar.”

In the past, companies have chosen to restrict these capabilities for everybody. Many chatbots refuse queries on which COVID mutations cause the virus to become more transmissible, for example. While this doesn’t bother the average user, it is a challenge for researchers. “It’s frustrating,” says James Diggans, vice president of policy and biosecurity at Twist Bioscience, a DNA synthesis company. “But I think it’s the right thing to do.”

The recent model releases relax some of these constraints for trusted parties. OpenAI says it grants access to GPT-Rosalind only to organizations with “strong internal controls” that ensure the model will not be misused. Anthropic has partnered with U.S. government agencies and private companies that use Mythos to find and patch cybersecurity vulnerabilities. However, Steph Batalis, research fellow at the Center for Security and Emerging Technology, says that defining “legitimate” researchers is harder outside U.S. institutions, raising equity concerns for international researchers. 

Deciding which models should have restricted access is a delicate balancing act that varies by domain. It’s easy to measure whether an AI model poses a potential cyber threat, says Diggans: “Can they crack existing systems?” Biological research is a more complex, multi-stage process that takes longer than cyberattacks; it’s less clear whether harm would come from a model such as GPT-Rosalind if it were publicly released. “We know that people want to, and do, commit cyber attacks,” Batalis says. “We just don't have that same sample size with the biological risks.” Other domains may become more contentious as AI capabilities continue to advance. Communications campaigns could be seen as propaganda operations in the wrong hands. 

‘Cyber capabilities are going to diffuse’

Open-source models, which can be downloaded and run for free, may change the calculus around AI model restrictions. The capabilities of open-source models have historically lagged proprietary models by three to seven months, according to Epoch AI, a research institute that studies AI progress. This means that, if the trend continues, an AI model with GPT-Rosalind- and Mythos-level capabilities could be publicly available by the end of the year.  “Cyber capabilities are going to diffuse,” the OpenAI spokesperson said. “Defenders need better tools earlier, not later.”

Open-source models could benefit international cyberattackers. In November, Anthropic announced that it had disrupted a Chinese state-sponsored group that was using the company’s paywalled models, by blocking their access to the AI. If similarly capable models are freely available on the open web, this would reduce Western companies’ leverage.

However, some open source developers have previously relied on outputs from leading proprietary systems to help train their models. The recent access restrictions on recent models may slow or stop the diffusion of the most advanced capabilities into open-source models—as long as companies can enforce the restrictions. (Some unauthorized users have reportedly already succeeded in accessing Claude Mythos.)

Whether or not open-source models catch up with the leading proprietary models, Mythos and GPT-Rosalind are the new floor of frontier AI capability—and the growing opportunities and risks posed by AI show no sign of slowing. “I think the government has a strong interest in managing that,” says Wildeford. “I don't really know how you get around the need for government intervention.”