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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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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
Hollywood in the 60s and the Good AI Future — Joel Dueck
amai · 2026-05-22 · via Hacker News - Newest: "AI"

I was in a discussion today with other CTOs about how AI is changing our work. It’s apparent that, over the long term, none of us see any technical reason why a frontier AI could not fulfill the responsibilities of most C-level positions, including ours. We’re building the foundations of the systems that will one day replace us. It’s a simple extrapolation: we’re already able to deliver much more, much more quickly — almost too quickly! — by ourselves, without having to hire teams. It seems silly to think that transformation won’t keep spreading.

Many of us, myself included, think that this could actually be great. There is an optimism for the “Star Trek” outcome — abundance, autonomy, and meaningful work by choice — felt by people doing the work now, not just futurists and fiction authors.

But good outcomes from technological displacement have never been the default. Historically, in most cases, capital owners capture the gains and displaced workers absorb the losses.

Enter 1960s Hollywood

In the 1960s, actors and screenwriters faced the same structural problem we are facing with AI. For them it was television. An actor would work in a movie, which would be recorded and later rebroadcast on TV. That is, the new technology (television) was creating new value for work they had already completed — and they were having to compete with their own past work!

Let’s say you get hired to act in a film. Basically, the person hiring you is taking the risk. They’re paying you your salary, and in return, they own that product. So, what SAG [the Screen Actors’ Guild] was saying was, You can play that film anywhere in the world, you can play it in Italy, you can have it dubbed — but when you put it on television, that’s a new revenue stream. Also, the argument was that that is taking work away from other actors. Because if you have this movie on, that time slot is no longer available for working actors.

On the other side, the head of 20th Century Fox [Spyros Skouras], his argument was very simple: Why should I pay you twice for the same job? I’ve already paid you for this job. I own this at this point. And that was basically the position of all of these studio owners. At the beginning of the strike, they were like, We’re not even going to talk about residuals. It’s a nonstarter. And Reagan said, We’re “trying to negotiate for the right to negotiate.” That’s how far apart they were. It was so foreign to these guys that they would have to share their revenues with actors after they’d already paid the actors.

— Wayne Federman, in a 2023 interview for Slate

So the Screen Actors’ Guild — led by Ronald Reagan, a fierce individualist — voted on a strike. The vote went 6,399 to 259 and the strike went forward. The actors gained something previously unthinkable: a continuous cut of all the ongoing value created by their work being used in new technology, and a one-time payout to fund health insurance and a pension that is still active today. (Read more in the 2011 Atlantic article What Reagan Did for Hollywood).

Important to note: the idea of actors being owed ongoing residuals for their work is not a moral axiom of the universe. It was, and is, purely a matter of perspective and opinion. It had to be negotiated for. Today we accept it as the default. But simply going along with industry and tech trends would have forfeited an entire infrastructure of baseline financial security for working performers.

Fast forward

The parallel to tech workers today is tighter than it might seem. AI models are trained on our code, our documentation, our architectural patterns, our websites: all the accumulated and ongoing output of our professional lives. Actors compete against recordings of their own performances; we compete against models trained on our own work.

To be clear: I’m not prescribing strikes and residual payments. I am saying that SAG demonstrated that we don’t have to accept default industry outcomes when rapid tech changes reshape everything. We can envision and champion policies that create better starting defaults for more people. But no one’s going to do it for us — and we can’t do it by acting individually.

We can bring our optimism to bear in envisioning the future we want and in building it. Not just by building good products and systems for individual businesses, but by building good social and legal policies to create a playing field built for humans. The opportunity is here now; it won’t last forever.