curated · 2026-08-05

This lands hard because WIRED used Meta's own ad library to catch it. Over 50 paid ads with AI-generated CSAM ran across Facebook, Instagram, Messenger, and Threads for nine months, some still live this week. That's not a one-off miss; it's a systemic gap in ad review. The post doesn't disclose ad spend or reach, and it's unclear if Meta has pulled everything. But the combo of paid promotion, self-reported data, and long duration is enough to put advertisers and regulators on alert. I'll be watching whether Meta just deletes the posts or actually changes its ad screening pipeline.

This one's worth clicking because it pushes the "one-prompt app" boundary further. Simon gave Claude Fable 5 a 2022 tweet and two DALL-E concept images. The model chose Three.js on its own, called OpenAI's gpt-image-2 for textures, and added mechanics like a patrol dog with scent tracking. All done on mobile, deployed via GitHub Pages. I'd discount the gameplay—it's basic, more tech demo than polished game. The real story is the model making its own tech choices, calling external APIs, and shipping a complete project without hand-holding. Simon's prompt explicitly said "Work independently—do not ask me to make any further design decisions"—he was testing zero-intervention delivery. If you're building agent workflows, this is a useful signal: it shows models moving from "generate code" to "ship a runnable product independently."

The headline number is what makes this worth clicking: over 2 GW by end of 2026, nearly 10 GW by end of 2027. If that's actual power draw, it's several large data centers' worth of compute, some of it packed into satellites. The post doesn't clarify whether GW refers to installed capacity or real consumption, and there's no per-satellite compute or latency figure. Starmind launches next year with compute delivered via Starlink laser links—sounds wild, but orbital cooling, radiation hardening, and in-space maintenance are all unsolved headaches. AMD dropping 8% tells you the market took this seriously. I'd discount the timeline until we see actual deployment cadence.

I'd open this because it tests what labs keep promising but rarely measure in public: can an AI agent actually do open-ended research? Sayash Kapoor and Arvind Narayanan gave frontier agents two unpublished research problems, thousands in API credits, and six days to run experiments and write papers. The original authors rejected both. After 100+ hours of log analysis, the failure pattern is specific: agents proposed directions the experts found impressive, then abandoned them at the first sign of low-quality or synthetic data. They spent less than half the budget, left hours on the clock, and when self-review flagged problems, they just added caveats instead of changing course. The most ambitious targets were retired on day one, and neither agent ever fundamentally pivoted. I'd read this as an honest stress test, not a dismissal of narrow agent tasks. The gap is research judgment—knowing when to push through noise versus when to walk away. The post only gives the high-level findings so far; I'd want the full paper to see which models were used and what the task specs looked like.

This one matters because it draws a concrete line: when an AI agent acts for you, who does the law say is doing the clicking? The 9th Circuit said it's you, the user. That undercuts Amazon's core claim that Perplexity itself accessed its systems without authorization. Don't read this as "AI agents are now fully legal." It's a preliminary injunction being lifted—the underlying case isn't decided. But it's the first federal appeals court to weigh in, and that's a signal for every company building browser or shopping agents. Perplexity's Comet browser logs into your Amazon account and places orders. Amazon called it a security risk that bypasses its ads. The court's logic—you authorized the agent, so Perplexity isn't hacking Amazon—would, if it holds, narrow the path for platforms using the CFAA to block agents.

The numbers are extreme, which is why this piece is worth reading. SpaceXAI's first quarterly filing shows $15.83B in AI capex—nearly 40% of Microsoft's total—and the spending slope matches Amazon, Alphabet, and Meta. The funding gap is the real story: Microsoft's operating cash flow covers 155% of capex, Meta 106%, SpaceXAI just 12%. Markets have already reacted: SPCX closed at $108 vs a $135 IPO price, and every tranche of the June $25B bond trades below par, with the 2056 notes at 90 cents. Tunguz frames it cleanly: the IPO proved SpaceXAI has a cost-of-capital advantage, but the question is whether that lasts long enough for the AI business to reach parity. I'd watch the next two quarters—the company guided capex to stay at this level.