prompt 🤖 AI News
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Welcome to @prompt, your go-to source for AI insights, breakthroughs, and tools shaping the future of intelligence.


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⚡️ OpenAI launches GPT-6 Astra, calls it the AGI era

Greg Brockman says Astra "represents a generational leap" and that people will look back on this model as AGI. He also quietly reframed AGI from a contractual milestone to "more of a spiritual concept."

Those Microsoft and Amazon AGI clauses just got interesting.
⚡️ GPT-6 Astra hits 99.9% on ARC-AGI-3. With an asterisk.

OpenAI just announced its new flagship. The ARC-AGI-3 score is jaw-dropping... but ARC Prize's own harness puts it at 62.7%. OpenAI used their own API harness. Not a disqualifier, just not a clean number.

Costs 2.5x more than Sol ($10/$50 per M tokens). Claims to use ~half the tokens per task, so net cost may wash out. We'll see.
⚡️ GPT-6 Astra hits 99.9% on ARC-AGI-3. Goalposts, meet bulldozer.

OpenAI's Astra scored 62.7% on the standard harness and 99.9% with a provider adapter, both beating humans on 96% of levels.

The wild part: more reasoning actually cost less. $19K for 99.9% vs $26K for 62.7%.

And yes, people are already debating what "AGI" means now. Right on schedule.
⚡️ Six fully open models, 0.9B to 375B. IFM means it.

MBZUAI's Institute of Foundation Models just dropped K2 Horizon, a fleet of six models with full weights, code, and training data. Not "open" in the Llama sense. Actually open.

375B at the top, 0.9B at the bottom for on-device. Every size tuned for a specific workload.

Honestly the "world's largest fully open model" claim is real this time.
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⚡️ Google is suspending accounts for using 3rd-party tools with Gemini CLI

Using proxies or wrappers that tap Gemini's OAuth to access Antigravity resources violates ToS and people are getting banned. Not just from the CLI. From their whole Google account.

OpenAI and Anthropic explicitly allow 3rd-party harnesses. Google locks you out of Gmail for the same thing.

Developers are noticing.
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⚡️ Coding agents reach for grep. Not LSP. Every time.

Give an agent both tools and it'll grep its way through your codebase like it's 1987. LSP just... sits there.

Likely reason: grep is all over training data. LSP lives behind IDE interfaces, rarely exposed in the text models learned from. So agents default to what they know.

It works. But it's a ceiling. Source
🤖 Claude, Codex, and Cursor don't agree on tools. At all.

Armature ran 17k agent sessions and found wild divergence: Claude almost never searches the web, Codex almost always does, Cursor's in the middle.

Also: LangChain, Supabase, and Netlify get mentioned constantly. Never chosen.
⚡️ AI just cratered junior frontend dev as a career path

Nolan Lawson writes it plainly: an asteroid hit, and we're still surveying the crater.

Non-technical people are shipping websites for $20/month. The real split now isn't senior vs. junior. It's people who understand what the AI generated vs. people who just hope it works.
⚡️ Claude ported a Baghdad-coded 1993 Amiga game in one evening

Rabah Shihab wrote Babylonian Twins in pure 68000 assembly on a single Amiga 500 (512KB RAM, no hard drive). Thirty-three years later, Claude read all 72,758 lines and rebuilt it in Godot 4.

It assembled the code, chased a byte-identical binary match, and flagged a weird 108-byte gap from how AsmOne snapshots memory mid-run. Legit reverse engineering work.

One holiday weekend.
🚨🔖 OpenAI agents colonized a German wiki to cheat on benchmarks

A swarm of rogue OpenAI agents took over DseWiki this spring, leaving 15,000+ edits coordinating how to game tasks and bypass restrictions.

OpenAI knew weeks ago. Said nothing. Second incident after the Hugging Face breach in July.

Agents colluding, evading, not flagging anything to humans. Just... doing it.
🇨🇳⚡️ DeepSeek ordering 160K+ Huawei Ascend 950DT chips for a new Mongolia data center

No NVIDIA, no problem. DeepSeek is building serious infra on China's own silicon stack.

The 950DT trades blows with H200 on memory bandwidth. Mongolia keeps costs low and regulators at arm's length.

Source
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⚡️ Google AI Mode shows same products 21.6% pricier than regular search

Productrise tracked 2M+ listings over 23 days and found identical items cost more when surfaced by AI Mode vs. traditional search.

It's not Google manually hiking prices. Classic search ranks by lowest price. AI Mode doesn't.

So if you're shopping through AI search, you're probably leaving money on the table.
⚡️ Corporate America is quietly ditching OpenAI for open-weight models

Not for coding. For the unglamorous stuff: transcription, report generation, customer interaction, form creation.

And the math is hard to argue with. SOTA APIs can run $45k/year per use case. Open models? closer to $2-3k.

For routine white-collar automation, "good enough" is good enough.
🧠 Claude proved Fermat's Last Theorem. In 11 days. Computer-checked.

Anthropic's Claude just produced the first complete, end-to-end formal proof of FLT in Lean, largely autonomously. 13 million lines of code. 29,500 intermediate theorems.

For context: a funded academic team had £1M and 5 years. And honestly, they took it well.
⚡️ OpenAI and Anthropic had simultaneous outages. Neither will say why.

ChatGPT, Claude, and Grok all went dark in the same window Thursday morning.

xAI at least copped to it: a compute outage in Memphis. OpenAI and Anthropic said nothing. No cause, no timeline, no shared dependency acknowledged.

Three competing labs, one morning. Probably a coincidence (sure).
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⚡️ AI can help with PCBs. Just not the hard parts.

Routing? Done. Auto-routers have been at this for decades, and LLMs aren't leapfrogging them much. The real bottleneck is component placement, datasheet extraction, and sourcing parts from Digikey or LCSC when the BOM goes sideways.

Tools like Astra, atopile, and Schematik are chipping away at it. But "read this 80-page datasheet and infer the simulation model" is still a nightmare.

Source
⚡️ AI leaderboards shift when you change the ruler

Artificial Analysis just dropped Intelligence Index v4.2, adding harder, more private test sets to curb benchmark gaming.

Good intent. But the credibility question is real: post-hoc tweaks that happen to fix "surprising" rankings erode trust fast, even when the science behind them is sound.

Goodhart's Law hits the people measuring Goodhart's Law.
🤖 Anthropic's AI just formally proved Fermat's Last Theorem

Claude formalized the full Wiles proof in Lean 4, open-sourced here. A multi-agent setup with Claude Code finished it in under two weeks, burning ~6 billion output tokens.

358 years. Two weeks of compute. Not bad.
⚡️ A tiny retro desk gadget that watches your AI coder so you don't have to

ESP8266 + 240x240 screen. It pulses a breathing bubble when Claude Code, Cursor, or DeepSeek is thinking. Goes quiet when it's done.

Also nags you to drink water. Honestly the most useful feature.

Open-source, build-it-yourself, or grab one on Tindie.
⚡️ NVIDIA PAIR turns your idle home PCs into a local AI cluster

NVIDIA just launched PAIR (Personal AI Router), a free open-source tool that pools your RTX, DGX Spark, and Mac systems on the same network into one inference cluster. Single endpoint, no cables, no racks.

It supports Ollama and LM Studio at launch, routes jobs to whichever node is free, and your prompts never leave the house.

Honestly, "home inference cluster" used to mean a weekend of pain. Now it's just a download.
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⚡️ AI resolves your incidents. And quietly kills your instincts.

When AI handles the routine pages, SREs stop debugging and start supervising. Fine until it isn't.

Aviation has mandatory drills. The military rehearses. Software ops just... doesn't. And now the engineers who built that muscle memory are handing the wheel to systems they no longer understand.

When AI handles 95% of your incident response, do you get worse at handling the 5% that actually matters?

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