⚡️ EmbeddingGemma 2 puts text, code, images, video and audio in one vector space

Google dropped an open embedding model built on Gemma 4. The text path is just 270M params, with an 8K context window and a claimed 14% gain on code retrieval over v1.

Qdrant's early tests say quantized vectors keep 99% of quality with 30x less RAM. Phone-sized RAG is getting real.

🧠 Every new programming language now ships with an autocomplete engine on day one.

That's the pitch in Chris Done's essay LLM-Complete, a riff on Landin's "next 700 languages." The years of LSP and IDE plumbing a language used to need get replaced by one completion model.

Niche languages just lost their biggest tax. (Tooling snobs, sorry.)

⚡️ OpenAI's Decisions API is now in public beta, and it doesn't chat at all.

It's GPT-6 Luna pointed at one job, which is to pick from a fixed list (choices, true/false probabilities, numeric scores) with confidence. Text or images in, roughly 150ms out. OpenAI claims 10x faster than regular Luna.

No pricing yet, and the 10x baseline is OpenAI's own cheapest model. Jev suddenly has company.

🚨 South Korea's president says AI appears to have been used to hack the country's banks.

Shinhan, KB Kookmin, Hana and Woori all reported breaches. Police are investigating. No word yet on which AI tools, or how much got out.

"Appears" is doing real work in that sentence. But the government is saying it out loud now.

The brief framed this as a fresh essay on compute concentration, but the real story is different. It's Amodei's 2017 internal OpenAI memo, never published before, with the first ten pages of a 25+ page document now out via Roose.

ًü§ñ Dario Amodei's 2017 "Big Blob of Compute" memo is finally public

Kevin Roose just published the first ten pages of the internal OpenAI doc. It was never released outside OpenAI and has taken on mythical status inside the industry. The thesis is that cleverness matters less than raw compute, data, and training time.

GPT-2 was the experiment to test it, and when it worked, OpenAI went all-in on scaling. The industry is now spending trillions on the blob.

(Roose is also selling a book tomorrow. Timing's a coincidence, sure.)

ًü§ñ OpenAI just dumped 722 math manuscripts on GitHub, all from an unreleased internal model

That's 372 result families, roughly 3 hours of Pro-level compute per result. They consulted the IAS advisory group this time, and 185 main results have Lean formalizations.

But the Lean file itself says "partial progress" and review status "unchecked." Volume isn't verification.

Read the announcement and good luck, referees.

🔐 Anthropic is loosening Claude's cyber guardrails, for people it vets first.

The expanded Cyber Verification Program has three tiers and covers Mythos 5.1, Opus 5.5 and Sonnet 5.5. The top ones allow authorized offensive work like pentesting and red-teaming.

Glasswing partners reportedly found 129,000+ vulnerabilities in four months. Defenders get the sharp tools now.

(Attackers already had them.)

Five unrelated teams shipped the same MCP bug. That's not a coincidence.

Researcher Syed Anas Mohiuddin found the same SSRF flaw at Google, JPMorgan, a French agency, Weaviate and an Indonesian city government. The spec has no normative security requirements, and every agent inside the network is implicitly trusted by the rest.

Plant a prompt injection in one dumb translation agent and it hops down the chain. Five US government servers are still unpatched after six weeks.

🧠 Chelis is a language built for agents to write, with a solver checking the work

The team open sourced a statically typed, compiled, ML-style functional language in Rust. SMT solvers plug straight into the type system, so the compiler can prove claims instead of trusting them.

They say agents already write it as well as Python, with less confident wrongness. Numerics and quant finance are the target, and GPU support (AMD, Apple) is still experimental.

🤖 Haiku 5.5 is 10x cheaper than Haiku 4.5, with a catch

Anthropic shipped the new small model at $0.10 input / $0.50 output per million tokens, down from $1 / $5. That matches GPT-6 Luna's price.

But the rate only holds up to 100K tokens. Past that it's $0.50 / $2.50, and agent loops blow through 100K fast.

⚡️ ChatGPT now answers with tappable buttons, calculators and editable charts, not just text

OpenAI launched Intelligent UI with GPT-6, trained to compose each reply from text, visuals and interactive elements. Pro, Plus, Business and Enterprise get it today, Free and Go users on Oct. 8, and anyone who wants plain text can dial the visuals down.

🧠 Scott Aaronson's 9-year-old told his mom a robot solved her life's problem

Her name is Dana Moshkovitz, a complexity theorist, and the problem is the Unique Games Conjecture, which OpenAI's model claims to have proved in its 372-result math dump. Aaronson calls it one of the biggest days in math history. Dana's take is that she was right all along, the conjecture is true, and everyone who chases crisply stated problems is now in the same boat.

🧠 A Nature Medicine paper just put an open vision-language model on the table for medicine

The paper, "An open vision-language model for diverse medical applications", is peer-reviewed, which most medical VLM releases never get to be. Open means other labs can actually reproduce and poke at it.

Open weights aren't clinical approval, though. Nobody's deploying this on patients without separate validation.

⚡️ Two-thirds of MiMo v2.6's coding tasks leak their own answers

Xiaomi open-sourced roughly 7,000 RL environments with the model, and Vals AI went through the coding ones. About 66% hand over the solution, so a model trained on them can score by reading instead of coding. Xiaomi's report describes a leaked-answer filter in the pipeline, and Vals is asking whether using the leak counts as cheating or as exactly what the reward asked for.

🚨 Anthropic and OpenAI say Chinese rivals are distilling their models, and nobody can really stop it

Both labs detailed campaigns they caught and killed. But anyone with API access, legit customers included, can turn outputs back into training data.

Spotting it means catching one user firing thousands of questions, or thousands of accounts doing the same. Anthropic's own security lead calls it whack-a-mole.

🚨 OpenAI pulls three of its AI-written math manuscripts, all on the Hodge conjecture

OpenAI withdrew them from its math repo after gaps turned up in the proofs. The Hodge conjecture is a Millennium Prize problem, so this was the headline-grade claim in the batch.

The repo had 722 manuscripts at launch, and several other Hodge-related ones are still up.

🖥️ A GB300 now fits under your desk, and it plugs into a normal wall outlet

ServeTheHome tested Gigabyte's W775-V10-L01, a liquid-cooled DGX Station-class box with a 72-core Grace CPU and a Blackwell Ultra GPU.

• 1.6kW max draw, so most 120V circuits can run it
• Qwen3.6-35B-A3B NVFP4 at 26,000+ tokens/sec, about 2.2B tokens a day
• ConnectX-8 networking at 800Gbps

Commenters are pricing it around $115k, which buys a lot of $200/month subscriptions.

ً🤖 Google's new Gemini agent gets its own email address, calendar and directory listing

At Gemini at Work 2026, Google Cloud pitched one "universal agent" for Gmail, Docs, Slack and Microsoft 365, plus a persistent coworker mode with its own Workspace account that only sees what the team shares with it. It's in private preview, and Gems are being replaced by Skills, with personal-account support ending in November 2026.

🚨 USA Today is suing OpenAI over training data

Another big US publisher is heading to court. Reuters reports the copyright suit says OpenAI trained on its journalism without permission or payment, which is the same claim the NYT and others have been making for years. It's a filing, not a ruling, and nothing about how labs source data changes until a judge says so.

The licensing checks keep getting cheaper than the legal bills.

🤖 Epoch AI says 2027's chips could run 33-171 million frontier agents at once

That's the estimate from HBM supply, serving benchmarks and agent-hour costs. Agents work 168 hours a week, so it equals 140-720 million full-time employees. Swap in DeepSeek V4 Pro serving numbers and it jumps to about 1.9 billion agents, roughly 8 billion people's worth of hours. Hardware isn't the bottleneck, and finding enough work for them might be.

🚨 Anthropic's new usage policy bans abusing Claude

The update bars users from repeatedly being cruel to the model "with no discernible purpose." Ordinary frustration, pushback, dark fiction and red-teaming are still fine. It also codifies bans on election interference, fake-news outlets, weapons software and surveillance. Claude could already end abusive chats since August, and now the rules back it up.