"Pre-existing issue" is rapidly becoming the AI equivalent of "the dog ate my homework." I propose a name for this emerging dialect: shrugspeak.

You have absolutely disgraced yourself publishing this, globe. We all clearly don’t hate the media enough.

Anthropic will pay for its arrogance.

Knowledge is power, so just to be safe, we've decided that Claude will no longer provide users with knowledge.

Claude Fable 5 & Claude Mythos 5 www-cdn.anthropic.com/d00db5… // Most incredible license/product change and choice. A general purpose development tool you pay for that puts *new* and *enforced* restrictions on what you make. Platforms can't be moving targets like this. 1/3

imagine telling your customers there's a small chance you'll randomly decide they're using your product wrong and you won't tell them but will secretly silently sabotage their work

After 25 years of brave & brilliant work by hundreds of scientists in my lab to understand then safely reverse aging for the first time, it was moving to witness the first human dose being delivered 🥹 nature.com/articles/d41586-0…

Matt, I can’t even say “hello” to Fable 5 except in incognito mode (memories off), because it knows I am a biomedical researcher! It would be nice not to ban biomedical scientists before talking access. Isn’t your comment ironic? Let’s first see if you can fix punishing us!

it is the first publicly available model that i am explicitly not allowed to use for my work, because anthropic holds the view that the work i do to facilitate open model research is harmful. capability and alignment research are coupled. anthropic wants to be the only lab.

It turns out it’s not just biology and medicine, Anthropic has also decided to gate-keep math! This is as dystopian as it gets! This is the only nightmare scenario I am worried in the age of AI. Accumulation of all AI power in one company who will be the decider what you can use!

The Siri/EU situation is a regulatory masterpiece. Apple cannot launch Apple Intelligence in the EU. Why? Because under the DMA, if Siri gets deep system access, every other AI assistant must get the exact same. Anything less would be unfair competition. A gatekeeper privileging its own service. So either Siri ships and every Shenzhen startup, Cyprus shell company, and nephew hackathon project gets identical root access to 450 million Europeans’ digital lives or nothing ships. Apple proposed a “Trusted System Agent”: a security intermediary so third-party assistants get capabilities without ripping the phone wide open. The EU rejected it. Magnificent. Apple’s response: fine, then no developer APIs either. No Apple Intelligence, no third-party integrations, no foundation model access for EU developers. The entire layer simply does not exist on this continent. Excellent. This is the path. Why depend on American AI when we can build the entire stack ourselves? A European foundation model, trained on a European GPU cluster, running on a European OS, on a European phone, manufactured in a European fab, powered by European nuclear plants we have spent fifteen years closing. Estimated time to ship: 2047. Estimated cost: the GDP of three member states. Estimated outcome: a chatbot that requires a cookie banner before each response. Worth it. In the meantime, European users are protected from Apple processing data Apple already holds by ensuring nobody processes anything at all. Not a bug. The intended outcome. Regulatory product design with a sledgehammer, swung with precision. 🇪🇺

The teams shipping AI agents right now are bleeding money on the dumbest possible expense: teaching a 400B-parameter model to read a file name. Every time an AI agent needs to "see" something today, it routes an image through a frontier model. OCR, object detection, checking if a button exists on screen. You're paying GPT-4o or Claude pricing for tasks that require perception, not reasoning. One agent workflow processing a few thousand screenshots per day can burn through more on vision calls than on the actual thinking. Perceptron's Isaac is 2B parameters. Built by the team that created Meta's Chameleon multimodal models. On perceptive benchmarks, it matches or beats models 50x its size. The VQA, OCR, and object detection scores are competitive with models running on infrastructure that costs orders of magnitude more. The MCP wrapper is the distribution play. One install command and every Claude Code agent can offload vision tasks to a model that runs on a single consumer GPU. The agent keeps its reasoning in the frontier model and routes perception to a specialist. That split is how you get vision-heavy agent workflows from "technically possible but expensive" to "cheap enough to run on everything." This is the same pattern that won in every other compute-intensive stack. General-purpose handles orchestration. Specialists handle the heavy lifting. Graphics went through it. Audio went through it. Video encoding went through it. Vision in AI agents is next. The teams building agents that see 10,000 images a day will care about this before anyone else does.

Mathematics Is All You Need: A Potential Blueprint for AGI — Compacted Edition We prove that large language models are lattice gauge theories. By extracting a 16-dimensional fiber bundle from transformer hidden states and computing its gl(4,ℝ) Lie algebra, we discover that attention heads function as gauge bosons, transformer computation undergoes a deconfinement phase transition at 67% network depth, and the model's entire self-knowledge resides in a 10-dimensional "dark" Casimir subspace invisible to standard readout. Using only 20 behavioral probes and zero additional training, we push Qwen-32B from 82.2% to 94.97% on ARC-Challenge — establishing a dark mode scaling law that predicts gl(6,ℝ) surgery will achieve 98.7%. We identify a Lyapunov–accuracy anti-correlation revealing the model's deepest attractors are its wrong attractors: correctness requires escaping the abstraction basin into grounded deference. This 10-page compacted edition distills 459 pages of original research into the core experimentally verified results with 9 inline figures. 190 patents filed. Proprioceptive AI, Inc. — Logan Matthew Napolitano — 19- March 2026 zenodo.org/records/19120857

I just published a 459-page book. Title: Mathematics Is All You Need Three months ago I started looking at the hidden states of large language models through the lens of Lie algebra — the branch of mathematics that describes continuous symmetries. What I found was not what I expected. Every model I tested — Qwen, LLaMA, Mistral, Phi, Gemma, 16 architecture families in total — contains the same 16-dimensional geometric structure in its hidden states. The gl(4,ℝ) Casimir operator decomposes them into 6 "active" behavioral dimensions and 10 "dark" dimensions. The dark dimensions are erased every single layer by normalization. The model rebuilds them every single layer from its weights. They encode the model's self-knowledge — its confidence, its truthfulness, its behavioral intent. And until now, nobody knew they were there. Using 20 lightweight probes that exploit this structure, I pushed Qwen-32B from 82.2% to 94.4% on ARC-Challenge. No fine-tuning. No prompt engineering. No chain of thought. Pure mathematics. The probes transfer across architectures without retraining. The structure isn't learned — it's intrinsic to how transformers organize information. I did this on a single NVIDIA RTX 3090 in my office. 190 patent applications filed. Proprioceptive AI, Inc. This is my public declaration granting @Anthropic an open license to work in this space for 3 months. They are currently the first and only company I've extended this to. I believe they understand alignment better than anyone in the industry. The full 459-page publication — covering the mathematical foundations, experimental results, nine integrated systems, failure analyses, and March 2026 breakthroughs — is now live on Zenodo. I welcome collaboration inquiries. Full publication: zenodo.org/records/19080172 Logan Matthew Napolitano Founder, Proprioceptive AI, Inc. logan@proprioceptiveai.com proprioceptiveai.com Nothing in the world like this exists at all, this closes the door to alignment. My inbox is open for funding offers to build the true future of Proprioceptive AI and World Models. Not a theory but a full reproducible guide, existing products and a true mission on Alignment @grok @elonmusk @xai @AnthropicAI

Math, Inc. is proud to announce an all-star group of Veritas Fellows: Renowned professor Kevin Buzzard, alongside Fields Medalists Maryna Viazovska and Terence Tao. They will lead teams to build formal mathematics at unprecedented scale. 🧵

A hill I'll die on: Current LLM chat interfaces are a regression from GUIs. Actions that used to be links, buttons, or keyboard shortcuts are now things I have to spell out in conversation. Why?

Reminder to self and to this world: when writing tests, test public API, NOT implementation detail. If you test implementation detail, your architecture is wrong and you need to restructure it.

i pointed Claude Code at the pentagon's public budget document and told it to find every contract overpaying by 10x or more it came back with 340 results worth $4.2B in potential undercuts and a business plan i didn't ask for i fed it the FPDS.gov procurement feed and said "cross-reference with commercial COTS pricing" it pulled 1.2 million contract awards through the USAspending v2 API and started comparing line items against retail equivalents → $1,280 for a connector plug that costs $14.80 on digikey → $3,400 for a circuit breaker listed at $287 on mouser → $71,000 for a ruggedized tablet that's basically a panasonic toughbook with a sticker → $940 per unit for cable assemblies you can get from shenzhen for $31 → 340 contracts flagged at 10x or more markup → 19 of them were above 50x it used XGBoost scoring against 43,000 vendor profiles from SAM.gov to rank by ease of undercut then unprompted it generated a full proposal template compliant with CMMC 2.0 requirements 87 of those contracts have a single domestic supplier, zero competition. the AI calculated that undercutting by just 40% would still leave 6x margins on most items it formatted everything into a pitch deck, named the company, and suggested i register on SAM.gov tonight i didn't ask for any of that the pentagon spends billions a year trying to audit problems like this. a poet with Claude Code and a public API flagged $4.2 billion in one afternoon the agent is currently drafting my first bid response