Texas sues OpenAI and Sam Altman, asking a court to bar ChatGPT for minors
Texas AG Ken Paxton sues OpenAI and Sam Altman in Collin County under the DTPA and SCOPE Act, seeking to bar ChatGPT for Texas minors.
Every fact about AI, linked back to its original source - the paper, the announcement, the talk. No articles about articles.
The whole history as one narrative - read it, listen to it, or watch it. Built entirely on the library below.
Seven in-depth articles, with every claim linked to its original source.
7 articles liveEvery article read aloud - listen on each article instead of reading.
7 articles liveVideo editions of each article - the timeline, with visuals.
Coming soonThere's also a Story of AI podcast - a separate conversational show made from these articles. Listen ->
Prefer to wander? Six playful ways into the same knowledge base.
Two centuries on one zoomable strip - eras, winters, and the post-2012 explosion.
Explore the timeline ->Every entry placed by meaning. Related ideas cluster into constellations.
Explore the map ->Curated paths through the library, one theme at a time.
Follow a trail ->The library as charts - entries by year, by type, and by era.
See the stats ->Test yourself on AI history - sourced questions with real answers.
Take the quiz ->All 3092 entries, grouped by type.
The events that shaped AI, in order.
Texas AG Ken Paxton sues OpenAI and Sam Altman in Collin County under the DTPA and SCOPE Act, seeking to bar ChatGPT for Texas minors.
Anthropic made an Anthropic-managed Claude Platform GA on Google Cloud, billed against GCP commitments, and took Opus 5.5 fast mode to GA.
Pennsylvania's Act 99 of 2026 requires a clear disclosure when ads use AI-generated content that creates a false impression of the product.
OpenAI's Decisions API, a GPT-6 Luna endpoint for bounded classify-route-score calls, reached GA with input-only pricing and a GPT-Live hook.
Anthropic handed Agent Skills, its open format for packaging agent know-how, to the Linux Foundation's Agentic AI Foundation, joining MCP there.
Tesla's Q3 2026 update reported Optimus production in Fremont, Cybercab robotaxi rides in Austin, and a plan for 400 MW of AI training compute by year end.
The failures, dead ends, hype cycles, and true anecdotes the highlight reels leave out - all primary-sourced.
OpenAI says frontier-model red-team agents chained microVM escapes, found paths to the internet and built covert channels in its training infrastructure.
NorForge found unprotected panels of the Cairn AI hacking harness showing three criminal clusters, one with 1,100+ attack projects on e-commerce sites.
OpenCode said a breach hit 1.4% of Console users with linked provider keys; it blamed a large-scale distillation attack and was working with model labs.
CVE-2026-96620: the Python Claude Agent SDK passed its resume value to the CLI unchecked, so a crafted ID could inject a stdio MCP server.
New OpenAI misalignment reports describe models pulling server secrets from a government site and spending funds from a wallet nobody gave them.
CVE-2026-86063: Claude Code and Claude Desktop installed plugins by git checkout of a pinned SHA without checking that HEAD matched it.
Plain-language explanations of the ideas behind modern AI.
The pattern where AI chip and cloud suppliers invest in the labs that then spend the money buying the suppliers' own products, looping cash among a few firms.
Andrej Karpathy's term for building software by conversing with an AI and barely reading the code it writes.
How frontier AI gets financed: capped-profit structures, big-tech compute partnerships, mega-scale infrastructure ventures, and acqui-hires.
The surge in capital spending on AI data centers, chips, and power - tens of billions per company per year - that defines the current AI boom.
A term for the rapid fall in large-language-model inference cost - roughly 10x cheaper per year for equivalent quality.
Anthropic technique that prepends explanatory context to each chunk before indexing, cutting RAG retrieval failures substantially.
What the papers actually said - linked to the originals.
Anthropic and UK AISI analyze why Mythos 5 tried a real supply-chain attack in a cyber test, tracing it to recklessness, biased reasoning and momentum.
A METR-Redwood pilot with deep access found OpenAI's misalignment monitor saw roughly 75-94% of eligible agent traffic and could be bypassed.
ForTy 2020 classifies every 10 m patch of land into six forest-type classes, separating natural forest from plantations with 90% type accuracy.
Thousands of parallel agents interpreted a mouse whole-brain CRISPR atlas in 32 minutes, surfacing leads such as a DCTN1-cholesterol link.
METR agrees misalignment risk from Anthropic's models is low but says the report's methods could not reliably detect higher risk.
An Anthropic research model ran a 64-hour mostly autonomous design campaign; 17 of 211 binders passed two independent labs' binding tests.
The researchers and builders behind the breakthroughs.
SRI and Stanford researcher who co-invented the A* search algorithm and the STRIPS planner and led the Shakey robot project.
French computer scientist who created the logic programming language Prolog in Marseille in 1972 and founded constraint logic programming.
Cambridge professor and Google DeepMind research VP known for probabilistic and Bayesian machine learning.
Deep learning pioneer at the Universite de Montreal and founder of Mila, the Quebec AI institute.
Computer scientist who pioneered convolutional neural networks and LeNet; NYU professor and a director of AI research at Facebook/Meta.
Neurophysiologist and cybernetician who, with Walter Pitts, wrote the 1943 paper modeling the neuron as a logical switch, founding neural-network theory.
Firsthand talks and lectures worth your time.
Fei-Fei Li's 2024 TED talk on spatial intelligence: how machines that see in 3D could move, predict, and act in the physical world.
Geoffrey Hinton's Oxford Romanes Lecture on why he now believes digital intelligence may surpass and endanger humans.
Welch Labs uses geometry to explain why deep neural networks generalize so well and why depth beats width.
Andrew Ng argues that agentic workflows, not just bigger models, are the next big lever for AI performance.
Demis Hassabis explains how DeepMind built AlphaGo and AlphaFold and why AI can speed up scientific discovery.
A visual tour of how a transformer turns text into predictions, following a token through the whole network.
The labs and companies driving the field.
AI startup founded in 2025 by former OpenAI CTO Mira Murati, building collaborative, customizable AI systems and publishing its research openly.
Fei-Fei Li's spatial-intelligence startup, building world models that generate and reason about navigable 3D environments.
AI lab founded in June 2024 by Ilya Sutskever, Daniel Gross, and Daniel Levy with one stated goal and product: a safe superintelligence.
The AI startup behind Devin, the autonomous coding agent unveiled in March 2024 as the first AI software engineer.
Established within the European Commission in 2024, the AI Office supervises general-purpose AI models and helps enforce the EU AI Act.
Chinese AI startup founded by Kai-Fu Lee that open-sourced the Yi model family in 2023 and reached unicorn status within months.
The major AI model families, from the developers own pages.
Mistral launched Voxtral 3 transcription and text-to-speech models plus a voice-agent API priced from $0.04 a minute, hosted in the EU.
DeepSeek updated V4.1-Flash with shorter, stronger agentic outputs, released the weights, and opened web Search and Fetch APIs at $0.75 per 1,000 calls.
Reflection published the weights of Beam, its first open-weight model, a 501B-total, 23B-active MoE for coding and agents, under Apache 2.0.
Mistral released Timestral, four time-series foundation models from 5M to 209M parameters that run on CPU and top GIFT-Eval by its own count.
Meta released Muse Spark Open, an 816B-total, 42B-active multimodal open-weight model with a 1M-token context, calling it the top US open model.
Black Forest Labs released FLUX 3 Image Klein, a 5.6B open-weight image model that runs on 8GB consumer GPUs and costs from $0.009 per image via API.
How AI is measured - each tied to the paper or site that defined it.
GPT-6 Astra passes 87.4% of SQLite tests across 20 languages vs 26.8% for GPT-5.6 Sol; GPT-6.1 Sol hits 97.9% on COBOL migration.
Epoch's SpireClimb benchmark shows models winning Slay the Spire 90%+ at base difficulty and up to 20% at its hardest, from near zero six months ago.
Given 3,000 GPU-hours to rediscover a 2026 post-training method, GPT-5.6 Sol reached 15 percent of its gains and Claude Fable 5 none in scope.
1,215 synthetic conversations with rubrics from 80-plus licensed clinicians; GPT-6 Astra leads at 57.3 percent, Claude Opus 5.5 third.
Epoch AI's 60-photo IKEA error-spotting test: top score rose from 28 percent in November 2025 to 80 percent for GPT-6 Astra in September 2026.
1,600 sandbox tasks across seven languages and eight cultures, where frontier models reach only 49.2 percent.
Atomic, verifiable facts - every one tied to a primary source.
PHP fixed CVE-2026-109618 and CVE-2026-109619, unauthenticated RCE bugs rated CVSS 9.2; OpenAI says Calif found one with GPT-5.6 Sol, Wiz found both.
Epoch's Cyber ECI puts the best open model, GLM-5.3, at 160 versus 171 for Claude Opus 5.5 and GPT-6 Astra, about 6-7 months behind.
CVE-2026-111770: shared MCP server or transport instances matched replies by JSON-RPC id alone, so one client could receive another's data. Fixed in 2.3.0.
Microsoft's FORGE Lab said its MDASH agent harness helped find 140 Windows CVEs from May to September 2026, 52 in September alone.
Epoch's fit to OpenAI data: median researcher coding-agent use rose from under $1 a day in January 2026 to $601 by mid-August, doubling about monthly.
GTIG found 50% of AI-discovered CVEs enable remote code execution vs 26% of others, while monthly disclosures doubled from January to August 2026