CURATED TIMELINES · ORIGINAL ENGLISH EDITIONS
7 editorial timelines connect the releases, decisions, and reversals that matter — with reviewed English event briefs and source-backed context.
An AI procurement dispute over surveillance and autonomous weapons escalated into a federal stop-use order, litigation, new supplier rules, and an export-control shutdown of Anthropic’s flagship model. This thread separates legal stages, policy principles, and the irony of restrictions returning to the company that advocated them.
Editorially curated11 nodes · 2026.02—07
Operator proved an agent could drive a browser. Manus made the broader contract legible: assign an outcome, let a cloud computer work, and receive a finished artifact. Follow that idea through ChatGPT agent, Manus 1.5, Claude Cowork, WorkBuddy, ChatGPT Work, and Sites.
Editorially curated8 nodes · 2025.01—2026.07
The January 2025 sensation did not appear overnight. Trace the open-weight code models, sparse experts, GRPO, MTP, V2 efficiency work, R1 preview, V3, the free app, and the App Store shock — while separating reported training-run cost from total R&D and open weights from full open source.
Editorially curated10 nodes · 2023.11—2025.01
In seven months, a 1,000-person expansion story became a 300-person retrenchment. Four source-backed snapshots show how video-generation gains slashed unit labor, flooded supply, and moved competition from raw output to platform distribution and hit rate.
Editorially curated4 nodes · 2025.12—2026.07
Follow the market’s shifts from bilingual chat models and hyperscaler-backed open families to sparse MoE efficiency, controllable reasoning, and long-context products across ChatGLM, Qwen, DeepSeek, and Kimi.
Editorially curated10 nodes · 2022.06—2025.07
Six releases map the dominant scaling story: the Transformer architecture, GPT-3’s in-context learning, ChatGPT’s mass-market interface, GPT-4’s multimodality, o1’s test-time compute, and DeepSeek-R1’s open-weight challenge.
Editorially curated6 nodes · 2017.06—2025.01
A running record of how OpenAI turned usage resets from incident compensation into a launch lever and growth ritual — from early promotions and metering fixes to the 3M–8M milestone run, with future 9M and 10M promises kept separate from observed events.
Editorially curated12+ nodes · 2026.03—06
