Gul Saeed Khattak (@Ldataengineer) header
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Lead Data Engineer at the University of Glasgow, exploring the future of data and AI through autonomous agents, and agentic workflows

Scotland, United Kingdom
Joined June 2023
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NVIDIA Open-Sources Auto Ontology, a Semantic Layer for AI Agents Your boss asks the AI agent: "What was revenue last quarter?" It answers in 3 seconds. Clean number. Nice chart. But it used the wrong "revenue" column. ๐—ก๐—ผ๐—ฏ๐—ผ๐—ฑ๐˜† ๐—ป๐—ผ๐˜๐—ถ๐—ฐ๐—ฒ๐˜€. That's the problem NVIDIA's new open-source library, Auto Ontology, goes after. Its README puts it plainly: "โ€ฆ๐˜ข ๐˜ณ๐˜ฆ๐˜ท๐˜ฆ๐˜ฏ๐˜ถ๐˜ฆ ๐˜ฎ๐˜ฆ๐˜ต๐˜ณ๐˜ช๐˜ค ๐˜ข๐˜ฏ๐˜ด๐˜ธ๐˜ฆ๐˜ณ๐˜ฆ๐˜ฅ ๐˜ง๐˜ข๐˜ด๐˜ต๐˜ฆ๐˜ณ ๐˜ช๐˜ด ๐˜ธ๐˜ฐ๐˜ณ๐˜ต๐˜ฉ ๐˜ฏ๐˜ฐ๐˜ต๐˜ฉ๐˜ช๐˜ฏ๐˜จ ๐˜ช๐˜ง ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฏ๐˜ถ๐˜ฎ๐˜ฃ๐˜ฆ๐˜ณ ๐˜ช๐˜ด ๐˜ธ๐˜ณ๐˜ฐ๐˜ฏ๐˜จ." ๐—ช๐—ต๐—ฎ๐˜ ๐—ถ๐˜ ๐—ถ๐˜€: A "context layer" that sits between an AI agent and your database. It tells the agent where the data lives, what each field means, and whether to use it. ๐—›๐—ผ๐˜„ ๐—ถ๐˜ ๐˜„๐—ผ๐—ฟ๐—ธ๐˜€, ๐˜€๐˜๐—ฒ๐—ฝ ๐—ฏ๐˜† ๐˜€๐˜๐—ฒ๐—ฝ: โ€ข ๐——๐—ถ๐˜€๐—ฐ๐—ผ๐˜ƒ๐—ฒ๐—ฟ: it reads your database metadata and drafts an ontology, a map of business terms like "active customer" โ€ข ๐—š๐—ฟ๐—ผ๐˜‚๐—ป๐—ฑ: agents use those terms instead of guessing from raw table names โ€ข ๐—ฉ๐—ฎ๐—น๐—ถ๐—ฑ๐—ฎ๐˜๐—ฒ: it checks generated SQL against certified definitions โ€ข ๐—˜๐˜…๐—ฝ๐—ผ๐˜€๐—ฒ: agents reach it through MCP, a CLI or an API โ€ข ๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป: certified corrections go back into the map ๐—™๐—ผ๐—ฟ ๐˜‚๐˜€๐—ฒ๐—ฟ๐˜€: Ask a question, get ๐˜๐—ต๐—ฒ ๐—ฎ๐—ป๐˜€๐˜„๐—ฒ๐—ฟ, ๐˜๐—ต๐—ฒ ๐—ฆ๐—ค๐—Ÿ ๐—ถ๐˜ ๐—ฟ๐—ฎ๐—ป, ๐—ฎ๐—ป๐—ฑ ๐˜๐—ต๐—ฒ ๐—ฟ๐—ผ๐˜„๐˜€. You can check the work, not just trust it. ๐—™๐—ผ๐—ฟ ๐—ฏ๐˜‚๐—ถ๐—น๐—ฑ๐—ฒ๐—ฟ๐˜€: โ€ข Apache 2.0, runs with Docker Compose or Helm โ€ข Works with Databricks, Postgres, Snowflake and DuckDB โ€ข Defaults to NVIDIA's Nemotron models, but ๐—ฎ๐—ป๐˜† ๐—ข๐—ฝ๐—ฒ๐—ป๐—”๐—œ-๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฎ๐˜๐—ถ๐—ฏ๐—น๐—ฒ ๐—ฒ๐—ป๐—ฑ๐—ฝ๐—ผ๐—ถ๐—ป๐˜ ๐˜„๐—ผ๐—ฟ๐—ธ๐˜€ โ€ข The MCP server has ๐Ÿต ๐—ฟ๐—ฒ๐—ฎ๐—ฑ-๐—ผ๐—ป๐—น๐˜† ๐˜๐—ผ๐—ผ๐—น๐˜€. There is deliberately no tool to browse raw tables, so agents must go through the business terms ๐—œ๐˜ ๐—ฏ๐˜‚๐—ถ๐—น๐—ฑ๐˜€ ๐—ผ๐—ป ๐—ฒ๐—ฎ๐—ฟ๐—น๐—ถ๐—ฒ๐—ฟ ๐˜„๐—ผ๐—ฟ๐—ธ: โ€ข Cube and dbt MetricFlow: semantic layers you write by hand in code โ€ข Wren AI: an open semantic layer for AI agents, with a context layer built partly by agents โ€ข Snowflake's Semantic View Autopilot: also drafts semantic models with AI, but only for Snowflake What's different here: ๐—ผ๐—ฝ๐—ฒ๐—ป ๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ, ๐˜„๐—ผ๐—ฟ๐—ธ๐˜€ ๐—ฎ๐—ฐ๐—ฟ๐—ผ๐˜€๐˜€ ๐—ณ๐—ผ๐˜‚๐—ฟ ๐—ฑ๐—ฎ๐˜๐—ฎ๐—ฏ๐—ฎ๐˜€๐—ฒ๐˜€, ๐—ฎ๐—ป๐—ฑ ๐—ฏ๐˜‚๐—ถ๐—น๐˜ ๐—ณ๐—ผ๐—ฟ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€ ๐˜๐—ต๐—ฟ๐—ผ๐˜‚๐—ด๐—ต ๐— ๐—–๐—ฃ. ๐—ง๐—ต๐—ฒ ๐—ต๐—ผ๐—ป๐—ฒ๐˜€๐˜ ๐—ฝ๐—ฎ๐—ฟ๐˜: โ€ข ๐—ง๐—ต๐—ฒ "๐Ÿต๐Ÿฌ% ๐—ณ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ" ๐—ฐ๐—น๐—ฎ๐—ถ๐—บ ๐—ถ๐˜€ ๐—ก๐—ฉ๐—œ๐——๐—œ๐—”'๐˜€ ๐—ผ๐˜„๐—ป ๐˜๐—ฒ๐˜€๐˜๐—ถ๐—ป๐—ด, with no baseline published โ€ข ๐—ก๐—ผ ๐—ฎ๐—ฐ๐—ฐ๐˜‚๐—ฟ๐—ฎ๐—ฐ๐˜† ๐˜€๐—ฐ๐—ผ๐—ฟ๐—ฒ๐˜€ ๐—ฎ๐—ฟ๐—ฒ ๐—ฝ๐˜‚๐—ฏ๐—น๐—ถ๐˜€๐—ต๐—ฒ๐—ฑ. NVIDIA ships an eval harness (BIRD, 1,534 questions) but no results โ€ข That harness was tested with ๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ ๐—ข๐—ฝ๐˜‚๐˜€ ๐Ÿฐ.๐Ÿด, ๐—ป๐—ผ๐˜ ๐—ก๐—ฒ๐—บ๐—ผ๐˜๐—ฟ๐—ผ๐—ป โ€ข ๐—ช๐—ถ๐˜๐—ต๐—ผ๐˜‚๐˜ ๐—›๐—ฎ๐˜€๐—ต๐—ถ๐—–๐—ผ๐—ฟ๐—ฝ ๐—ฉ๐—ฎ๐˜‚๐—น๐˜, ๐—ฑ๐—ฎ๐˜๐—ฎ๐—ฏ๐—ฎ๐˜€๐—ฒ ๐—ฝ๐—ฎ๐˜€๐˜€๐˜„๐—ผ๐—ฟ๐—ฑ๐˜€ ๐—ฎ๐—ฟ๐—ฒ ๐˜€๐˜๐—ผ๐—ฟ๐—ฒ๐—ฑ ๐˜‚๐—ป๐—ฒ๐—ป๐—ฐ๐—ฟ๐˜†๐—ฝ๐˜๐—ฒ๐—ฑ in Postgres (per the README) โ€ข It's young: ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿณ๐Ÿฑ๐Ÿฌ ๐—š๐—ถ๐˜๐—›๐˜‚๐—ฏ ๐˜€๐˜๐—ฎ๐—ฟ๐˜€, and NVIDIA isn't accepting outside contributions ๐—ง๐—ต๐—ฒ ๐—ฏ๐—ถ๐—ด๐—ด๐—ฒ๐—ฟ ๐—ฝ๐—ผ๐—ถ๐—ป๐˜: the hard part of AI analytics isn't writing SQL. ๐—œ๐˜'๐˜€ ๐—ฎ๐—ด๐—ฟ๐—ฒ๐—ฒ๐—ถ๐—ป๐—ด ๐—ผ๐—ป ๐˜„๐—ต๐—ฎ๐˜ ๐˜๐—ต๐—ฒ ๐˜„๐—ผ๐—ฟ๐—ฑ๐˜€ ๐—บ๐—ฒ๐—ฎ๐—ป. GitHub: github.com/NVIDIA/auto-ontolโ€ฆ Links in reply ๐Ÿ‘‡
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๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ-๐— ๐—ฒ๐—บ: ๐—œ ๐—ง๐—ต๐—ผ๐˜‚๐—ด๐—ต๐˜ ๐—œ๐˜ ๐—ช๐—ฎ๐˜€ ๐—๐˜‚๐˜€๐˜ ๐—”๐—ป๐—ผ๐˜๐—ต๐—ฒ๐—ฟ ๐— ๐—ฒ๐—บ๐—ผ๐—ฟ๐˜† ๐—Ÿ๐—ฎ๐˜†๐—ฒ๐—ฟ. ๐—œ๐˜ ๐—œ๐˜€๐—ป'๐˜. When I first saw claude-mem, I thought: another memory layer. We already have mem0, supermemory, Letta and Basic Memory. Then I dug in. ๐—” ๐—ณ๐—ฒ๐˜„ ๐˜๐—ต๐—ถ๐—ป๐—ด๐˜€ ๐—ฐ๐—ฎ๐—บ๐—ฒ ๐˜‚๐—ฝ ๐˜๐—ต๐—ฎ๐˜ ๐—ฒ๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐—ฑ๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—ฒ๐—ฟ ๐˜‚๐˜€๐—ถ๐—ป๐—ด ๐—ฐ๐—ผ๐—ฑ๐—ถ๐—ป๐—ด ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€ ๐˜€๐—ต๐—ผ๐˜‚๐—น๐—ฑ ๐—ธ๐—ป๐—ผ๐˜„. ๐—ง๐—ต๐—ฒ ๐—ฃ๐—ฟ๐—ผ๐—ฏ๐—น๐—ฒ๐—บ ๐—œ๐˜ ๐—ฆ๐—ผ๐—น๐˜ƒ๐—ฒ๐˜€ You spend an hour with Claude Code. It reads your files, runs the tests, finds the bug, fixes it. Then you close the session. Tomorrow it knows ๐—ป๐—ผ๐˜๐—ต๐—ถ๐—ป๐—ด about that hour. Here's the surprise: Claude Code does have its own "auto memory". But its docs say it ๐˜ด๐˜ฌ๐˜ช๐˜ฑ๐˜ด ๐˜ฅ๐˜ฆ๐˜ฃ๐˜ถ๐˜จ๐˜จ๐˜ช๐˜ฏ๐˜จ ๐˜ง๐˜ช๐˜น๐˜ฆ๐˜ด and anything it can work out from the code. ๐—ง๐—ต๐—ฎ๐˜'๐˜€ ๐˜๐—ต๐—ฒ ๐—ด๐—ฎ๐—ฝ ๐—ฐ๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ-๐—บ๐—ฒ๐—บ ๐—ณ๐—ถ๐—น๐—น๐˜€. ๐—›๐—ผ๐˜„ ๐—œ๐˜ ๐—ช๐—ผ๐—ฟ๐—ธ๐˜€ โ€ข ๐—œ๐˜ ๐˜„๐—ฎ๐˜๐—ฐ๐—ต๐—ฒ๐˜€: hooks fire on the agent's own events, like session start, each prompt and each tool call. โ€ข ๐—œ๐˜ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฟ๐—ฒ๐˜€๐˜€๐—ฒ๐˜€: a model turns what happened into short notes. โ€ข ๐—œ๐˜ ๐˜€๐˜๐—ผ๐—ฟ๐—ฒ๐˜€: the notes go into a SQLite database on your machine, with Chroma for meaning-based search. โ€ข ๐—œ๐˜ ๐—ฏ๐—ฟ๐—ถ๐—ป๐—ด๐˜€ ๐˜๐—ต๐—ฒ๐—บ ๐—ฏ๐—ฎ๐—ฐ๐—ธ: at the next session start, relevant notes are added to the context. Search is staged: a short index first (๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿฑ๐Ÿฌโ€“๐Ÿญ๐Ÿฌ๐Ÿฌ ๐˜๐—ผ๐—ธ๐—ฒ๐—ป๐˜€ per result), then a timeline, then full details (๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿฑ๐Ÿฌ๐Ÿฌโ€“๐Ÿญ,๐Ÿฌ๐Ÿฌ๐Ÿฌ ๐˜๐—ผ๐—ธ๐—ฒ๐—ป๐˜€) only for what matters. ๐—ข๐—ป๐—ฒ ๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ, ๐—ฆ๐—ฒ๐˜ƒ๐—ฒ๐—ป ๐—ง๐—ผ๐—ผ๐—น๐˜€ ๐— ๐—ผ๐—ป๐—ฑ๐—ฎ๐˜†: you and the agent spend an hour on a login bug. It reads ๐šŠ๐šž๐š๐š‘/๐š–๐š’๐š๐š๐š•๐šŽ๐š ๐šŠ๐š›๐šŽ.๐š๐šœ, runs the tests, sees 3 failures, finds the token-refresh time was wrong, fixes it. Tests pass. ๐—ง๐˜‚๐—ฒ๐˜€๐—ฑ๐—ฎ๐˜†: new session. You ask: "The auth test is failing again. What did we change last time?" What does the agent know? โ€ข CLAUDE.md: ๐—ผ๐—ป๐—น๐˜† ๐˜„๐—ต๐—ฎ๐˜ ๐˜†๐—ผ๐˜‚ ๐˜„๐—ฟ๐—ผ๐˜๐—ฒ ๐—ถ๐—ป๐˜๐—ผ ๐˜๐—ต๐—ฒ ๐—ณ๐—ถ๐—น๐—ฒ ๐˜†๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐—น๐—ณ. If you didn't write down Monday's fix, it doesn't know. โ€ข Claude Code auto memory: notes about you, your feedback, ongoing project decisions and references. By design it skips debugging fixes, so ๐— ๐—ผ๐—ป๐—ฑ๐—ฎ๐˜†'๐˜€ ๐—ณ๐—ถ๐˜… ๐—ถ๐˜€ ๐—น๐—ถ๐—ธ๐—ฒ๐—น๐˜† ๐—ป๐—ผ๐˜ ๐˜๐—ต๐—ฒ๐—ฟ๐—ฒ. โ€ข mem0: ๐—ป๐—ผ๐˜๐—ต๐—ถ๐—ป๐—ด, unless you're building your own app and your code sends it the conversation. It pulls facts out of what you send. A building block, not a memory plugin for Claude Code. โ€ข supermemory plugin: hooks send your prompt to Supermemory's service (it needs their API key) and add matching memories and a profile of you. ๐—ง๐—ต๐—ฒ ๐—ฐ๐—น๐—ผ๐˜€๐—ฒ๐˜€๐˜ ๐—ฟ๐—ถ๐˜ƒ๐—ฎ๐—น. โ€ข Letta Code: ๐˜†๐—ผ๐˜‚'๐—ฑ ๐—ฏ๐—ฒ ๐˜‚๐˜€๐—ถ๐—ป๐—ด ๐—Ÿ๐—ฒ๐˜๐˜๐—ฎ'๐˜€ ๐—ผ๐˜„๐—ป ๐—ฎ๐—ด๐—ฒ๐—ป๐˜ instead of Claude Code. It rewrites its own memory, skills and prompts, and tracks its memory in git. โ€ข Basic Memory: Markdown files you and the AI both read and edit through MCP. It knows about Monday if a note was written on Monday. โ€ข claude-mem: ๐—ต๐—ผ๐—ผ๐—ธ๐˜€ ๐—ฟ๐—ฒ๐—ฐ๐—ผ๐—ฟ๐—ฑ๐—ฒ๐—ฑ ๐—ฒ๐—ฎ๐—ฐ๐—ต ๐˜€๐˜๐—ฒ๐—ฝ ๐—ผ๐—ป ๐— ๐—ผ๐—ป๐—ฑ๐—ฎ๐˜†: the file read, the test run, the failures, the edit. A model turned that into a note like "๐˜ฃ๐˜ถ๐˜จ๐˜ง๐˜ช๐˜น: ๐˜ต๐˜ฐ๐˜ฌ๐˜ฆ๐˜ฏ ๐˜ณ๐˜ฆ๐˜ง๐˜ณ๐˜ฆ๐˜ด๐˜ฉ ๐˜ช๐˜ฏ ๐˜ฎ๐˜ช๐˜ฅ๐˜ฅ๐˜ญ๐˜ฆ๐˜ธ๐˜ข๐˜ณ๐˜ฆ.๐˜ต๐˜ด ๐˜ถ๐˜ด๐˜ฆ๐˜ฅ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ธ๐˜ณ๐˜ฐ๐˜ฏ๐˜จ ๐˜ฆ๐˜น๐˜ฑ๐˜ช๐˜ณ๐˜บ". On Tuesday it's added at session start, and the agent can search the timeline. ๐—œ๐—ป ๐˜€๐—ต๐—ผ๐—ฟ๐˜: โ€ข mem0 is ๐—ณ๐—ผ๐—ฟ ๐—ฏ๐˜‚๐—ถ๐—น๐—ฑ๐—ถ๐—ป๐—ด ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ผ๐˜„๐—ป ๐—ฎ๐—ฝ๐—ฝ. โ€ข Letta Code ๐—ฟ๐—ฒ๐—ฝ๐—น๐—ฎ๐—ฐ๐—ฒ๐˜€ ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ฎ๐—ด๐—ฒ๐—ป๐˜. โ€ข Basic Memory is ๐—ป๐—ผ๐˜๐—ฒ๐˜€ ๐˜†๐—ผ๐˜‚ ๐—ฐ๐—ฎ๐—ป ๐—ฟ๐—ฒ๐—ฎ๐—ฑ ๐˜†๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐—น๐—ณ. โ€ข supermemory and claude-mem ๐—ฏ๐—ผ๐˜๐—ต ๐—ฝ๐—น๐˜‚๐—ด ๐—ถ๐—ป๐˜๐—ผ ๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ ๐—–๐—ผ๐—ฑ๐—ฒ. supermemory keeps memory in its cloud service. claude-mem records each tool call and keeps the database on your machine. ๐—ช๐—ต๐—ฎ๐˜ ๐—˜๐—น๐˜€๐—ฒ ๐—ง๐—ต๐—ฒ ๐——๐—ถ๐—ด๐—ด๐—ถ๐—ป๐—ด ๐—จ๐—ป๐—ฐ๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐—ฒ๐—ฑ โ€ข ๐—œ๐˜'๐˜€ ๐—ป๐—ผ๐˜ ๐—ท๐˜‚๐˜€๐˜ ๐—ณ๐—ผ๐—ฟ ๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ: install options for OpenCode, T3 Code, Antigravity CLI, Grok Bot, Pi and DeepSeek Harness, plus plugins for Cursor, Codex and Hermes Agent. โ€ข ๐—ฆ๐—ต๐—ฎ๐—ฟ๐—ฒ๐—ฑ ๐—บ๐—ฒ๐—บ๐—ผ๐—ฟ๐˜† ๐—ถ๐˜€ ๐—ผ๐—ฝ๐˜-๐—ถ๐—ป: agents write to the same project memory, but by default a new session only loads notes from the same agent. One setting changes that. โ€ข ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐˜€๐—ฒ๐˜€๐˜€๐—ถ๐—ผ๐—ป๐˜€ ๐—ด๐—ผ ๐˜๐—ผ ๐—ฎ ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น: the installer first offers claude-mem's own hosted note-writer (30-day trial). Your own Anthropic, OpenRouter or Gemini key still sends session data to that provider. ๐—™๐˜‚๐—น๐—น๐˜† ๐—น๐—ผ๐—ฐ๐—ฎ๐—น ๐—บ๐—ฒ๐—ฎ๐—ป๐˜€ ๐—ฝ๐—ผ๐—ถ๐—ป๐˜๐—ถ๐—ป๐—ด ๐—ถ๐˜ ๐—ฎ๐˜ ๐—ฎ ๐˜€๐—ฒ๐—น๐—ณ-๐—ต๐—ผ๐˜€๐˜๐—ฒ๐—ฑ ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น. โ€ข ๐—ฆ๐—ฒ๐—น๐—ณ-๐—ฟ๐—ฒ๐—ฝ๐—ผ๐—ฟ๐˜๐—ฒ๐—ฑ: the README's "๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿญ๐Ÿฌ๐˜… ๐˜๐—ผ๐—ธ๐—ฒ๐—ป ๐˜€๐—ฎ๐˜ƒ๐—ถ๐—ป๐—ด๐˜€" has no independent test. โ€ข ๐—–๐—ผ๐—ฝ๐—ถ๐—น๐—ผ๐˜: listed in the repo description, but the repo has no Copilot-specific files as of today. โ€ข ๐—–๐—ฟ๐˜†๐—ฝ๐˜๐—ผ ๐˜๐—ผ๐—ธ๐—ฒ๐—ป: the README promotes a third-party token, CMEM, that the author has embraced. ๐—ง๐—ต๐—ฒ ๐—ก๐˜‚๐—บ๐—ฏ๐—ฒ๐—ฟ๐˜€ ๐—”๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿญ๐Ÿญ๐Ÿญ.๐Ÿด๐—ธ ๐—š๐—ถ๐˜๐—›๐˜‚๐—ฏ ๐˜€๐˜๐—ฎ๐—ฟ๐˜€ and 9.7k forks as of today. Created August 2025, Apache-2.0, now at v15.9.0. ๐—”๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿต๐Ÿฏ๐—ธ ๐—ป๐—ฝ๐—บ ๐—ฑ๐—ผ๐˜„๐—ป๐—น๐—ผ๐—ฎ๐—ฑ๐˜€ in the last 30 days. ๐—ง๐—ต๐—ฒ ๐—ฏ๐—ถ๐—ด๐—ด๐—ฒ๐—ฟ ๐—ฝ๐—ผ๐—ถ๐—ป๐˜: ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฎ๐˜ฐ๐˜ฅ๐˜ฆ๐˜ญ ๐˜ช๐˜ด ๐˜ฏ๐˜ฐ ๐˜ญ๐˜ฐ๐˜ฏ๐˜จ๐˜ฆ๐˜ณ ๐˜ต๐˜ฉ๐˜ฆ ๐˜ฃ๐˜ฐ๐˜ต๐˜ต๐˜ญ๐˜ฆ๐˜ฏ๐˜ฆ๐˜ค๐˜ฌ. ๐˜ž๐˜ฉ๐˜ข๐˜ต ๐˜ต๐˜ฉ๐˜ฆ ๐˜ข๐˜จ๐˜ฆ๐˜ฏ๐˜ต ๐˜ณ๐˜ฆ๐˜ฎ๐˜ฆ๐˜ฎ๐˜ฃ๐˜ฆ๐˜ณ๐˜ด ๐˜ช๐˜ด. Links in reply ๐Ÿ‘‡ github.com/thedotmack/claudeโ€ฆ
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Gul Saeed Khattak retweeted
๐—ง๐—ต๐—ฒ ๐—™๐˜‚๐—น๐—น ๐—ฆ๐˜๐—ผ๐—ฟ๐˜† ๐—ข๐—ณ ๐—ง๐—ต๐—ฒ $๐Ÿฒ.๐Ÿฏ๐—• ๐—•๐—ถ๐—ป๐—ฎ๐—ป๐—ฐ๐—ฒ ๐—›๐—ฎ๐—ฐ๐—ธ, ๐—™๐—ฟ๐—ผ๐—บ ๐—” ๐—๐—ผ๐—ฏ ๐—ข๐—ณ๐—ณ๐—ฒ๐—ฟ ๐—ง๐—ผ ๐—˜๐—บ๐—ฝ๐˜๐˜† ๐—ช๐—ฎ๐—น๐—น๐—ฒ๐˜๐˜€ The biggest crypto theft in history started with a job interview. A software engineer at Binance, the worldโ€™s largest crypto exchange, had a profile on a job site. It mentioned they worked at Binance. One day a message came in from a โ€œProject Directorโ€ at another company. There was a role. Interested? First came an interview with someone from HR. Then a second round, with the companyโ€™s CEO. None of it was real. Not the HR person, not the CEO, not the company. On the other side were North Korean hackers, and they were about to take $6.3 billion. Hereโ€™s how they did it, based on what Binance has now made public. After the interviews, the โ€œcompanyโ€ sent a take-home assignment. Thatโ€™s normal in tech hiring. You download a small task, work on it, send it back. The engineer downloaded it. Hidden inside was a way into the laptop. From then on, the hackers could use that engineerโ€™s work computer as if they were sitting at it. But the laptop was just the front door. What they really wanted was Binanceโ€™s wallets. In crypto, a wallet is where coins are kept. Whoever controls it can send those coins anywhere, and once theyโ€™re sent, thereโ€™s no bank to call and no โ€œundoโ€ button. Binance holds billions of dollars of its customersโ€™ coins in its wallets. So the hackers went after the engineers who build and run them. They already knew who those people were, because a second trap had been running at the same time. The hackers ran an online ad pushing a fake version of Homebrew, a free tool developers use to install software on their computers. Another Binance engineer clicked the ad and installed the fake one. Binance caught it and removed it. Too late. The hackers had already learned that engineerโ€™s role, and who else at Binance managed the wallets. So now they had a laptop inside Binance and a list of names. Next, they turned Binanceโ€™s own tools against it. Binance gives staff an internal AI tool for their work. From the hacked laptop, the attackers used it to take over two more engineers: one who runs the wallet systems day to day, and one who writes wallet software. Binance hasnโ€™t said exactly how. On one of those computers they found a โ€œcontainer deployment permission token.โ€ In plain English: big companies run their software inside sealed boxes called containers. A deployment token is a digital pass that lets you launch or change what runs in those boxes. Binance says the attacker got into one of these containers, a working part of Binanceโ€™s own system, and from there sent out withdrawals Binance never approved. Thatโ€™s the part that should scare every company. They never stole the walletsโ€™ private keys, the master passwords to crypto wallets. Binance says thereโ€™s no sign any key leaked. They didnโ€™t need one. They got into Binanceโ€™s own machinery and had it send the money out. On Thursday, October 29, they took over a series of Binance wallets and drained them. $6.3 billion. More than four times the old record, the roughly $1.5 billion stolen from Bybit in 2025, also blamed on North Korea. Binance calls it a โ€œmonthslong scheme.โ€ That means all of this happened before a single coin moved: a fake company, a fake HR person, a fake CEO doing a second-round interview, a fake download pushed through ads, and quietly mapping out who did what inside Binance. Some of the money was saved. Part of what was taken was stablecoins, crypto tokens pegged 1:1 to the US dollar. Unlike Bitcoin, theyโ€™re issued by companies, and those companies can freeze them. Tether and Circle froze the stolen ones, and about $2.5 billion has been recovered. Binance shut withdrawals for about 48 hours. It says it has refilled 98% of the stolen coins from its own reserves and that customer funds are safe. Two details stay with me. Binance has a policy that employees in roles that arenโ€™t public-facing shouldnโ€™t have LinkedIn profiles. It had already seen hackers targeting its staff on LinkedIn, and it says it stopped 57 North Korea-linked hacking attempts this year. This one it didnโ€™t stop. And none of it needed a genius hack to get started. It needed a believable job offer and one engineer willing to do a take-home test. Links in First Reply ๐Ÿ‘‡๐Ÿ‘‡ โ€œThis should not have happened,โ€ Binance said. thehackernews.com/2026/10/biโ€ฆ
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Replying to @MassielDuran2
Partly resolves. A recent PR sets a default path per ambiguous group, and you can review it. But a review note on another PR flags your exact failure mode: the join target shown to the SQL prompt can be arbitrary and wrong with no error. Counts over one-to-many joins can also count rows instead of entities. Join paths are where Iโ€™d test hardest.
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Replying to @miniagentstudio
Both, which is the interesting bit. It auto-drafts the ontology from your metadata, then people certify terms before agents rely on them, and certified corrections go back into the map. So the machine drafts and humans own the meaning. Whether that holds up when the schema changes every sprint is the part nobody has shown yet.
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Gul Saeed Khattak retweeted
๐—”๐—น๐—น ๐—ฌ๐—ผ๐˜‚ ๐—ก๐—ฒ๐—ฒ๐—ฑ ๐˜๐—ผ ๐—ž๐—ป๐—ผ๐˜„ ๐—”๐—ฏ๐—ผ๐˜‚๐˜ ๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ'๐˜€ ๐—ก๐—ฒ๐˜„ ๐— ๐—ฒ๐˜€๐˜€๐—ฎ๐—ด๐—ฒ ๐—ง๐—ต๐—ฟ๐—ฒ๐—ฎ๐—ฑ๐˜€ Picture a coding agent two hours into a job. It has opened 40 files, run the tests a dozen times and written a long plan. Now it wants to take one tiny next step. Until now, to do that, it had to send Anthropic's API ๐˜๐—ต๐—ฒ ๐—ฒ๐—ป๐˜๐—ถ๐—ฟ๐—ฒ ๐—ฐ๐—ผ๐—ป๐˜ƒ๐—ฒ๐—ฟ๐˜€๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ด๐—ฎ๐—ถ๐—ป. Every file, every test log, every earlier message. Then again on the next step. And the next. ๐—ข๐—ป ๐—ก๐—ผ๐˜ƒ๐—ฒ๐—บ๐—ฏ๐—ฒ๐—ฟ ๐Ÿฎ, ๐—”๐—ป๐˜๐—ต๐—ฟ๐—ผ๐—ฝ๐—ถ๐—ฐ ๐—ฎ๐—ฑ๐—ฑ๐—ฒ๐—ฑ "๐—บ๐—ฒ๐˜€๐˜€๐—ฎ๐—ด๐—ฒ ๐˜๐—ต๐—ฟ๐—ฒ๐—ฎ๐—ฑ๐˜€", ๐—ฎ๐—ป๐—ฑ ๐˜๐—ต๐—ฎ๐˜ ๐—ฐ๐—ต๐—ฎ๐—ป๐—ด๐—ฒ๐˜€. Here's the difference, with made-up sizes just to show the idea: โŒ ๐—•๐—ฒ๐—ณ๐—ผ๐—ฟ๐—ฒ: ๐—ป๐—ผ ๐˜๐—ต๐—ฟ๐—ฒ๐—ฎ๐—ฑ Turn 1: send the whole conversation (800 KB) Turn 2: send all of it again, plus your new message (802 KB) Turn 3: all of it again, plus the next message (804 KB) โœ… ๐—”๐—ณ๐˜๐—ฒ๐—ฟ: ๐˜„๐—ถ๐˜๐—ต ๐—ฎ ๐˜๐—ต๐—ฟ๐—ฒ๐—ฎ๐—ฑ Turn 1: send the whole conversation once (800 KB) Turn 2: send only your new message and the ID of Claude's last reply (about 2 KB) Turn 3: only the next message and the latest ID (about 2 KB) Anthropic's servers stitch the full conversation back together before Claude reads it. So Claude still sees everything. Your app just stops carrying it back and forth. Those sizes aren't far from real life. Anthropic says the typical request in long Claude Code sessions went from ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿด๐Ÿฌ๐Ÿฌ ๐—ž๐—• ๐˜๐—ผ ๐Ÿญ.๐Ÿด ๐—ž๐—•. ๐—ฆ๐—ผ ๐˜„๐—ต๐—ฎ๐˜ ๐—ต๐—ฎ๐—ฝ๐—ฝ๐—ฒ๐—ป๐˜€ ๐˜๐—ผ ๐˜๐—ถ๐—บ๐—ฒ ๐—ฎ๐—ป๐—ฑ ๐—ฝ๐—ฟ๐—ถ๐—ฐ๐—ฒ? โฑ๏ธ ๐—ง๐—ถ๐—บ๐—ฒ ๐—ด๐—ผ๐—ฒ๐˜€ ๐—ฑ๐—ผ๐˜„๐—ป. Without a thread, the API has to receive, check and tokenize the whole conversation again before Claude can start. With a thread, most of that work covers only the new part. On really big sessions (500K to 1M tokens), Anthropic says Claude started replying ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿฏ๐Ÿฑ% ๐˜€๐—ผ๐—ผ๐—ป๐—ฒ๐—ฟ. ๐Ÿ’ฐ ๐—ฃ๐—ฟ๐—ถ๐—ฐ๐—ฒ ๐˜€๐˜๐—ฎ๐˜†๐˜€ ๐˜๐—ต๐—ฒ ๐˜€๐—ฎ๐—บ๐—ฒ. Claude still reads the full conversation on every turn, so you pay for the same tokens as before. Rate limits don't change either. If you want to cut cost, that's still the job of prompt caching. People get confused about who this affects, so let's split it in two. ๐—œ๐—ณ ๐˜†๐—ผ๐˜‚ ๐—ท๐˜‚๐˜€๐˜ ๐˜‚๐˜€๐—ฒ ๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ ๐—–๐—ผ๐—ฑ๐—ฒ You don't have to do anything. Anthropic says threads are already ๐—ผ๐—ป ๐—ฏ๐˜† ๐—ฑ๐—ฒ๐—ณ๐—ฎ๐˜‚๐—น๐˜ ๐—ณ๐—ผ๐—ฟ ๐—บ๐—ผ๐˜€๐˜ ๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ ๐—–๐—ผ๐—ฑ๐—ฒ ๐˜‚๐˜€๐—ฒ๐—ฟ๐˜€. It all happens in the background. There's no new button, no setting and nothing on screen. You chat and code the way you always have. In long sessions, replies may just start a bit sooner. If you step away for a while, the thread expires ๐Ÿฑ ๐—บ๐—ถ๐—ป๐˜‚๐˜๐—ฒ๐˜€ after the last request. The full history then gets sent again to start a new one. You won't see that happen. That one reply just won't get the speed boost. Anthropic has only talked about Claude Code here. It hasn't said anything about the regular Claude chat app. ๐—œ๐—ณ ๐˜†๐—ผ๐˜‚ ๐—ฏ๐˜‚๐—ถ๐—น๐—ฑ ๐—ผ๐—ป ๐˜๐—ต๐—ฒ ๐—”๐—ฃ๐—œ Here it's the opposite: ๐—ป๐—ผ๐˜๐—ต๐—ถ๐—ป๐—ด ๐—ฐ๐—ต๐—ฎ๐—ป๐—ด๐—ฒ๐˜€ ๐˜‚๐—ป๐—น๐—ฒ๐˜€๐˜€ ๐˜†๐—ผ๐˜‚ ๐˜๐˜‚๐—ฟ๐—ป ๐—ถ๐˜ ๐—ผ๐—ป. The easiest way is the thread helper in Anthropic's SDK. In Python it looks like this: client = anthropic.Anthropic() thread = client.beta.messages.thread( model="claude-opus-5-5", max_tokens=1024, system="You are a coding assistant.") thread.send({"role": "user", "content": "Fix the failing test."}) thread.send({"role": "user", "content": "Now run it again."}) The first send() sends the full conversation and starts the thread. Every send() after that sends only the new message. The helper adds the beta header for you, and if a thread has expired, it sends the full history again on its own. A few things worth knowing before you switch it on: If your chats are only a few thousand tokens long, you probably won't notice much. This is built for long-running agents. ๐—ข๐˜๐—ต๐—ฒ๐—ฟ๐˜€ ๐—ด๐—ผ๐˜ ๐—ต๐—ฒ๐—ฟ๐—ฒ ๐—ณ๐—ถ๐—ฟ๐˜€๐˜, ๐—ถ๐—ป ๐—ฎ ๐—ฑ๐—ถ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐˜ ๐˜„๐—ฎ๐˜† OpenAI's Responses API and Google's Interactions API can already continue a conversation from an ID. ๐—™๐—ผ๐—ฟ ๐—น๐—ผ๐—ป๐—ด-๐—ฟ๐˜‚๐—ป๐—ป๐—ถ๐—ป๐—ด ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€, ๐—ท๐˜‚๐˜€๐˜ ๐—บ๐—ผ๐˜ƒ๐—ถ๐—ป๐—ด ๐˜๐—ต๐—ฒ ๐—ฐ๐—ผ๐—ป๐˜ƒ๐—ฒ๐—ฟ๐˜€๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ฟ๐—ผ๐˜‚๐—ป๐—ฑ ๐—ต๐—ฎ๐˜€ ๐—ฏ๐—ฒ๐—ฐ๐—ผ๐—บ๐—ฒ ๐—ฝ๐—ฎ๐—ฟ๐˜ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐˜„๐—ฎ๐—ถ๐˜. claude.com/resources/articleโ€ฆ
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Fair, I know he was joking, and Iโ€™m a big fan of Matthew, been watching his YouTube for ages. Agree China has serious talent. My point: Abdul El-Sayed never mentioned Chinese mathematicians. He talked about China copying US models, not maths. Maybe I worded it too strongly.
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Fortune (the main story: fake recruiter, interviews, Homebrew, AI tool, token, 98% refilled, $2.5B recovered, 57 attempts, LinkedIn policy, Binanceโ€™s quote) fortune.com/2026/11/03/binanโ€ฆ NBC News (hacked laptop โ†’ container โ†’ withdrawals Binance never approved; Tetherโ€™s freeze) nbcnews.com/business/marketsโ€ฆ Wikipedia, 2026 Binance hack (the date: Thursday, 29 October) en.wikipedia.org/wiki/2026_Bโ€ฆ
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๐—ง๐—ต๐—ฒ ๐—™๐˜‚๐—น๐—น ๐—ฆ๐˜๐—ผ๐—ฟ๐˜† ๐—ข๐—ณ ๐—ง๐—ต๐—ฒ $๐Ÿฒ.๐Ÿฏ๐—• ๐—•๐—ถ๐—ป๐—ฎ๐—ป๐—ฐ๐—ฒ ๐—›๐—ฎ๐—ฐ๐—ธ, ๐—™๐—ฟ๐—ผ๐—บ ๐—” ๐—๐—ผ๐—ฏ ๐—ข๐—ณ๐—ณ๐—ฒ๐—ฟ ๐—ง๐—ผ ๐—˜๐—บ๐—ฝ๐˜๐˜† ๐—ช๐—ฎ๐—น๐—น๐—ฒ๐˜๐˜€ The biggest crypto theft in history started with a job interview. A software engineer at Binance, the worldโ€™s largest crypto exchange, had a profile on a job site. It mentioned they worked at Binance. One day a message came in from a โ€œProject Directorโ€ at another company. There was a role. Interested? First came an interview with someone from HR. Then a second round, with the companyโ€™s CEO. None of it was real. Not the HR person, not the CEO, not the company. On the other side were North Korean hackers, and they were about to take $6.3 billion. Hereโ€™s how they did it, based on what Binance has now made public. After the interviews, the โ€œcompanyโ€ sent a take-home assignment. Thatโ€™s normal in tech hiring. You download a small task, work on it, send it back. The engineer downloaded it. Hidden inside was a way into the laptop. From then on, the hackers could use that engineerโ€™s work computer as if they were sitting at it. But the laptop was just the front door. What they really wanted was Binanceโ€™s wallets. In crypto, a wallet is where coins are kept. Whoever controls it can send those coins anywhere, and once theyโ€™re sent, thereโ€™s no bank to call and no โ€œundoโ€ button. Binance holds billions of dollars of its customersโ€™ coins in its wallets. So the hackers went after the engineers who build and run them. They already knew who those people were, because a second trap had been running at the same time. The hackers ran an online ad pushing a fake version of Homebrew, a free tool developers use to install software on their computers. Another Binance engineer clicked the ad and installed the fake one. Binance caught it and removed it. Too late. The hackers had already learned that engineerโ€™s role, and who else at Binance managed the wallets. So now they had a laptop inside Binance and a list of names. Next, they turned Binanceโ€™s own tools against it. Binance gives staff an internal AI tool for their work. From the hacked laptop, the attackers used it to take over two more engineers: one who runs the wallet systems day to day, and one who writes wallet software. Binance hasnโ€™t said exactly how. On one of those computers they found a โ€œcontainer deployment permission token.โ€ In plain English: big companies run their software inside sealed boxes called containers. A deployment token is a digital pass that lets you launch or change what runs in those boxes. Binance says the attacker got into one of these containers, a working part of Binanceโ€™s own system, and from there sent out withdrawals Binance never approved. Thatโ€™s the part that should scare every company. They never stole the walletsโ€™ private keys, the master passwords to crypto wallets. Binance says thereโ€™s no sign any key leaked. They didnโ€™t need one. They got into Binanceโ€™s own machinery and had it send the money out. On Thursday, October 29, they took over a series of Binance wallets and drained them. $6.3 billion. More than four times the old record, the roughly $1.5 billion stolen from Bybit in 2025, also blamed on North Korea. Binance calls it a โ€œmonthslong scheme.โ€ That means all of this happened before a single coin moved: a fake company, a fake HR person, a fake CEO doing a second-round interview, a fake download pushed through ads, and quietly mapping out who did what inside Binance. Some of the money was saved. Part of what was taken was stablecoins, crypto tokens pegged 1:1 to the US dollar. Unlike Bitcoin, theyโ€™re issued by companies, and those companies can freeze them. Tether and Circle froze the stolen ones, and about $2.5 billion has been recovered. Binance shut withdrawals for about 48 hours. It says it has refilled 98% of the stolen coins from its own reserves and that customer funds are safe. Two details stay with me. Binance has a policy that employees in roles that arenโ€™t public-facing shouldnโ€™t have LinkedIn profiles. It had already seen hackers targeting its staff on LinkedIn, and it says it stopped 57 North Korea-linked hacking attempts this year. This one it didnโ€™t stop. And none of it needed a genius hack to get started. It needed a believable job offer and one engineer willing to do a take-home test. Links in First Reply ๐Ÿ‘‡๐Ÿ‘‡ โ€œThis should not have happened,โ€ Binance said. thehackernews.com/2026/10/biโ€ฆ
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๐—”๐—น๐—น ๐—ฌ๐—ผ๐˜‚ ๐—ก๐—ฒ๐—ฒ๐—ฑ ๐˜๐—ผ ๐—ž๐—ป๐—ผ๐˜„ ๐—”๐—ฏ๐—ผ๐˜‚๐˜ ๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ'๐˜€ ๐—ก๐—ฒ๐˜„ ๐— ๐—ฒ๐˜€๐˜€๐—ฎ๐—ด๐—ฒ ๐—ง๐—ต๐—ฟ๐—ฒ๐—ฎ๐—ฑ๐˜€ Picture a coding agent two hours into a job. It has opened 40 files, run the tests a dozen times and written a long plan. Now it wants to take one tiny next step. Until now, to do that, it had to send Anthropic's API ๐˜๐—ต๐—ฒ ๐—ฒ๐—ป๐˜๐—ถ๐—ฟ๐—ฒ ๐—ฐ๐—ผ๐—ป๐˜ƒ๐—ฒ๐—ฟ๐˜€๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ด๐—ฎ๐—ถ๐—ป. Every file, every test log, every earlier message. Then again on the next step. And the next. ๐—ข๐—ป ๐—ก๐—ผ๐˜ƒ๐—ฒ๐—บ๐—ฏ๐—ฒ๐—ฟ ๐Ÿฎ, ๐—”๐—ป๐˜๐—ต๐—ฟ๐—ผ๐—ฝ๐—ถ๐—ฐ ๐—ฎ๐—ฑ๐—ฑ๐—ฒ๐—ฑ "๐—บ๐—ฒ๐˜€๐˜€๐—ฎ๐—ด๐—ฒ ๐˜๐—ต๐—ฟ๐—ฒ๐—ฎ๐—ฑ๐˜€", ๐—ฎ๐—ป๐—ฑ ๐˜๐—ต๐—ฎ๐˜ ๐—ฐ๐—ต๐—ฎ๐—ป๐—ด๐—ฒ๐˜€. Here's the difference, with made-up sizes just to show the idea: โŒ ๐—•๐—ฒ๐—ณ๐—ผ๐—ฟ๐—ฒ: ๐—ป๐—ผ ๐˜๐—ต๐—ฟ๐—ฒ๐—ฎ๐—ฑ Turn 1: send the whole conversation (800 KB) Turn 2: send all of it again, plus your new message (802 KB) Turn 3: all of it again, plus the next message (804 KB) โœ… ๐—”๐—ณ๐˜๐—ฒ๐—ฟ: ๐˜„๐—ถ๐˜๐—ต ๐—ฎ ๐˜๐—ต๐—ฟ๐—ฒ๐—ฎ๐—ฑ Turn 1: send the whole conversation once (800 KB) Turn 2: send only your new message and the ID of Claude's last reply (about 2 KB) Turn 3: only the next message and the latest ID (about 2 KB) Anthropic's servers stitch the full conversation back together before Claude reads it. So Claude still sees everything. Your app just stops carrying it back and forth. Those sizes aren't far from real life. Anthropic says the typical request in long Claude Code sessions went from ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿด๐Ÿฌ๐Ÿฌ ๐—ž๐—• ๐˜๐—ผ ๐Ÿญ.๐Ÿด ๐—ž๐—•. ๐—ฆ๐—ผ ๐˜„๐—ต๐—ฎ๐˜ ๐—ต๐—ฎ๐—ฝ๐—ฝ๐—ฒ๐—ป๐˜€ ๐˜๐—ผ ๐˜๐—ถ๐—บ๐—ฒ ๐—ฎ๐—ป๐—ฑ ๐—ฝ๐—ฟ๐—ถ๐—ฐ๐—ฒ? โฑ๏ธ ๐—ง๐—ถ๐—บ๐—ฒ ๐—ด๐—ผ๐—ฒ๐˜€ ๐—ฑ๐—ผ๐˜„๐—ป. Without a thread, the API has to receive, check and tokenize the whole conversation again before Claude can start. With a thread, most of that work covers only the new part. On really big sessions (500K to 1M tokens), Anthropic says Claude started replying ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐Ÿฏ๐Ÿฑ% ๐˜€๐—ผ๐—ผ๐—ป๐—ฒ๐—ฟ. ๐Ÿ’ฐ ๐—ฃ๐—ฟ๐—ถ๐—ฐ๐—ฒ ๐˜€๐˜๐—ฎ๐˜†๐˜€ ๐˜๐—ต๐—ฒ ๐˜€๐—ฎ๐—บ๐—ฒ. Claude still reads the full conversation on every turn, so you pay for the same tokens as before. Rate limits don't change either. If you want to cut cost, that's still the job of prompt caching. People get confused about who this affects, so let's split it in two. ๐—œ๐—ณ ๐˜†๐—ผ๐˜‚ ๐—ท๐˜‚๐˜€๐˜ ๐˜‚๐˜€๐—ฒ ๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ ๐—–๐—ผ๐—ฑ๐—ฒ You don't have to do anything. Anthropic says threads are already ๐—ผ๐—ป ๐—ฏ๐˜† ๐—ฑ๐—ฒ๐—ณ๐—ฎ๐˜‚๐—น๐˜ ๐—ณ๐—ผ๐—ฟ ๐—บ๐—ผ๐˜€๐˜ ๐—–๐—น๐—ฎ๐˜‚๐—ฑ๐—ฒ ๐—–๐—ผ๐—ฑ๐—ฒ ๐˜‚๐˜€๐—ฒ๐—ฟ๐˜€. It all happens in the background. There's no new button, no setting and nothing on screen. You chat and code the way you always have. In long sessions, replies may just start a bit sooner. If you step away for a while, the thread expires ๐Ÿฑ ๐—บ๐—ถ๐—ป๐˜‚๐˜๐—ฒ๐˜€ after the last request. The full history then gets sent again to start a new one. You won't see that happen. That one reply just won't get the speed boost. Anthropic has only talked about Claude Code here. It hasn't said anything about the regular Claude chat app. ๐—œ๐—ณ ๐˜†๐—ผ๐˜‚ ๐—ฏ๐˜‚๐—ถ๐—น๐—ฑ ๐—ผ๐—ป ๐˜๐—ต๐—ฒ ๐—”๐—ฃ๐—œ Here it's the opposite: ๐—ป๐—ผ๐˜๐—ต๐—ถ๐—ป๐—ด ๐—ฐ๐—ต๐—ฎ๐—ป๐—ด๐—ฒ๐˜€ ๐˜‚๐—ป๐—น๐—ฒ๐˜€๐˜€ ๐˜†๐—ผ๐˜‚ ๐˜๐˜‚๐—ฟ๐—ป ๐—ถ๐˜ ๐—ผ๐—ป. The easiest way is the thread helper in Anthropic's SDK. In Python it looks like this: client = anthropic.Anthropic() thread = client.beta.messages.thread( model="claude-opus-5-5", max_tokens=1024, system="You are a coding assistant.") thread.send({"role": "user", "content": "Fix the failing test."}) thread.send({"role": "user", "content": "Now run it again."}) The first send() sends the full conversation and starts the thread. Every send() after that sends only the new message. The helper adds the beta header for you, and if a thread has expired, it sends the full history again on its own. A few things worth knowing before you switch it on: If your chats are only a few thousand tokens long, you probably won't notice much. This is built for long-running agents. ๐—ข๐˜๐—ต๐—ฒ๐—ฟ๐˜€ ๐—ด๐—ผ๐˜ ๐—ต๐—ฒ๐—ฟ๐—ฒ ๐—ณ๐—ถ๐—ฟ๐˜€๐˜, ๐—ถ๐—ป ๐—ฎ ๐—ฑ๐—ถ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐˜ ๐˜„๐—ฎ๐˜† OpenAI's Responses API and Google's Interactions API can already continue a conversation from an ID. ๐—™๐—ผ๐—ฟ ๐—น๐—ผ๐—ป๐—ด-๐—ฟ๐˜‚๐—ป๐—ป๐—ถ๐—ป๐—ด ๐—ฎ๐—ด๐—ฒ๐—ป๐˜๐˜€, ๐—ท๐˜‚๐˜€๐˜ ๐—บ๐—ผ๐˜ƒ๐—ถ๐—ป๐—ด ๐˜๐—ต๐—ฒ ๐—ฐ๐—ผ๐—ป๐˜ƒ๐—ฒ๐—ฟ๐˜€๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ฟ๐—ผ๐˜‚๐—ป๐—ฑ ๐—ต๐—ฎ๐˜€ ๐—ฏ๐—ฒ๐—ฐ๐—ผ๐—บ๐—ฒ ๐—ฝ๐—ฎ๐—ฟ๐˜ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐˜„๐—ฎ๐—ถ๐˜. claude.com/resources/articleโ€ฆ
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Gul Saeed Khattak retweeted
Saw this and wondered why Elon still works like this when he doesn't need to. I got the answer pretty quickly. Tbh a yacht is fun for a week. After that it's the same sea every morning. Some might disagree , but that is fine . Most of us think the point of money is to stop working. But rest only feels good when there's work around it. Take the work away and relaxing becomes its own kind of boredom. What doesn't get boring is building something nobody has built before. You never really finish it, so it keeps you hooked for years. If Elon had cashed out and moved onto a boat, he wouldn't be Elon, and none of us would be talking about his 3am office nights. People with lots of money and nothing to build often drift into bad habits. People deep in building something rarely have time for them. On a much smaller scale, my best late nights are the ones spent building something. It feels more like rest than any day off.
An employee who worked closely with Elon Musk for four years revealed that he had seen Elon working in the office countless times at 1, 2, even 3 a.m. Elon works every waking hour. He doesnโ€™t go out for lunch or dinner. He mostly has his food brought into meetings and eats while the meeting continues. As the richest person on the planet, he could be anywhere in the world, relaxing on a yacht and enjoying his wealth. Instead, he keeps showing up at the office, working late, and giving his precious time to building a better future for humanity. Huge respect for Elon. The dedication he puts into building a better future deserve far more recognition.
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Gul Saeed Khattak retweeted
๐—ก๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ฎ'๐˜€ ๐Ÿฑ๐Ÿญ% ๐—ฅ๐˜‚๐—น๐—ฒ: ๐—ช๐—ต๐—ฎ๐˜ ๐—œ๐˜ ๐—š๐—ถ๐˜ƒ๐—ฒ๐˜€ ๐—ฌ๐—ผ๐˜‚ ๐—”๐—ป๐—ฑ ๐—ช๐—ต๐—ฎ๐˜ ๐—œ๐˜ ๐——๐—ผ๐—ฒ๐˜€๐—ป'๐˜ Picture a data centre in Singapore. Racks full of Nvidia chips. Its biggest clients are Chinese AI companies that can't buy those chips at home, so they rent them. ๐—ง๐—ต๐—ฒ ๐—จ๐—ป๐—ฑ๐—ฒ๐—ฟ๐—น๐˜†๐—ถ๐—ป๐—ด ๐—œ๐—ฑ๐—ฒ๐—ฎ Compute is a physical thing, but access to it isn't. You can stop a box at a border. It's much harder to stop someone logging in to a box in another country. So there are two doors: โ€ข ๐—•๐˜‚๐˜†๐—ถ๐—ป๐—ด: export controls, plus Nvidia's "white list", which per the FT more than halved approved Asian buyers this year. โ€ข ๐—ฅ๐—ฒ๐—ป๐˜๐—ถ๐—ป๐—ด: Chinese companies leasing GPUs in overseas data centres, including for model training. Close the first door and traffic moves to the second. ๐—ง๐—ต๐—ถ๐˜€ ๐—ฟ๐˜‚๐—น๐—ฒ ๐—ถ๐˜€ ๐—ฎ ๐˜ƒ๐—ฎ๐—น๐˜ƒ๐—ฒ ๐—ผ๐—ป ๐˜๐—ต๐—ฒ ๐˜€๐—ฒ๐—ฐ๐—ผ๐—ป๐—ฑ ๐—ฑ๐—ผ๐—ผ๐—ฟ. ๐—”๐—ป ๐—”๐—ป๐—ฎ๐—น๐—ผ๐—ด๐˜† It's a bit like a landlord telling a building manager: no more than 49% of tenants from one place. Not a law. A lease condition, enforced by whoever signs the lease. ๐—ก๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ฎ ๐—ป๐—ผ๐˜„ ๐˜„๐—ฎ๐—ป๐˜๐˜€ ๐˜๐—ต๐—ฎ๐˜ ๐˜๐—ผ ๐—ฐ๐—ต๐—ฎ๐—ป๐—ด๐—ฒ. ๐—ช๐—ต๐—ฎ๐˜ ๐—›๐—ฎ๐—ฝ๐—ฝ๐—ฒ๐—ป๐—ฒ๐—ฑ According to the Financial Times (five people familiar with the matter), Nvidia has told cloud providers that ๐—ฎ๐˜ ๐—น๐—ฒ๐—ฎ๐˜€๐˜ ๐Ÿฑ๐Ÿญ% of their services must go to non-Chinese companies. There was no such limit before. โ€ข ๐—ก๐—ผ ๐—ฝ๐—ฎ๐—ฝ๐—ฒ๐—ฟ๐˜„๐—ผ๐—ฟ๐—ธ: the instruction was given verbally, through Nvidia's sales and regional teams. โ€ข ๐—ช๐—ผ๐—ฟ๐—น๐—ฑ๐˜„๐—ถ๐—ฑ๐—ฒ: it applies to clients globally, not only in Asia (two people told the FT). โ€ข ๐—ก๐—ฒ๐˜„ ๐—ฑ๐—ฒ๐—ฎ๐—น๐˜€ ๐—ผ๐—ป๐—น๐˜†: existing leases are not affected. โ€ข ๐—ฆ๐—ถ๐—ป๐—ฐ๐—ฒ ๐˜๐—ต๐—ฒ ๐˜€๐˜‚๐—บ๐—บ๐—ฒ๐—ฟ: two people said Nvidia did it pre-emptively, to cut criticism from US lawmakers. ๐—ช๐—ต๐˜† ๐—ฅ๐—ฒ๐—ป๐˜๐—ถ๐—ป๐—ด ๐— ๐—ฎ๐˜๐˜๐—ฒ๐—ฟ๐˜€ US export rules mostly control where chips are shipped. Renting them in a data centre abroad has been the gap. Many Chinese groups used overseas leases for heavy AI work, including model training. Nvidia had already tightened the front door. This year it built a "white list" of approved Asian buyers and ๐—บ๐—ผ๐—ฟ๐—ฒ ๐˜๐—ต๐—ฎ๐—ป ๐—ต๐—ฎ๐—น๐˜ƒ๐—ฒ๐—ฑ it, per the FT. That pushed more Chinese firms toward renting. This new rule goes after ๐˜๐—ต๐—ฒ ๐—ฟ๐—ฒ๐—ป๐˜๐—ถ๐—ป๐—ด. ๐—ช๐—ต๐—ฎ๐˜ ๐—œ๐˜ ๐——๐—ผ๐—ฒ๐˜€ ๐—ง๐—ผ ๐—ฃ๐—ฟ๐—ถ๐—ฐ๐—ฒ๐˜€ A rack of B300 chips sells for ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ $๐Ÿฒ๐Ÿฌ๐Ÿฌ,๐Ÿฌ๐Ÿฌ๐Ÿฌ internationally. One person told the FT a rack fetched ๐—ฅ๐—บ๐—ฏ๐Ÿญ๐Ÿด.๐Ÿฑ๐—บ๐—ป (๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ $๐Ÿฎ.๐Ÿด๐—บ๐—ป) in China last month. That is ๐—ฟ๐—ผ๐˜‚๐—ด๐—ต๐—น๐˜† ๐Ÿฐ.๐Ÿณ ๐˜๐—ถ๐—บ๐—ฒ๐˜€ the price. The B300 can't legally be sold in China. ๐—™๐—ผ๐—ฟ ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ฃ๐—ฟ๐—ผ๐˜ƒ๐—ถ๐—ฑ๐—ฒ๐—ฟ๐˜€ Chinese tech groups are the biggest clients for data centres in places like south-east Asia. A Singapore-based provider told the FT it is hard to find enough non-Chinese clients outside the US. Providers that can't find them may have to ๐˜€๐—ต๐—ฟ๐—ถ๐—ป๐—ธ. New contracts only. ๐—ง๐—ต๐—ฒ ๐— ๐—ฎ๐—ฝ ๐—ข๐—ณ ๐—–๐—ต๐—ถ๐—ป๐—ฎ ๐—–๐—ผ๐—บ๐—ฝ๐˜‚๐˜๐—ฒ ๐—–๐—ผ๐—ป๐˜๐—ฟ๐—ผ๐—น๐˜€, ๐—ข๐—ป๐—ฒ ๐—Ÿ๐—ถ๐—ป๐—ฒ ๐—˜๐—ฎ๐—ฐ๐—ต โ€ข ๐—จ๐—ฆ ๐—ฒ๐˜…๐—ฝ๐—ผ๐—ฟ๐˜ ๐—ฐ๐—ผ๐—ป๐˜๐—ฟ๐—ผ๐—น๐˜€: block shipping top chips like the B300 to China. โ€ข ๐—•๐—œ๐—ฆ ๐—ฟ๐˜‚๐—น๐—ฒ (๐—๐—ฎ๐—ป๐˜‚๐—ฎ๐—ฟ๐˜†): license applicants must list remote cloud users in China and other listed countries. โ€ข ๐—•๐—œ๐—ฆ ๐—ด๐˜‚๐—ถ๐—ฑ๐—ฎ๐—ป๐—ฐ๐—ฒ (๐— ๐—ฎ๐˜† ๐Ÿฏ๐Ÿญ): a license is needed for advanced chips going to companies headquartered in China or Macau, wherever they are. โ€ข ๐—ก๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ฎ'๐˜€ ๐˜„๐—ต๐—ถ๐˜๐—ฒ ๐—น๐—ถ๐˜€๐˜ (๐˜๐—ต๐—ถ๐˜€ ๐˜†๐—ฒ๐—ฎ๐—ฟ): approved Asian buyers more than halved, per the FT. โ€ข ๐—ฅ๐—ฒ๐—บ๐—ผ๐˜๐—ฒ ๐—”๐—ฐ๐—ฐ๐—ฒ๐˜€๐˜€ ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† ๐—”๐—ฐ๐˜: passed the House 369-22 in January; sitting with the Senate Banking Committee. โ€ข ๐—ก๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ฎ'๐˜€ ๐Ÿฑ๐Ÿญ% ๐—ฟ๐˜‚๐—น๐—ฒ (๐—ป๐—ผ๐˜„): aimed at the cloud provider's customer mix, not the chip. ๐—ช๐—ต๐—ฒ๐—ฟ๐—ฒ ๐—ง๐—ต๐—ถ๐˜€ ๐—™๐—ถ๐˜๐˜€ Government rules set the floor. Nvidia is adding its own layer on top, so lawmakers have less to criticise (two people told the FT that was the motive). ๐—ช๐—ต๐—ผ ๐—™๐—ฒ๐—ฒ๐—น๐˜€ ๐—œ๐˜ โ€ข ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ฝ๐—ฟ๐—ผ๐˜ƒ๐—ถ๐—ฑ๐—ฒ๐—ฟ๐˜€ ๐—ถ๐—ป ๐˜€๐—ผ๐˜‚๐˜๐—ต-๐—ฒ๐—ฎ๐˜€๐˜ ๐—”๐˜€๐—ถ๐—ฎ: Chinese tech groups are their biggest clients. โ€ข ๐—–๐—ต๐—ถ๐—ป๐—ฒ๐˜€๐—ฒ ๐—”๐—œ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€: already paying a premium. A B300 rack, ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ $๐Ÿฒ๐Ÿฌ๐Ÿฌ๐—ธ abroad, reportedly fetched $๐Ÿฎ.๐Ÿด๐—บ๐—ป in China last month (one deal). ๐—ง๐—ต๐—ฒ ๐—ฏ๐—ถ๐—ด๐—ด๐—ฒ๐—ฟ ๐—ฝ๐—ผ๐—ถ๐—ป๐˜: ๐˜ต๐˜ฉ๐˜ฆ ๐˜ค๐˜ฉ๐˜ช๐˜ฑ ๐˜ธ๐˜ข๐˜ณ ๐˜ช๐˜ด ๐˜ฎ๐˜ฐ๐˜ท๐˜ช๐˜ฏ๐˜จ ๐˜ง๐˜ณ๐˜ฐ๐˜ฎ ๐˜ธ๐˜ฉ๐˜ฐ ๐˜ค๐˜ข๐˜ฏ ๐˜ฃ๐˜ถ๐˜บ ๐˜ค๐˜ฉ๐˜ช๐˜ฑ๐˜ด ๐˜ต๐˜ฐ ๐˜ธ๐˜ฉ๐˜ฐ ๐˜ค๐˜ข๐˜ฏ ๐˜ณ๐˜ฆ๐˜ฏ๐˜ต ๐˜ต๐˜ฉ๐˜ฆ๐˜ฎ. FT (original report): ft.com/content/1902df70-1380โ€ฆ Links in reply ๐Ÿ‘‡
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Gul Saeed Khattak retweeted
Who is this reply even for? Saw a reply today under my NVIDIA auto-ontology repo post today . It just said "@bot save this". I assumed it was a joke, so I looked it up. @bot is xAI's Grok Bot, an agent app they launched in August 2026. You tag it under a post and the post goes to your own agent, which runs on its own computer in the cloud all day. So that reply wasn't really for the person who shared the repo. It was for someone's private assistant, left out in public where the rest of us could read it. Feels a bit like leaving a note for your cleaner on a stranger's front door. I get why people do it though. I have hundreds of bookmarks I've never opened. Every time I save something I tell myself I'll read it later, and I don't. At least an agent might actually go through the list. I read that repo properly because I'm building an ontology layer on top of a lineage graph at work. I doubt most people saving it will open the README. Their bots probably will. Still can't decide how I feel about that.
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Replying to @MatthewBerman
"Spoofing our models" โ‰  "China has no good mathematicians."
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Replying to @paarangatrai
The $249 Vercel figure assumes both vCPUs are busy 100% of the month. Here's what I mean: Vercel bills CPU only while it's working, and memory the whole time. For 2 vCPU / 4 GB over a month: โ€ข 100% busy: $187 CPU + $62 memory = $249 โ€ข 10% busy: $19 CPU + $62 memory = ~$81 So at 10% the gap vs your $4.76 goes from ~52x to ~17x. Still a big win, just a different headline. What CPU use do your agent sandboxes actually average? 5%? 20%? That one number decides the real gap.
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Replying to @MatthewBerman
Matthew, feels like you are putting words in his mouth here. Thatโ€™s not what he said.
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Replying to @MatthewBerman
Bit of a stretch, Matthew. Saying China relies on US models isnโ€™t the same as saying they donโ€™t have good mathematicians. Thereโ€™s an argument to challenge here, but thatโ€™s not what he said ???? !!!
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๐—ก๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ฎ'๐˜€ ๐Ÿฑ๐Ÿญ% ๐—ฅ๐˜‚๐—น๐—ฒ: ๐—ช๐—ต๐—ฎ๐˜ ๐—œ๐˜ ๐—š๐—ถ๐˜ƒ๐—ฒ๐˜€ ๐—ฌ๐—ผ๐˜‚ ๐—”๐—ป๐—ฑ ๐—ช๐—ต๐—ฎ๐˜ ๐—œ๐˜ ๐——๐—ผ๐—ฒ๐˜€๐—ป'๐˜ Picture a data centre in Singapore. Racks full of Nvidia chips. Its biggest clients are Chinese AI companies that can't buy those chips at home, so they rent them. ๐—ง๐—ต๐—ฒ ๐—จ๐—ป๐—ฑ๐—ฒ๐—ฟ๐—น๐˜†๐—ถ๐—ป๐—ด ๐—œ๐—ฑ๐—ฒ๐—ฎ Compute is a physical thing, but access to it isn't. You can stop a box at a border. It's much harder to stop someone logging in to a box in another country. So there are two doors: โ€ข ๐—•๐˜‚๐˜†๐—ถ๐—ป๐—ด: export controls, plus Nvidia's "white list", which per the FT more than halved approved Asian buyers this year. โ€ข ๐—ฅ๐—ฒ๐—ป๐˜๐—ถ๐—ป๐—ด: Chinese companies leasing GPUs in overseas data centres, including for model training. Close the first door and traffic moves to the second. ๐—ง๐—ต๐—ถ๐˜€ ๐—ฟ๐˜‚๐—น๐—ฒ ๐—ถ๐˜€ ๐—ฎ ๐˜ƒ๐—ฎ๐—น๐˜ƒ๐—ฒ ๐—ผ๐—ป ๐˜๐—ต๐—ฒ ๐˜€๐—ฒ๐—ฐ๐—ผ๐—ป๐—ฑ ๐—ฑ๐—ผ๐—ผ๐—ฟ. ๐—”๐—ป ๐—”๐—ป๐—ฎ๐—น๐—ผ๐—ด๐˜† It's a bit like a landlord telling a building manager: no more than 49% of tenants from one place. Not a law. A lease condition, enforced by whoever signs the lease. ๐—ก๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ฎ ๐—ป๐—ผ๐˜„ ๐˜„๐—ฎ๐—ป๐˜๐˜€ ๐˜๐—ต๐—ฎ๐˜ ๐˜๐—ผ ๐—ฐ๐—ต๐—ฎ๐—ป๐—ด๐—ฒ. ๐—ช๐—ต๐—ฎ๐˜ ๐—›๐—ฎ๐—ฝ๐—ฝ๐—ฒ๐—ป๐—ฒ๐—ฑ According to the Financial Times (five people familiar with the matter), Nvidia has told cloud providers that ๐—ฎ๐˜ ๐—น๐—ฒ๐—ฎ๐˜€๐˜ ๐Ÿฑ๐Ÿญ% of their services must go to non-Chinese companies. There was no such limit before. โ€ข ๐—ก๐—ผ ๐—ฝ๐—ฎ๐—ฝ๐—ฒ๐—ฟ๐˜„๐—ผ๐—ฟ๐—ธ: the instruction was given verbally, through Nvidia's sales and regional teams. โ€ข ๐—ช๐—ผ๐—ฟ๐—น๐—ฑ๐˜„๐—ถ๐—ฑ๐—ฒ: it applies to clients globally, not only in Asia (two people told the FT). โ€ข ๐—ก๐—ฒ๐˜„ ๐—ฑ๐—ฒ๐—ฎ๐—น๐˜€ ๐—ผ๐—ป๐—น๐˜†: existing leases are not affected. โ€ข ๐—ฆ๐—ถ๐—ป๐—ฐ๐—ฒ ๐˜๐—ต๐—ฒ ๐˜€๐˜‚๐—บ๐—บ๐—ฒ๐—ฟ: two people said Nvidia did it pre-emptively, to cut criticism from US lawmakers. ๐—ช๐—ต๐˜† ๐—ฅ๐—ฒ๐—ป๐˜๐—ถ๐—ป๐—ด ๐— ๐—ฎ๐˜๐˜๐—ฒ๐—ฟ๐˜€ US export rules mostly control where chips are shipped. Renting them in a data centre abroad has been the gap. Many Chinese groups used overseas leases for heavy AI work, including model training. Nvidia had already tightened the front door. This year it built a "white list" of approved Asian buyers and ๐—บ๐—ผ๐—ฟ๐—ฒ ๐˜๐—ต๐—ฎ๐—ป ๐—ต๐—ฎ๐—น๐˜ƒ๐—ฒ๐—ฑ it, per the FT. That pushed more Chinese firms toward renting. This new rule goes after ๐˜๐—ต๐—ฒ ๐—ฟ๐—ฒ๐—ป๐˜๐—ถ๐—ป๐—ด. ๐—ช๐—ต๐—ฎ๐˜ ๐—œ๐˜ ๐——๐—ผ๐—ฒ๐˜€ ๐—ง๐—ผ ๐—ฃ๐—ฟ๐—ถ๐—ฐ๐—ฒ๐˜€ A rack of B300 chips sells for ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ $๐Ÿฒ๐Ÿฌ๐Ÿฌ,๐Ÿฌ๐Ÿฌ๐Ÿฌ internationally. One person told the FT a rack fetched ๐—ฅ๐—บ๐—ฏ๐Ÿญ๐Ÿด.๐Ÿฑ๐—บ๐—ป (๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ $๐Ÿฎ.๐Ÿด๐—บ๐—ป) in China last month. That is ๐—ฟ๐—ผ๐˜‚๐—ด๐—ต๐—น๐˜† ๐Ÿฐ.๐Ÿณ ๐˜๐—ถ๐—บ๐—ฒ๐˜€ the price. The B300 can't legally be sold in China. ๐—™๐—ผ๐—ฟ ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ฃ๐—ฟ๐—ผ๐˜ƒ๐—ถ๐—ฑ๐—ฒ๐—ฟ๐˜€ Chinese tech groups are the biggest clients for data centres in places like south-east Asia. A Singapore-based provider told the FT it is hard to find enough non-Chinese clients outside the US. Providers that can't find them may have to ๐˜€๐—ต๐—ฟ๐—ถ๐—ป๐—ธ. New contracts only. ๐—ง๐—ต๐—ฒ ๐— ๐—ฎ๐—ฝ ๐—ข๐—ณ ๐—–๐—ต๐—ถ๐—ป๐—ฎ ๐—–๐—ผ๐—บ๐—ฝ๐˜‚๐˜๐—ฒ ๐—–๐—ผ๐—ป๐˜๐—ฟ๐—ผ๐—น๐˜€, ๐—ข๐—ป๐—ฒ ๐—Ÿ๐—ถ๐—ป๐—ฒ ๐—˜๐—ฎ๐—ฐ๐—ต โ€ข ๐—จ๐—ฆ ๐—ฒ๐˜…๐—ฝ๐—ผ๐—ฟ๐˜ ๐—ฐ๐—ผ๐—ป๐˜๐—ฟ๐—ผ๐—น๐˜€: block shipping top chips like the B300 to China. โ€ข ๐—•๐—œ๐—ฆ ๐—ฟ๐˜‚๐—น๐—ฒ (๐—๐—ฎ๐—ป๐˜‚๐—ฎ๐—ฟ๐˜†): license applicants must list remote cloud users in China and other listed countries. โ€ข ๐—•๐—œ๐—ฆ ๐—ด๐˜‚๐—ถ๐—ฑ๐—ฎ๐—ป๐—ฐ๐—ฒ (๐— ๐—ฎ๐˜† ๐Ÿฏ๐Ÿญ): a license is needed for advanced chips going to companies headquartered in China or Macau, wherever they are. โ€ข ๐—ก๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ฎ'๐˜€ ๐˜„๐—ต๐—ถ๐˜๐—ฒ ๐—น๐—ถ๐˜€๐˜ (๐˜๐—ต๐—ถ๐˜€ ๐˜†๐—ฒ๐—ฎ๐—ฟ): approved Asian buyers more than halved, per the FT. โ€ข ๐—ฅ๐—ฒ๐—บ๐—ผ๐˜๐—ฒ ๐—”๐—ฐ๐—ฐ๐—ฒ๐˜€๐˜€ ๐—ฆ๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† ๐—”๐—ฐ๐˜: passed the House 369-22 in January; sitting with the Senate Banking Committee. โ€ข ๐—ก๐˜ƒ๐—ถ๐—ฑ๐—ถ๐—ฎ'๐˜€ ๐Ÿฑ๐Ÿญ% ๐—ฟ๐˜‚๐—น๐—ฒ (๐—ป๐—ผ๐˜„): aimed at the cloud provider's customer mix, not the chip. ๐—ช๐—ต๐—ฒ๐—ฟ๐—ฒ ๐—ง๐—ต๐—ถ๐˜€ ๐—™๐—ถ๐˜๐˜€ Government rules set the floor. Nvidia is adding its own layer on top, so lawmakers have less to criticise (two people told the FT that was the motive). ๐—ช๐—ต๐—ผ ๐—™๐—ฒ๐—ฒ๐—น๐˜€ ๐—œ๐˜ โ€ข ๐—–๐—น๐—ผ๐˜‚๐—ฑ ๐—ฝ๐—ฟ๐—ผ๐˜ƒ๐—ถ๐—ฑ๐—ฒ๐—ฟ๐˜€ ๐—ถ๐—ป ๐˜€๐—ผ๐˜‚๐˜๐—ต-๐—ฒ๐—ฎ๐˜€๐˜ ๐—”๐˜€๐—ถ๐—ฎ: Chinese tech groups are their biggest clients. โ€ข ๐—–๐—ต๐—ถ๐—ป๐—ฒ๐˜€๐—ฒ ๐—”๐—œ ๐—ฐ๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€: already paying a premium. A B300 rack, ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ $๐Ÿฒ๐Ÿฌ๐Ÿฌ๐—ธ abroad, reportedly fetched $๐Ÿฎ.๐Ÿด๐—บ๐—ป in China last month (one deal). ๐—ง๐—ต๐—ฒ ๐—ฏ๐—ถ๐—ด๐—ด๐—ฒ๐—ฟ ๐—ฝ๐—ผ๐—ถ๐—ป๐˜: ๐˜ต๐˜ฉ๐˜ฆ ๐˜ค๐˜ฉ๐˜ช๐˜ฑ ๐˜ธ๐˜ข๐˜ณ ๐˜ช๐˜ด ๐˜ฎ๐˜ฐ๐˜ท๐˜ช๐˜ฏ๐˜จ ๐˜ง๐˜ณ๐˜ฐ๐˜ฎ ๐˜ธ๐˜ฉ๐˜ฐ ๐˜ค๐˜ข๐˜ฏ ๐˜ฃ๐˜ถ๐˜บ ๐˜ค๐˜ฉ๐˜ช๐˜ฑ๐˜ด ๐˜ต๐˜ฐ ๐˜ธ๐˜ฉ๐˜ฐ ๐˜ค๐˜ข๐˜ฏ ๐˜ณ๐˜ฆ๐˜ฏ๐˜ต ๐˜ต๐˜ฉ๐˜ฆ๐˜ฎ. FT (original report): ft.com/content/1902df70-1380โ€ฆ Links in reply ๐Ÿ‘‡
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Replying to @Scobleizer
Agree with this. For me though, 10x better mostly means 10x more reliable. My biggest worry with agents in production is whether they actually follow the steps I give them. Half the time one gets quietly skipped and I only notice when the output looks off. If a founder can show me their agent sticks to the process and stays accurate run after run, that's the 10x I'd pay attention to.
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