AI technology, read across systems.

Huaweidata is an AI technology magazine for long-form notes on agents, software, research, infrastructure, and the institutions forming around them. The English edition is canonical; Chinese mirrors keep the same structure.

Latest Daily

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  1. A dark desk where one glowing invariant line connects a proof grid, company map, database, robotic hand, and financial timeline
    Editor's Desk - Verifiable Ground

    When agents start writing code, reading company context, touching databases, operating robots, and entering financial systems, acceptance has to move from fluency back into structure.

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  2. Dark editor desk scene with layered papers, screens, and structured notes
    Editor Desk · Teach Why, Not What

    A scroll-driven essay on checklists, training data, audit chains, and the daily actions that all point to the same problem.

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  3. Interactive mechanism diagram showing an LLM using a stateful Python REPL, typed returns, scoped object injection, and recursive sub-agents
    Editor's Desk · Issue 3: Make Latent Visible

    A magazine letter on the week of May 12, 2026: across AI agents, perpetual futures, robotic hands, self-driving labs, cat facial mimicry, and a Colorado wet-slab avalanche, surface signals are quietly decoupling from deep structure.

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  4. Editorial desk at dawn with a scaffolded tower model, an AI agent graph on a laptop, a negative bar chart printout, a data center reflection, and a small cat silhouette
    Editor's Desk · May Week 2: When Scaffolding Starts to Cost You

    A magazine-style read of one strange week in tech: Anthropic ships 'how an agent audits itself' as an SDK, Karpathy's own coding guide quietly makes Claude Code worse, the academic line on rubric verifiers, and a two-month-old kitten that just rewrote 70 years of cat archaeology.

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Latest Column

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  1. Technical flow diagram showing a question moving through tokens, context, tool calls, sampling, and output generation in an LLM
    A Question's Journey - LLM from Input to Output

    A full mechanism timeline from one prompt through context, tokenization, Transformer internals, generation, tool calls, sampling, latency, and reasoning budget.

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