Old Zhang's AI Learning
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Old Zhang's AI Learning

AI practitioner specializing in large-model evaluation and on-premise deployment, agents, AI programming, Vibe Coding, general AI, and broader tech trends, with daily original technical articles.

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Latest from Old Zhang's AI Learning

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Old Zhang's AI Learning
Old Zhang's AI Learning
Jul 30, 2026 · Artificial Intelligence

Alibaba Qoder Voice Tested: Can It Finally Ditch the ‘Li Jie’ Meme?

The author evaluates Alibaba’s newly released Qoder Voice, a real‑time full‑duplex AI coding assistant powered by Qwen‑Audio‑3.0‑Realtime, describing its setup, interaction flow, model performance (84.1% score, global No.1), and practical experience including interrupt handling, Appshot context, and shortcut configuration.

AI coding assistantAppshotQoder
0 likes · 5 min read
Alibaba Qoder Voice Tested: Can It Finally Ditch the ‘Li Jie’ Meme?
Old Zhang's AI Learning
Old Zhang's AI Learning
Jul 29, 2026 · Frontend Development

Turn Scientific Visualizations into Reusable Skills: 10 Open‑Source Interactive Experiments

The article presents z‑sci‑viz‑lab, a reusable Skill that transforms scientific concepts into single‑page interactive demos, outlines an eight‑step workflow, shows two usage patterns, details the Vite + Three.js + Canvas stack, and demonstrates nine concrete experiments ranging from eclipses to plate tectonics.

Three.jsVisualizationVite
0 likes · 13 min read
Turn Scientific Visualizations into Reusable Skills: 10 Open‑Source Interactive Experiments
Old Zhang's AI Learning
Old Zhang's AI Learning
Jul 27, 2026 · Industry Insights

Deploying Kimi K3 Locally: Why You Need Up to $30 Million in Infrastructure

The article breaks down the massive hardware and budget requirements for running the open‑sourced 2.8‑trillion‑parameter Kimi K3 model locally, showing that a single node cannot hold the 1.56 TB weights and that realistic deployments start at ¥7‑8 million and can exceed ¥30 million for the recommended 64‑GPU supernode.

AI InfrastructureGPU H200Kimi K3
0 likes · 7 min read
Deploying Kimi K3 Locally: Why You Need Up to $30 Million in Infrastructure
Old Zhang's AI Learning
Old Zhang's AI Learning
Jul 27, 2026 · Fundamentals

Exploring the Kakeya Conjecture: A Codex‑Powered Interactive Lab After Wang Hong’s Fields Medal

The article explains the history and recent proof of the three‑dimensional Kakeya conjecture, describes how the author used Codex to create an interactive Three.js experiment that visualizes the conjecture, and outlines a reusable workflow for turning complex scientific ideas into accessible web demos.

CodexFields MedalInteractive Visualization
0 likes · 11 min read
Exploring the Kakeya Conjecture: A Codex‑Powered Interactive Lab After Wang Hong’s Fields Medal
Old Zhang's AI Learning
Old Zhang's AI Learning
Jul 26, 2026 · Artificial Intelligence

ChatGPT Web Now Supports Skills – Unlocking a Hidden Cloud Computer

The author notes that the latest ChatGPT web interface has merged Codex‑like Skills and a cloud‑based sandbox, allowing users to upload and run over a hundred Skills without consuming Codex limits, effectively turning the service into an always‑on AI “cloud computer” for tasks such as file handling, document generation, and web automation.

AI automationChatGPTCloud Sandbox
0 likes · 7 min read
ChatGPT Web Now Supports Skills – Unlocking a Hidden Cloud Computer
Old Zhang's AI Learning
Old Zhang's AI Learning
Jul 25, 2026 · Artificial Intelligence

How Much Does Deploying GLM‑5.2 Locally Cost? A Detailed Cost Breakdown

The article provides a thorough cost analysis for locally deploying the GLM‑5.2 large language model, detailing hardware configurations, FP8 and BF16 precision options, single‑node versus dual‑node setups, memory requirements, and why regulated finance firms are the primary candidates for such an investment.

AI InfrastructureBF16FP8
0 likes · 7 min read
How Much Does Deploying GLM‑5.2 Locally Cost? A Detailed Cost Breakdown
Old Zhang's AI Learning
Old Zhang's AI Learning
Jul 24, 2026 · Industry Insights

Jensen Huang’s First X Post Unveils a 25‑Institution Open‑Weight AI Letter

Jensen Huang’s debut X post shares a public letter signed by 25 AI‑focused organizations, urging open model weights to democratize AI, broaden competition across the entire stack, and keep control of data and upgrades within enterprises, while highlighting the shifting dominance from closed‑source giants.

AI competitionAI ecosystemIndustry Analysis
0 likes · 7 min read
Jensen Huang’s First X Post Unveils a 25‑Institution Open‑Weight AI Letter