slvDev
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esp32-ai
A 28.9 million parameter language model runs on an $8 ESP32-S3 microcontroller entirely on-device, generating simple stories at about 9.5 tokens per second.
AI 仓库情报摘要
FR-AI / ANALYSIS为什么值得关注
值得关注的原因在于它是以 Quarto 构建研究演讲的简洁实用示例，并且明确说明幻灯片本身由编码智能体起草，成为其所讨论工作流程的具体示范。
适合谁使用
- 对使用 AI 编码助手感兴趣的研究人员
- 使用计算工作流程的数据科学家和流行病学家
- 准备可复现演讲或演示文稿的学术人员
- 寻找幻灯片项目示例的 Quarto 用户
典型使用场景
- 了解编码智能体如何辅助起草研究演示文稿
- 复用该 Quarto 项目结构用于会议汇报或实验室组会
- 向同事或学生展示 AI 辅助的研究工作流程
- 将其中包含的布局、分节文件和图表改编用于其他幻灯片
项目优势
- 项目布局清晰简洁，内容按小节分离
- 通过 Task 或 Quarto 提供自动化渲染、预览和检查流程
- 提供在线渲染版本，便于直接查看
- 与当前关于 AI 在研究工作流程中的讨论高度相关
使用前须知
- 该仓库是幻灯片而非可复用的工具或库
- 本地构建需要熟悉 Quarto，并可选使用 Task
- README 除构建方式和文件结构外未提供更多深入技术细节
README 快速开始
How I am LLM
Slides for a 15-minute talk on integrating coding agents into research workflows.
Sam Abbott, London School of Hygiene & Tropical Medicine, 30 July 2026.
Rendered: samabbott.co.uk/how-I-llm
Building
Requires Quarto and, optionally, Task.
task # render to _site/
task preview # live-reloading preview
task check # validate the Quarto project
Layout
index.qmd— title slide, talk plan, and section includes_partials/— one file per sectionfigures/— figures, including the model diagram from BVDOutbreakSizestyle.css— presentation styling
These slides were themselves drafted by coding agents; the final section describes how.
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deltafin
Deltafin is a research project that runs the 2.8-trillion-parameter Mixture-of-Experts model Kimi K3 on a single Apple Silicon Mac (e.g., M1 Max with 64 GB) at about 16 seconds per token, using exact, reproducible inference with local or streaming expert loading.
jamesob
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local-llm
A comprehensive guide for building and configuring a high-end local machine to run state-of-the-art LLMs, with detailed hardware choices, BIOS tuning, and Docker-based model serving.