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fleetwood.dev

Personal blog · fleetwood.dev/postsaihardwareprogramming

fleetwood.dev is a personal blog at fleetwood.dev about ai, hardware and programming. Since 2021, 8 different Hacker News readers have linked it 32 times, most often “A case for client-side machine learning”. It is still writing: the last post was on 2025-07-05, and you can follow it by feed.

Visit the blog
32mentions?
8HN people?
2021–2025first – last linked?
Links on Hacker News per year · peak 10 in 2024

Too few sampled comments (2) to say how often HN recommends it.?

Why HN links it

Posts on running machine learning client-side in the browser, covering the WebNN API and running LLMs in the browser with WebGPU, including its limitations. Commenters link them as background.

Summarised by Claude from a sample of 2 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

fleetwood.dev

Most-linked posts?

  1. A case for client-side machine learning
    3 people · 8 mentions · first linked 2022-10-31
  2. Layer Normalization as Fast as Possible
    3 people · 6 mentions · first linked 2023-12-12
  3. Domain specific architectures for AI inference
    3 people · 5 mentions · first linked 2025-03-08
  4. Running LLMs in the Browser with Rust and WebGPU
    2 people · 3 mentions · first linked 2023-04-26

What Hacker News says?

  1. I described this system word for word 2 years ago, glad to see it come to fruition on the only software stack integrated enough to do it. https://fleetwood.dev/posts/a-case-for-client-side-machine-l...

    Comment linking /posts/a-case-for-client-side-machine-learning

    on “A look at Apple's technical approach to AI including core model performance etc.”
  2. Submitted You could have designed state of the art positional encoding as a story · 216 points

    HN discussion
  3. Read this book for the first time recently, a huge amount of prescient ideas in there. I wrote a blog post exploring how far away glasses like Manfreds are: https://fleetwood.dev/posts/a-first-principles-analysis-of-c...

    Comment linking /posts/a-first-principles-analysis-of-consumer-smart-glasses.mdx

    on “Accelerando (2005)”
  4. Submitted Running LLMs in the Browser with Rust and WebGPU as a story · 8 points

    HN discussion
  5. This isn't correct. It's 100% feasible to run very capable models on consumer devices. I wrote up a feasibility investigation last year: https://fleetwood.dev/posts/a-case-for-client-side-machine-l...

    Comment linking /posts/a-case-for-client-side-machine-learning

    on “Stability AI Launches the First of Its StableLM Suite of Language Models”
  6. Submitted Domain specific architectures for AI inference as a story · 4 points

    HN discussion
  7. https://fleetwood.dev/posts/a-case-for-client-side-machine-l...

    Comment linking /posts/a-case-for-client-side-machine-learning

    on “Ask HN: What's the idea behind the WebNN API?”
  8. Submitted Domain specific architectures for AI inference as a story · 4 points

    HN discussion
  9. Why were you skeptical of it originally? I wrote about this coming to pass over a year ago now: https://fleetwood.dev/posts/a-case-for-client-side-machine-l...

    Comment linking /posts/a-case-for-client-side-machine-learning

    on “Deno 1.39: The Return of WebGPU”
  10. Submitted Domain specific architectures for AI inference as a story · 3 points

    HN discussion
  11. I wrote a similar blog post in Nov 22: https://fleetwood.dev/posts/a-case-for-client-side-machine-l...

    Comment linking /posts/a-case-for-client-side-machine-learning

    on “The Coming of Local LLMs”
  12. Submitted Domain specific architectures for AI inference as a story · 3 points

    HN discussion
  13. As an example, INT8 support in WebGPU would enable running quantized models, allowing larger LLMs to run locally in the browser. See Limitations section here: https://fleetwood.dev/posts/running-llms-in-the-browser

    Comment linking /posts/running-llms-in-the-browser

    on “WebGPU – All of the cores, none of the canvas”
  14. Submitted A first principles analysis of smartglasses as a story · 3 points

    HN discussion
  15. Submitted A first principles analysis of smartglasses as a story · 3 points

    HN discussion
  16. Submitted A case for client-side machine learning as a story · 3 points

    HN discussion
  17. Submitted A Rust based ML model analyzer as a story · 3 points

    HN discussion
  18. Submitted fMRI timeseries similarity with a 10x speedup using Rust as a story · 3 points

    HN discussion
  19. Submitted Arc Virtual Cell Challenge: A Primer as a story · 2 points

    HN discussion
  20. Submitted Arc Virtual Cell Challenge: A Primer as a story · 2 points

    HN discussion
  21. Submitted A first principles analysis of smartglasses as a story · 2 points

    HN discussion
  22. Submitted A case for client-side machine learning (2022) as a story · 2 points

    HN discussion
  23. Submitted A case for client-side machine learning as a story · 2 points

    HN discussion
  24. Submitted Layer Normalization as Fast as Possible as a story · 1 points

    HN discussion
  25. Submitted Domain specific architectures for AI inference as a story · 1 points

    HN discussion
  26. Submitted Layer Normalization as Fast as Possible (2023) as a story · 1 points

    HN discussion
  27. Submitted Layer Normalization as fast as possible (2023) as a story · 1 points

    HN discussion
  28. Submitted A first principles analysis of smartglasses as a story · 1 points

    HN discussion
  29. Submitted Layer Normalization as Fast as Possible as a story · 1 points

    HN discussion
  30. Submitted Layer Normalization as Fast as Possible as a story · 1 points

    HN discussion

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