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aegis_camera

HN member
Joined
Wed, Mar 18, 2026, 3:57 AM UTC
HN karma
107
Public activity
58 items

About aegis_camera

service@sharpai.org

Recent public activity

  1. story
  2. comment
    Comment #47607251

    Thanks, we are not large R&D lab, limited resources. We were working on a product with is a Local VLM first BYOD when you want Video Security application, our users requested to ha…

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    Comment #47607176

    Tried, but wrong time to post, it got zero attention . :)

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    Comment #47606393

    One of my user requested MLX comparison with GGUF, he wanted to run the benchmark, I was thinking about how to get MLX support without bundling the python code together with SharpA…

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    Comment #47606245

    Here is a reference https://www.sharpai.org/benchmark/ For specific tasks, local model could achieve workable level.

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    Comment #47606237

    Thanks, pure Swift was the design idea and since I found nothing could be used for my project https://www.sharpai.org then I created Swift version. Python is too heavy to be delive…

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    Comment #47606185

    https://www.sharpai.org/benchmark/ The MLX part is what we've done with SwiftLM, the local result is still being verified more details are on-going.

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    Comment #47606167

    I've ran this on an IPHONE 13 pro (6GB) memory, QWEN 3 1.7B runs good. So local will get more intelligent for the task you want it done soon or already.

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    Comment #47606113

    Yes, I've ran it on IOS, IPHONE 13 pro beside M5 pro, I'll test it on my M2 Mini and M3 Air.

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    Comment #47606054

    the Python mlx-metal trick is actually what's crashing it. The mlx.metallib from pip is a different version of MLX than what your Swift binary was built against. It gets past the s…

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    Comment #47605950

    git clone https://github.com/SharpAI/SwiftLM # no --recursive needed cd SwiftLM swift build -c release ### Please let me know if this fix the issue: # Copy metallib next to the bin…

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    Comment #47605777

    [flagged]

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    Comment #47605682

    Yes, this is a reference project, the main different is we don't use os swap ( it introduces latency, will add https://github.com/danveloper/flash-moe to the original reference as …

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    Comment #47605650

    I'll add more details. We just wired up the pipeline on both MAC and IOS.

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    Comment #47604383

    We implemented two techniques to run massive 100B+ parameter MoE models natively on the M5 Pro 64GB MacBook Pro: TurboQuant KV compression: We ported the V3 Lloyd-Max codebooks fro…

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  19. comment
    Comment #47604191

    Thank you for your feedback.

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  22. comment
    Comment #47496267

    I see, so connect to the existing HA will be the priority.

  23. comment
    Comment #47461736

    Hi, thanks for your bug report, we had a fix and uploaded to the following GitHub release page, we are working on more testing meanwhile: https://github.com/SharpAI/DeepCamera/rele…

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    Comment #47461150

    [flagged]

  25. comment
    Comment #47460560

    I don't know if I can post the email here hopefully hn doesn't filter it out: service at sharpai.org