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AI in the browser

The technical and practical side of running AI on your own device: why on-device AI is private by design, what actually runs locally vs in the cloud, how AI runs in your browser with WebGPU and WebAssembly, the privacy cost of free AI tools, and whether browser AI works offline.

13 articles

About the AI in the browser thread

On-device AI is the technical bet the whole portfolio rests on, and this cluster is where the bet gets examined honestly. Running a model in a browser tab means the user's data never moves, which resolves the privacy problem structurally instead of by promise, but it also means running inside a memory budget, on whatever GPU is present, over a model you had to download first.

The articles cover both sides: how WebGPU and WebAssembly make local inference viable, what genuinely runs locally versus what still needs a server, what free cloud AI tools actually cost you in data, and whether any of it works offline. The recurring conclusion is that "private by design" is an architecture claim you can verify by watching the network tab, not a policy claim you have to trust.

What this topic covers

  • Why on-device inference is private by design, and how to verify the claim yourself
  • WebGPU and WebAssembly: what makes browser inference fast enough to use
  • What runs locally today vs what still requires a server, as of 2026
  • The privacy cost of free cloud AI tools, stated plainly
  • Offline behaviour, model downloads, caching, and first-run cost

Who it's for

Developers evaluating client-side ML, privacy-conscious users deciding what to trust, and anyone trying to separate on-device marketing from on-device reality.

13 articles in this thread, newest first. Every one is free to read with no signup.

  1. An AI tool being evaluated on a test bench, with real user files and probe inputs feeding in and gauges reporting quality, failure behavior, pricing risk, and export paths

    AI in the browser · Jul 15, 2026

    Evaluating AI tools before you depend on them

    A ninety-minute evaluation protocol for AI tools: score candidates on a test set built from your own work, probe failure modes on purpose, verify where processing runs, model repricing risk, and perform a real export before anything important depends on the answer.

    Novus Stream Solutions (hub)

  2. A device and a cloud with AI workloads sorted between them: image segmentation, transcription, and small language models on the device side; frontier models and video generation on the server side

    AI in the browser · Jul 14, 2026

    What local AI can actually do in mid-2026

    A vendor-free status report on on-device AI as of mid-2026: segmentation, transcription, and small language models are genuinely local now; frontier reasoning and video generation are not, and the reasons are physics, not politics.

    Novus Stream Solutions (hub)

  3. A photo at a fork between an upload-to-cloud path and an on-device path, with a privacy checklist

    AI in the browser · Jun 12, 2026

    Are AI photo editors safe? What to check before you upload

    Where your photo actually goes in an AI editor, how to read the privacy policy, the on-device alternative, and a quick checklist before uploading anything personal.

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  4. A large model made of high-precision numbers being compressed into a much smaller model of low-precision integers, shrinking from a download too big for a browser to one that fits

    AI in the browser · Jun 12, 2026

    Model quantization: how big AI models shrink to run in a browser

    A plain-English explanation of the technique that makes on-device AI possible: why a model’s size is the gatekeeper for running it in a browser, what a model actually is under the hood, how quantization stores its numbers in fewer bits for a roughly four-times reduction, why models tolerate the lost precision, what it costs in accuracy, and how it combines with distillation and pruning.

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  5. A two-column map of what on-device AI can do today versus where it still hits a wall

    AI in the browser · Jun 8, 2026

    What on-device AI can't do yet

    The honest edges of in-browser AI: frontier models, heavy video, tight memory, and when a fallback wins.

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  6. Why on-device AI is private by design

    AI in the browser · Jun 7, 2026

    Why on-device AI is private by design

    The difference between “we promise not to look” and “the data physically cannot leave.”

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  7. What AI runs on your device versus in the cloud

    AI in the browser · Jun 7, 2026

    What runs on your device vs in the cloud

    A practical guide to telling on-device AI from cloud AI, and what each implies.

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  8. How AI runs in your browser with WebGPU and WebAssembly

    AI in the browser · Jun 7, 2026

    How AI runs in your browser (WebGPU and WebAssembly, explained)

    A plain-language explainer of the browser tech that makes on-device AI fast enough to use.

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  9. The privacy cost of free AI tools

    AI in the browser · Jun 7, 2026

    The privacy cost of free AI tools

    What "free" can really mean when your images or audio are uploaded to a server.

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