Category
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.
11 articles
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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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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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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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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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AI in the browser · Jun 7, 2026
Do browser AI tools work offline?
How on-device AI tools keep working without a connection, and what still needs the network.
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AI in the browser · Jun 6, 2026
How big are in-browser AI models (and why size matters)
Why an on-device model is tens to hundreds of megabytes — and why that download is worth it.
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AI in the browser · May 30, 2026
Bring your own ONNX model: running your own weights in the browser
The logical end state of on-device AI — if the computation happens on your machine, the model does not have to be ours. How BYO-ONNX works and why it exists.
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