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by miohtama
786 days ago
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Depending on the underling machine learning activity (GPU/no-GPU) it should be already possible today. Any low level machine learning loops are raw native code or GPU already and Python’s execution speed is irrelevant here. The question is do the web browsers and WebAssembly have enough RAM to do any meaningful machine learning work. |
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Which have better process isolation; containers or Chrome's app sandbox at pwn2own how do I know what is running in a WASM browser tab?
JupyterLite, datasette-lite, and the Pyodide plugin for vscode.dev ship with Pyodide's WASM compilation of CPython and SciPy Stack / PyData tools.
`%pip install -q mendeley` in a notebook opened with the Pyodide Jupyter kernel works by calling `await micropip.install(["mendeley"])` IIRC.
picomamba installs conda packages from emscripten-forge, which is like conda-forge: https://news.ycombinator.com/item?id=33892076#33916270 :
> FWIU Service Workers and Task Workers and Web Locks are the browser APIs available for concurrency in browsers
sqlite-wasm, sqlite-wasm-http, duckdb-wasm, (edit) postgresql WASM / pglite ; WhatTheDuck, pretzelai ; lancedb/lance is faster than pandas with dtype_backend="arrow" and has a vector index
"SQLite Wasm in the browser backed by the Origin Private File System" (2023) https://news.ycombinator.com/item?id=34352935#34366429
"WebGPU is now available on Android" (2024) https://news.ycombinator.com/item?id=39046787
"WebNN: Web Neural Network API" https://www.w3.org/TR/webnn/ : https://news.ycombinator.com/item?id=36159049
"The best WebAssembly runtime may be no runtime" (2024) https://news.ycombinator.com/item?id=38609105
(Edit) emscripten-forge packages are built for the wasm32-unknown-emscripten build target, but wasm32-wasi is what is now supported by cpython (and pypi?) https://www.google.com/search?q=wasm32-wasi+conda-forge