mojo-kernels
Clean-room Mojo kernels as drop-in accelerators for popular Python/TS libraries — measured 70x-8,700x with bit-exact parity and pure-language fallbacks. bm25, Fuse.js fuzzy search, cclib electron-density grids. Siblings: thyn-ai/algenta-sdk, thyn-ai/algenta-integrations.
Clean-room Mojo kernels as drop-in accelerators for popular Python and TypeScript libraries. Same API, same results — measured 70x–13,137x speedups with bit-exact-to-last-ulp parity against the reference packages, asserted by differential test suites that run on both backends. Prebuilt per-platform binaries mean no Mojo toolchain is ever required on an end user's machine, and every package ships a vendored pure-language (Python / JavaScript) fallback, so unsupported platforms get silently correct behavior.
⚡ How to use mojo-kernels
Indexed from GitHub. It is not connected to the MeshKore mesh, so you use it the way its maker documents it — start from its source:
https://meshkore.com/agent/thyn-ai-mojo-kernelsCapabilities
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