Making Apple Neural Engine work in a custom inference stack
CoreML as an accelerator, not end-to-end runtime—1.8× speedup on M4 chips.
There were several issues but I found a solution for each and it currently live at the GitHub repo link.
Repo: https://github.com/raphaelwkago69-create/GLYPH
Attack it. If you break a claim, file an issue.
CoreML as an accelerator, not end-to-end runtime—1.8× speedup on M4 chips.
65K lines of C++20 making blockchain produce useful AI models instead of wasting electricity.
Ambitious lattice PoW blockchain, but unverified claims and no working mainnet or active community evidence.
Another PoW blockchain social network when Lens, Farcaster, and Steemit already exist.
CNN inference fully hardcoded as silicon logic, not software optimized for hardware.
Strips away PyTorch flexibility entirely; full CNN inference as deterministic hardware logic in SystemVerilog.