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SirStone c8b2a8c6c5 docs: reverse-engineer the BitBrain algorithm from its C source; assess as a gun
Reads docs/BitBrain_C_code.zip end to end (full_mnist_2048.c 568 lines +
bitarray.h), reconciles every weight/data file's byte size against its
loader, and answers two questions:

1. What the algorithm is: signed thresholded address decoders (random
   projections) -> write-once sparse binary coincidence bit tensors ->
   counting/argmax readout. Thresholds and ADs come from an unsupervised
   program that is NOT in the zip; only the SBC tensors are learned here.
   The supervised rule is genuinely online, single-pass, order-free, and
   has no learning rate - so it satisfies ModularBot's reset-on-enemy-change
   constraint. Found and isolated a real bug: read_from_sbc's uint8_t
   bit_test truncates the 32-bit bit test, so only ADEs with i%%32 < 8 are
   ever counted. Shipped reader: 96.540%% (reproduced exactly); with the bug
   fixed: 97.210%%.

2. Whether it can become a gun: not on this evidence. Measured full
   inference at ~0.56 ms/sample (cost is not the blocker), but the AD layer
   is unobtainable, and this repo has already shown the binding constraint
   is the target signal, not the learner - the TM head scored 2.08pp below
   its own majority class and the AD/SBC primitives are already in the
   16-family shootout as WiSARD/Bloom/SDM. Recommends a readout swap on the
   existing WiSARD feature extractor and a Gate-2b-style >=80%% side-accuracy
   gate before any port.

Also: recommends committing the 11 MB zip under its explicit name.
2026-09-24 20:17:08 +02:00