A simple tool to allow storage of signed, encrypted, incremental backups using Amazon's Glacier storage
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Updated
Sep 17, 2026 - Python
A simple tool to allow storage of signed, encrypted, incremental backups using Amazon's Glacier storage
Expanding linear RNN state-transition matrix eigenvalues to include negatives improves state-tracking tasks and language modeling without added training or inference costs.
Two error detection techniques made with Python & Matlab
CLI-first LLM runtime parity diagnostics. Same model, same input, first causal divergence.
Minimal feature store with in-memory + Redis backends and an explicit online/offline parity check covering 5 named divergence types. p99 single-read 2.1us on 100K cells.
Few of the codes I practiced while coding.
Python implementations of parity bit error detection (even and odd parity), demonstrating limitations and applications in serial communication.
Prove that a refactor moved no value, and name the one that did.
Interactive pyserial-based RS-232 probe for COM port baud/framing/flow-control discovery, validation, and reporting on legacy hardware.
Three composing Claude Code skills (EN + 中文) on one atom-ID spine: freeze an owner↔code contract → audit parity → gate with independent verification. 让"完成"=独立验收过,而不是"实施者说完成".
A simple example in Python with the help of Sage sending messages between server and client sockets detecting errors with Parity-check code.
python problems
Differential memristive crossbar with a hardware-friendly in-situ (Manhattan/sign-rule) learning rule, tested on parity-3 — the calibrated in-memory-compute baseline of the physical-learning-substrates portfolio. Verdict #1: PASS, learns parity-3 at SNR ~24.5 (half co-located: physics activations, off-array error sign, physical-pulse increment).
GGUF parity and model-validation tools for comparing logits and hidden states against llama.cpp or other references.
Energy-based (Ising/Boltzmann) learning substrate for parity-3 — can a local, physics-native contrastive rule both compute and learn the couplings? Part of the Physical Learning Substrates portfolio.
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