Posts
All the articles I've posted.
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Private Stablecoins, GPU Provers, and the Rand Bridge
Stablecoins moved trillions of dollars last year across ledgers where every payment is permanently public. This is a tour of what that costs, and of one way out: a shielded stablecoin bridge whose privacy proofs are manufactured by a competitive market of GPUs. We cover why privacy is a payments requirement rather than a luxury, how the Rand Protocol prover market and bridge fit together, what the economics of a proof actually look like, and what a graphics card is really doing during the five seconds it spends convincing the world you paid your rent.
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Encrypted Chat Over Sound: An Acoustic MFSK Modem in Rust
I wrote a program that sends encrypted chat between two laptops using nothing but a speaker and a microphone. No network, no pairing, no passphrase — the peers agree a key over the air with X25519 and you verify it by reading four words aloud. Here is the whole stack: parallel MFSK modulation, Goertzel detection, Reed–Solomon with cross-block interleaving, half-duplex carrier sense, and AES-256-GCM with a short authentication string.
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The Intelligent Worm: Adaptive Malware
A conceptual, defense-oriented threat analysis of the 'Intelligent Worm' — a hypothetical self-propagating program whose exploitation capability is regenerated by an AI reasoning loop rather than fixed at authoring time. I walk the history of static worms through an epidemiological lens (the reproductive number R0 and the epidemic threshold), show why patching has historically driven outbreaks below threshold, and argue that an adaptive exploit term changes the shape of that curve. I take the feasibility limits seriously — hallucination, verification cost, autonomous experimentation — survey what current LLM-agent security research (Morris II, the Fang et al. autonomous-exploitation results, Google's Big Sleep) actually demonstrates, and lay out the defensive re-architecture the threat model implies. No exploit code, no propagation implementation: this is a stress-test of our defensive assumptions.
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On Quantum Algorithms for Neural-Network Training: A Conjecture on Fault-Tolerant Speedups
The Suhubdy Conjecture — a three-form mathematical conjecture for a fault-tolerant quantum algorithm that accelerates — or replaces — backpropagation for empirical-risk minimisation in neural networks. Positioned against the Baur–Strassen cheap-gradient bound, Jordan and Gilyén–Arunachalam–Wiebe gradient-estimation algorithms, Abbas et al. (NeurIPS 2023) impossibility, quantum SDP and interior-point solvers, the Zhang–Leng–Li and Garg–Kothari–Netrapalli–Sherif lower bounds, and the 2024–2026 line on quantum non-logconcave sampling. Companion arXiv-style preprint (.tex source and .pdf) provided.