A Transformer model that preserves logical equivalence
Optimize logic circuits by minimizing their size while preserving logical equivalence. Provide a logic circuit in Aiger format with up to 8 inputs and 2 outputs, and specify the number of Monte-Car...
A Transformer model that preserves logical equivalence launched on March 2, 2025 with 9 votes, #3,084 of 7,215 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 1 year on.
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Duplicate 3 layers in a 24B LLM, logical deduction .22→.76. No trainingMar 2026 · github.com · ▲265I replicated David Ng's RYS method (https://dnhkng.github.io/posts/rys/) on consumer AMD GPUs (RX 7900 XT + RX 6950 XT) and found something I didn't expect. Transformers appear to have discrete "reasoning circuits" — contiguous blocks of 3-4 layers that act as indivisible cognitive units. Duplicate the right block and the model runs its reasoning pipeline twice. No weights change. No training. The model just thinks longer. The results on standard benchmarks (lm-evaluation-harness, n=50): Devstral-24B, layers 12-14 duplicated once: - BBH Logical Deduction: 0.22 → 0.76…
- IMI made a discrete logic network card2024 · qdiv.dev · ▲541
Building a 10BASE-T Ethernet transceiver (receiver and transmitter) with discrete logic chips
zkGolf – Competitive optimization of formally verified circuitsJul 2026 · zk.golf · ▲69Zero-Knowledge Proofs (ZKPs) let an untrusted proved show that computation was executed correctly without revealing the inputs to the verifier. However to prove anything, the computation first has to be expressed as a circuit: a system of polynomial equations (constraints) over a finite field. Circuits are the assembly language of zk and every constraint costs prover (and sometimes verifier) time, so production circuits are aggressively hand-optimized. Over the last months, we have been experimenting with writing formal specifications instead and letting LLMs produce the circuits: as long as…
Symbolic Circuit Distillation: prove program to LLM circuit equivalenceJan 2026 · github.com · ▲16Hi HN, I've been exploring various applications of formal methods to ML/interpretability and I've been hoping to get more eyes on the approach. I have been working on a small interpretability project I call Symbolic Circuit Distillation. The goal is to take a tiny neuron-level circuit (like the ones in OpenAI's "Sparse Circuits" work) and automatically recover a concise Python program that implements the same algorithm, along with a bounded formal proof that the two are equivalent on a finite token domain. Roughly, the pipeline is: 1. Start from a pruned circuit graph for a specific…
A Implementation of Alpha Zero for Chess in MLX2025 · github.com · ▲71A chess engine implementation inspired by AlphaZero, using MLX for neural network computations and Monte Carlo Tree Search (MCTS) for move selection.
We built an 8-bit CPU as 2nd year EE studentsJun 2026 · github.com · ▲108Hi! me and my friends together built an 8 bit CPU implemented in Logisim purely from scratch. The control unit of this system does not implement the generic microcode ROM or any kind of RAM. This was made purely from discrete logic gates and coded the system to run different programs. key features: Custom 16-instruction Harvard ISA, 8-bit fixed format, 4 general purpose registers Hardwired control unit built entirely from AND/OR gate logic matrix Dual-phase clocking to eliminate race conditions Bootstrap Control Unit that cold-boots via ROM-to-RAM transfer Early-exit conditional…
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