Claudish is a bidirectional translator between English and a language called Claudish. It is powered by compiled neural programs with 0.6 billion parameters. The translator supports conversion from English to Claudish and from Claudish back to English.

A new puzzle challenges participants to reverse engineer a chip layout without additional information about its function. Modern chips are initially created from code using hardware description languages like Verilog, which are then synthesized into a netlist.

A perceptron is the simplest form of a neural network, processing one input to produce a binary output. It can be built from scratch in Python using basic components like a weight, a bias, and a loop, allowing for live learning demonstrations in a browser without complex mathematics or libraries.

An NSFW filter for Marginalia Search is being developed in response to requests from API consumers. The filter will utilize a single hidden layer neural network, having explored various other methods prior to this decision.

Tinygrad is a neural network framework designed for simplicity and speed, breaking down complex networks into three operation types: ElementwiseOps, ReduceOps, and MovementOps. ElementwiseOps include operations like SQRT and ADD, ReduceOps perform functions like SUM and MAX on a single tensor, and MovementOps manage data movement without copying, utilizing ShapeTrack.

nCPU is a CPU architecture that operates entirely on GPU, utilizing tensors for registers, memory, flags, and the program counter. All arithmetic operations, including addition, multiplication, bitwise operations, and shifts, are performed through trained neural networks, with specific methods like Kogge-Stone carry-lookahead for addition and learned byte-pair lookup tables for multiplication.