MASTERMIND

MASTERMIND

Here are some key aspects of MASTERMIND:

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SimpleMind

SimpleMind: A Neural Network Implementation in JAX

The SimpleMind class is a powerful yet straightforward implementation of a neural network in JAX. It supports various activation functions, optimizers, and regularization techniques, making it versatile for different machine learning tasks. With parallel backpropagation and detailed logging, it provides an efficient and transparent framework for neural network training.

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observe

mindX as a protocol — the catalogue, observability as an append-only protocol

A single append-only event stream mirrors every write mindX makes, turning observability into a replayable, optimizable substrate.

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mindXtrain — One-Command Qwen3 Fine-Tuning on AMD MI300X

mindXtrain is the first one-command Qwen3 fine-tuner natively optimized for AMD MI300X. It is the AMD-shaped half of the PYTHAI/DELTAVERSE stack: a single Python package that takes a YAML recipe and produces a trained, evaluated, FP8-quantized, served, and on-chain-anchored model — all on a single MI300X, all driven by a 60-second on-device autotune that pins kernel and collective choices before training starts. This post is the canonical landing page for the project. If you are […]

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