Show HN: Andrej Karpathy's microgpt.py to C99 microgpt.c – 4,600x faster (github.com)

Andrej Karpathy has unveiled microgpt.c, a zero-dependency implementation of a GPT-style character-level language model, achieving a remarkable 4,600x speed increase over its Python counterpart, microgpt.py. This C99 implementation mirrors the architecture and training mechanisms of the original model but compiles directly to native code. The result is a lightweight model capable of training in just 20 milliseconds and generating names in microseconds, all without relying on Python, PyTorch, or GPUs. This approach not only facilitates faster training and inference but also provides a minimalistic, readable codebase ideal for educational purposes. The significance of this development for the AI/ML community lies in its accessibility and educational value. With the entire model fitting into fewer than 50 KB of RAM, it is perfectly suited for embedded systems and edge devices, making it a practical tool for both researchers and students. By stripping away framework abstractions, microgpt.c allows users to explore essential components of neural networks, such as attention mechanisms and optimization techniques, at a fundamental level. Additionally, the optional SIMD feature enhances performance further on larger models, showcasing how efficient implementations can drive rapid prototyping and experimentation in AI applications.