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Converts an input image into 3D meshes, Gaussian splats, and audio files using Claude skills and external AI APIs.
Archives experiments of AI agents autonomously tuning optimizers, schedules, and hyperparameters to reach target validation loss in fewest steps on a small LM benchmark.
Integrates Ghostty into a macOS terminal with vertical tabs, sidebar metadata, OSC notifications, and in-app browser for AI coding agents.
Provides AI agent toolkit with coding CLI, unified LLM API, TUI/web UI libs and Slack bot support.
Automates articulated 3D asset creation by prompting LLMs to generate executable Python code defining parts, geometry and joints.
Cleans raw datasets into instruction-response JSON/Parquet, trains a Rust BPE tokenizer, tokenizes text to memory-mapped numpy arrays, and runs stratified sampling for balanced pretraining data.
Cross-posts to X, Mastodon, Bluesky and LinkedIn via APIs with image alt-text and RSS automation in a Kotlin self-hosted service.
Implements dataset construction and confidence estimation for LLM capability calibration using verbalized, P(True), and consistency methods.
Implements lightweight training runtime, primitives and Qwen MoE model layers for Megatron.
Evaluates language models on reconstructing complete codebases from compiled binaries and documentation.