Fast training, uncensored generation, free to try, open-source.

My hypothesis

My first experiments with Google's new Veo3 video generation model. I share the results, the prompts used, the current costs.

I like to automate as much work as possible. Here's a simple shell / bash script I'm using to save time by automatically creating git commit messages. r/git disliked it.

The simplest guide to vector embeddings in practice and how to use them, including video demos solving real problems at our startup by quantifying text meaning for classification and similarity tasks.

Getting great LLM output with an LLM-as-a-judge requires more effort, not more tools

Why superintelligent AI would protect humanity as a source of complexity and knowledge

I tested 5 AI-text detectors that claim to detect LLM-generated text. The outcome: they don't work well.

We'll train a real GPT AI language model from scratch using Python on macOS, specifically designed to generate Shakespearean text, using the Tiny Shakespeare dataset.

Use a fast LLM, HTMX, and Photon Designer to recommend actions to the user.

Use Django and webhooks to build an app that uses AI to color black and white photos.