Simon Willison

Video compressor

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Simon Willison created a video compressor tool that uses the WebAssembly build of FFMPEG to optimize a demo video of his Equal Earth animation recorded on his phone. He employed Claude Fable 5.1 in Claude Code for web to generate the tool, enabling him to publish the optimized video on his blog. The project showcases how modern web technologies can streamline video processing workflows.

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Google AI Blog
Feb 23, 2024

VideoPrism: A foundational visual encoder for video understanding

Posted by Long Zhao, Senior Research Scientist, and Ting Liu, Senior Staff Software Engineer, Google Research An astounding number of videos are available on the Web, covering a variety of content from everyday moments people share to historical moments to scientific observations, each of which contains a unique record of the world. The right tools could help researchers analyze these videos, transforming how we understand the world around us.

By Google AI
Simon Willison
Sep 13

shot-scraper 1.12

Shot‑scraper 1.12 adds WebP support, allowing users to capture web page screenshots in WebP format with an optional quality setting. The new --quality flag controls compression, while omitting it produces lossless images. WebP screenshots are reported to be significantly smaller than JPEG or PNG equivalents.

Simon Willison
Sep 7

Mercator ↔ Equal Earth

Simon Willison created an animated transition tool that morphs a map from the Mercator projection to the Equal Earth projection using D3. The project was inspired by the recent UN vote on the Equal Earth map projection and was built with GPT‑6 Astra (medium) in ChatGPT Work. It showcases how modern AI and web technologies can visualize complex geospatial transformations.

Google AI Blog
Jan 31, 2024

MobileDiffusion: Rapid text-to-image generation on-device

Posted by Yang Zhao, Senior Software Engineer, and Tingbo Hou, Senior Staff Software Engineer, Core ML Text-to-image diffusion models have shown exceptional capabilities in generating high-quality images from text prompts. However, leading models feature billions of parameters and are consequently expensive to run, requiring powerful desktops or servers (e.

By Google AI
Simon Willison
Sep 2

llm 0.34

The release of llm 0.34 introduces a new feature that enhances log output by including response duration in both milliseconds and a human‑readable format. The short log view now contains a dedicated duration_ms field. Additionally, the update incorporates multiple bug fixes and a notable performance boost to llm logs, attributed to waveplate integration.