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Evidence synthesis at the DEFRA science conference, TESSERA transcoding and building a new SPA, OpenStreetMap/DuckDB bindings in OxCaml, and early thoughts on vibecoding etiquette.
For Pi Day, I have implemented the same algorithm in both OCaml and OxCaml and compared the generated assembly and runtime performance.
How we restructured TESSERA's geospatial embeddings from millions of individual numpy files into sharded Zarr v3 stores for efficient HTTP streaming, enabling everything from single-pixel mobile lookups to regional-scale analysis with just a couple of range requests.
Following my previous CPU vs GPU post I started thinking about what the ONNX inference engine actually did and if it could be replicated in OxCaml with SIMD.
The UK government recently launched the Fuel Finder API, providing real-time pricing data for over 7,000 petrol stations across the country.
Visiting satellite production lines in Los Angeles, and why the questions have changed since 2022.
In a previous post, I compared the ONNX Runtime with PyTorch on the CPU and GPU. In this post, I take this to the extreme to see if a CPU can outpace the NVIDIA L4 GPU.
