Pedro Sousa's preprint reports that replacing handcrafted terrain descriptors with Tessera satellite foundation model embeddings improves probabilistic weather downscaling, achieving better prediction…
Josh Millar of Imperial College London led an article published in GetMobile benchmarking micro-NPUs, ultra-low-power neural network accelerators found in low-cost chips such as ESP32-based boards and…
OpenUK's AI Openness report, published in July 2026, features a fireside chat with Anil Madhavapeddy on open foundation models like TESSERA, emphasizing that non-inspectable, non-reproducible models a…
Anil Madhavapeddy, a University of Cambridge computer scientist, examined a first-year PhD viva in the Faculty of Law on planetary infrastructure regulation and reported that 1.7 million low Earth orb…
Anil Madhavapeddy spoke at the CHIA annual conference in Cambridge on AI for science and career guidance for young scientists, and wrote up notes from the first Cloud-Native Geospatial Forum held in L…
Sir David Attenborough visited the Cambridge Conservation Initiative's 10th anniversary, while Andrew Balmford delivered the Royal Society Environment Prize lecture on sustainable high-yield farming. …
Developer Anil Madhavapeddy released ocaml-deepseek, an OCaml library that integrates DeepSeek's open-weight LLM directly into applications via a native inference engine, enabling local, dependency-fr…
The Tessera team released v1.1 of their geospatial embedding model, improving temporal stability and reducing noise in regions with sparse satellite observations. The update eliminates grid-like seams…
Developer Anil Madhavapeddy released TESSERA v1.1 and GeoTessera 0.9, improving temporal embeddings and S3+Zarr support, while also advancing io-uring libraries for OCaml. The updates address performa…
Sadiq Jaffer spoke about TESSERA at Cambridge's Pint of Science event, while Cambridge undergraduates Radhika Iyer and Oliver Fogelin completed dissertations applying TESSERA to conservation and build…
Researchers at Cambridge University used AI and a 20-petabyte geospatial model called TESSERA to help identify hedgehogs in images, leading to a BBC News article and a flurry of media appearances. The…