Excited for three Fluid presentations coming up: Fluid: Towards Transparent, Explorable Research Outputs rsecon25.society-rse.org Language-Based Dependency Tracking for Explorables liveprog.org Authoring Tools for Transparent Climate Reporting conf.researchr.org/home/icfp-sp...

👀 Fancy a summer internship working at the intersection of programming languages, AI/ML and HCI, working on a new language being developed at ICCS for open climate science communication? See @f.luid.org and www.epsrc.group.cam.ac.uk/DTP/internsh... for more information. ⏰ Deadline Fri 14 March!

Landing page now loads ~5 times faster thanks to a nice PR from Jacob Pake: f.luid.org

The Institute of Computing for Climate Science (ICCS) has moved to Bluesky: @iccscambridge.bsky.social

Come join us in Cambridge! 2 new EPSRC-funded residental undergraduate internships available this summer, working alongside our DeepMind interns at the intersection of PL, AI/ML and HCI. Deadline 14 March. More at f.luid.org/student-proj.... Apply here: www.epsrc.group.cam.ac.uk/DTP/internsh....

@dynamicaspects.org presented Fluid at last week’s Virtual Earth System Research Institute journal club. Talk available at www.youtube.com/watch?v=5KUW... www.schmidtsciences.org/virtual-eart...

This poster provides a bit of context for our two DeepMind summer internships: an AI “authoring assistant” (for writing text with embedded Fluid computations), and an AI “reading assistant” (for turning provenance traces into natural language explanations). www.cst.cam.ac.uk/outreach/dee...

Interested in a working on AI for transparent science communication? We have two Google DeepMind internships available to develop AI-based tooling for Fluid. These are fully residential and in collaboration with Institute of Computing for Climate Science, Cambridge. www.cst.cam.ac.uk/outreach/dee...

New paper (accepted to ESOP 2025) “Cognacy Queries over Dependence Graphs for Transparent Visualisations”, with Joe Bond, Cristina David, Minh Nguyen and @dorchard.bsky.social. arxiv.org/abs/2403.04403

Matrix convolution example, running with our new dependence-graph implementation of Fluid. Output interactions highlights inputs cells being consumed; input interactions highlight output cells that consume that input. 50-80x speedup vs. the previous implementation! ⏩⏩