Evaluating LLMs for providing evidence-based information on conservation actions This is an idea proposed in 2025 as a good starter project, and is currently being worked on by Radhika Agrawal. It is co-supervised with Alec Christie and Sadiq Jaffer. We are building a Conservation Co-Pilot to improve worldwide conservation action through evidence-driven insights.
What might a Dame of the Realm, a Fellow of the Royal Society, the latest member of the UK Joint Nature Conservation Committee, and me all covet? That's right: a Junior Ranger badge from Shenandoah National Park! After an intense few days, Bill Sutherland, Julia P.G. Jones, EJ Milner-Gulland and I headed into nature to experience the spectacular landscapes of the Blue Ridge Mountains in Virginia and do some birding.
I spent a couple of days at the National Academy of Sciences in the USA at the invitation of the Royal Society, who held a forum on "Measuring Biodiversity for Addressing the Global Crisis". It was a packed program for those working in evidence-driven conservation: I was honoured to talk about our work on using AI to "connect the dots" between disparate data like the academic literature and remote observations at scale.
Josh Millar has just released the latest survey paper he lead on energy-aware approaches to optimise deep-learning training and inference on embedded devices, such as those benchmarked in "Benchmarking Ultra-Low-Power µNPUs" recently. Any comments, please do let any of us know!
Our paper on how the careful design of LLMs is crucial for expert-level evidence retrieval has been published today in PLOS One and is available fully open access! In a nutshell, we tested 10 LLMs with six different retrieval strategies on their ability to answer questions related to conservation, benchmarked against the Conservation Evidence database that has been hand-assembled by experts over the last two decades.
I joined Cambridge's loftily named Environment Sustainability Strategy Committee this academic year, and have attended a couple of meetings with the latest one being held today. While a lot of what goes on is intricately tied into the University's rather special governance structure and the complexity of the College system, there has been significant progress on making all of this more visible more widely.
In my earlier note about how AI should unite conservation, I talked about the robust debate ongoing within Cambridge about whether or not we're too "AI obsessed" and are losing track of our goals in the rush to adopt learning algorithms. Jacqueline Garget has written a brilliant roundup about how colleages like Sam Reynolds, Chris Sandbrook and Sadiq Jaffer in the CCI are leading conversations to make sure we advance with eyes wide open.
With the sunsetting of Equinix Metal I've also been migrating the Recoil machines over to new hosts in Mythic Beasts. This time around, rather than manually setting up services, I've turned to a nice new tool called Komodo which helps with deploying Docker containers across multiple servers. Unlike many other container management solutions, Komodo is refreshingly simple.
The BIOMASS forest mission satellite was successfully boosted into space a couple of days ago, after decades of development from just down the road in Stevenage. I'm excited by this because it's the first global-scale P-band SAR instrument that can penetrate forest canopys to look underneath. This, when combined with hyperspectral mapping will give us a lot more insight into global tree health.
I had a tremendous time participating in last year's horizon scan of AI and Conservation, which laid out the opportunities that technological progress from AI (a catchall phrase here) could bring to hard-working conservation practitioners.
Like many others, my website is under a constant barrage of crawling from bots. I need to figure out which one is hosing me, but I am also resisting having third-party trackers of any form. I took a look at hosting a Plausible instance as OCaml does, but it's yet another service to run and maintain.