The IETF announced their new AI Preferences Working Group (AIPREF), which will "work on standardizing building blocks that allow for the expression of preferences about how content is collected and processed for Artificial Intelligence models" . This is quite well timed; the IETF tries not to standardise too early before there is running code but also needs to move before it's too late and a bad defacto standard is chosen.

This week I've been reading three really nice pieces of work by my colleagues, in the form of a review paper on biodiversity and AI, a benchmark for 3D forest reconstruction using laser scanners and a mobile app for measuring the width of tree trunks. A real bonanza for forest lovers!

Over the past year, Sadiq Jaffer and I have been getting an object lesson in how the modern Internet handles researcher access to data, as we've been downloading tens of millions of research papers towards our Conservation Evidence project.

We've uploaded a revised preprint on our ongoing work on quantifying the biodiversity cost of global food consumption, lead by Thomas Ball. This is based on the recently published LIFE metric, combined with supply chain data and provenance modeling.

Carl Edward Rasmussen recently gave a great talk in our group about his thoughts on mechanisms against climate change. He persuasively argued that the Paris Agreement was doing more harm than good by giving the illusion of being a concrete agreement, but is in reality a huge distraction. Our actual emissions have increased since the Paris agreement was signed!

While Bluesky is taking off like a rocket, a number of us moving towards self sovereign digital infrastructure have been looking at how to use the Bluesky network for other uses than just short-form notes. This is possible because of my colleague Martin Kleppmann's hard work on the "AT Protocol" that underpins the Bluesky network.

With the vast amount of data we have these days for our planetary computing processing, it's naturally tempting to use more hardware offload. The obvious choice, GPGPUs, are not a great fit for the problem due to the difficulty of unlocking high data parallelism for geospatial data. So it's back to an old technology I worked on twelve years ago in the form of FPGAs!

We've been happy users of Matrix for our group communications in the EEG. Today we've been bringing in more members of the wider group to using it instead of Slack. As part of that, I've set up a cool bot called Hookshot which allows Matrix to be connected to external services such as GitHub and Atom/RSS feeds. This is a test post to demonstrate to the members of the EEG how Matrix and Atom work!

Sadiq Jaffer sent along this piece in The Conversation last week about the remarkable number of academic papers that are now AI generated. The numbers of these papers are probably underestimated: What caught my eye in this article is their development of the Problematic Paper Screener, which the good folks at Retraction Watch developed. It works with high precision to detect papers issued by grammar-based generators.

There's a letter in Science today from a bunch of well known remote sensing researchers that make the unusual point that modern satellite resolution is getting too good to be accurate for forest carbon estimation. The lead author Laura Duncanson is a remote sensing scientist at Maryland who works on the incredible GEDI instrument on the International Space Station.

The terms carbon credits and carbon offsets are often used interchangeably, but are in fact two distinct concepts. I've spent a nice Sunday morning reading up on some recent articles that Bhaskar Vira sent me which introduce a third term, known as "carbon contributions" . Rather than this adding confusion, I found it helped me clarify my own thoughts on the matter, which I note down here in draft form.