If AI continues to evolve--as it surely will--so too will the labels attached to those who work in it.

Digital Health Technologies (DHTs) including consumer wearable devices and digital health applications offer an opportunity for continuous, large-scale data collection. Wearables give insight into physiological biomarkers that help us understand the human body, through passive data collection. Such data can be collected at a regularity that would be impossible otherwise. Digital health applications provide the chance to collect diverse types of data from clinically validated surveys, GPS, and contextual inputs. This combination has the ability to make profound advances in our understanding of the factors that affect individuals on a personal and population level [Grace et al., 2025]. One of these factors is the menstrual cycle. Particularly because of its inter-individual variability, studying it requires large sample sizes, and to truly grasp its effects on the human body, it needs to be observed on a near-daily scale [Bull et al., 2019].

Moreoever, we develop estimation theory providing tight control on the error of any estimated trajectory, indicating that the representations could even be used in quite noise-sensitive follow-on analyses.

This allows for local interpretation of the agent's intention based on its behavioural policy.

Here we provide additional qualitative comparison of segmentation results and CM visualization results on MNIST and MS datasets. We examine the ability of our method to learn the CMs of annotators and the true label distribution on single label per image.

West Somerset Lagoon would harness renewable energy for UK's AI boom - and create'iconic' arc around Bristol Channel The architect of the London Eye wants to build a vast tidal power station in a 14-mile arc off the coast of Somerset that could help Britain meet surging electricity demand to power artificial intelligence - and create a new race track to let cyclists skim over the Bristol Channel. Julia Barfield, who designed the Eye and the i360 observation tower in Brighton, is part of a team that has drawn up the £11bn proposal. The proposal comes amid growing concern that rapidly rising use of AI in Britain will drive up carbon emissions unless more renewable energy sources are found. The AI boom is expected to add to sharp increases in demand for electricity across the UK, which the government estimated this month could more than double by 2050. "If the decision is to go ahead with adopting more and more AI - which I am surprised is not being questioned more at a time of climate emergency - then it is going to be better with a renewable energy source," said Barfield.