Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we learn about AI for science, delve into world models, research transparent and trustworthy AI, and hear about the lottery ticket hypothesis.
The latest interview in our series with the AAAI/SIGAI Doctoral Consortium participants featured Ximing Wen who is researching transparent and trustworthy AI systems. We found out more about her work, her experience as a research intern, and what inspired her to study AI.
In this wide-ranging conversation, Jonathan Frankle delves into empiricism versus theoretical proofs, how the approach to computer science has changed (even if the fundamental problems haven’t), how younger researchers are rapidly adapting to a world that values impact above all else, and what it means to be a researcher.
On 31 March, our editorial team headed to the Royal Society for AI for Science. This day-long conference explored how AI is changing the nature of scientific discovery, and was hosted by the Fundamental Research team from the Alan Turing Institute. Ella Scallan summarised the day and invited talks in this write up.
The AIhub coffee corner captures the musings of AI experts over a short conversation. This month we delve into world models. What are they, and what potential do they have? Joining the conversation this time are: Sanmay Das, Rina Dechter, Tom Dietterich, Sabine Hauert, Michael Littman, and Marija Slavkovik.
Partnership on AI has published a progress report on post-deployment governance practices pertaining to foundation models. The document, entitled 2026 Transparency Report on Foundation Model Impacts, measures the progress of 13 foundation model providers in publicly documenting the impacts of their foundation models.
The 2025 conference on artificial intelligence, ethics and society (AIES) took place in the north of Madrid within the 180m-high tower block that forms the vertical campus of IE University. In this piece, we reflect on the three-day event, and outline the conversations and presentations from a discussion session on LLMs in the context of clinical usage and human rights.
The recently launched Robotics Café is a weekly online seminar series that brings together researchers, students and industry practitioners working in the field of autonomous robotics. Scheduled every Thursday, the talks are available to watch live or later as YouTube recordings. So far, the talks have covered robots catching objects in the air, and predictive uncertainty for model-based planning and control.
The Association for Computational Linguistics (ACL) have announced that they will be desk rejecting papers with hallucinated references for their forthcoming annual conference. During the final checks of the camera-ready versions of papers accepted to ACL 2026, the organisers identified over 100 papers that contained citations to non-existent literature. They made the decision to desk-reject these accepted papers to maintain the quality and trustworthiness of the conference proceedings.
In a related move, the pre-print server arXiv is introducing a policy to deal with AI slop generated by large language models (LLMs). Authors will receive a one-year ban if there is incontrovertible evidence that they have used generative AI and not checked the results. For example, hallucinated references or meta comments from the LLM.
You may remember The Wizard of AI, a video essay from Alan Warburton, released in 2023. Alan has again teamed up with the Open Data Institute (ODI) to produce another short film, entitled Image Empire. An accompanying field guide unpacks the content of the film and is tailored for use in educational and organisational contexts.
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