Author name: Lucy Smith

AAAI, AAAI Doctoral Consortium, AAAI2026, ACM SIGAI, opinions

Making AI systems more transparent and trustworthy: an interview with Ximing Wen

The latest interview in our series with the AAAI/SIGAI Doctoral Consortium participants features 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. Tell us a bit about your PhD – where are you studying, […]

News, quick read

Report on foundation model impacts released

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. In carrying out their analysis, authors Jacob Pratt and Albert Tanjaya reviewed […]

education

Forthcoming machine learning and AI seminars: May 2026 edition

This post contains a list of the AI-related seminars that are scheduled to take place between 5 May and 30 June 2026. All events detailed here are free and open for anyone to attend virtually. 5 May 2026 Perspectives after the MUSAiC Project Speaker: Bob L. T. Sturm (KTH Royal Institute of Technology) Organised by: […]

AAAI, ACM SIGAI, articles, monthly digest

AIhub monthly digest: April 2026 – machine learning for particle physics, AI Index Report, and table tennis

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 meet PhD students and early-career researchers, find out how machine learning is used for particle physics discoveries, cast an eye over the latest AI Index […]

AAAI, AAAI Doctoral Consortium, AAAI2026, ACM SIGAI, opinions

Interview with Deepika Vemuri: interpretability and concept-based learning

The latest interview in our series with the AAAI/SIGAI Doctoral Consortium participants features Deepika Vemuri who is working on interpretability and concept-based learning. We found out more about the two aspects of concept-based models that she’s been researching. Could you tell us a bit about your PhD – where are you studying, and what is […]

News

Sony AI table tennis robot outplays elite human players

Ace rotates its paddle as it prepares to return the ball back to its human opponent, Yamato Kawamata, during a match in December 2025. Credit: Sony AI. In an article published today in Nature, Sony AI introduce Ace, the first robot to beat elite human players in competitive physical sport. Although AI systems have shown […]

AAAI, AAAI Doctoral Consortium, AAAI2026, ACM SIGAI, opinions

Interview with Xinwei Song: strategic interactions in networked multi-agent systems

In this interview series, we’re meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. We hear from Xinwei Song about the two main research threads she’s worked on so far, plans to expand her investigations, and what inspired her to study AI. Could you start with a quick introduction […]

AAAI, AAAI Doctoral Consortium, AAAI2026, ACM SIGAI, opinions

Formal verification for safety evaluation of autonomous vehicles: an interview with Abdelrahman Sayed Sayed

In this interview series, we’re meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. We sat down with Abdelrahman Sayed Sayed to chat about his work on formal verification applied to autonomous vehicles. Could you tell us a bit about where you’re studying and the broad topic of your […]

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