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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 […]
Jamillah Knowles & Digit / Pink Office / Licenced by CC-BY 4.0 Yolanda Gil is a professor at the University of Southern California, where she also serves as Senior Director for major strategic AI and data science initiatives. From 2018 – 2020, she was president of AAAI. In her invited talk at AAAI 2026, she
#AAAI2026 invited talk: Yolanda Gil on improving workflows with AI Read More »
By Christina Dinh Nguyen, University of Toronto Cultural heritage is constantly under threat. In recent years, we’ve witnessed the destruction of museums, archives and libraries around the world — from wildfires in California to bombing in Gaza and wars in Ukraine and Iran. Meanwhile, book scientists are working tirelessly with an array of technologies —
By Zach Winn In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during the manufacturing process of products like steel, semiconductors, and solar cells to help improve strength, control electrical conductivity, optimize performance, and more. But even
IceMing & Digit / Stochastic Parrots at Work / Licenced by CC-BY 4.0 By Mayank Kejriwal, University of Southern California When a human says an event is “probable” or “likely,” people generally have a shared, if fuzzy, understanding of what that means. But when an AI chatbot like ChatGPT uses the same word, it’s not
‘Probably’ doesn’t mean the same thing to your AI as it does to you Read More »
In a landscape that can flip quickly from soaking up water to sending it downstream, small differences in how wet the wetlands are can be the difference between a manageable spring and a damaging flood. USFWS Mountain-Prairie, CC BY 4.0. By Ali Ameli, University of British Columbia In recent years, the Prairies have seen bigger
Water flow in prairie watersheds is increasingly unpredictable — but AI could help Read More »
By Landon Butler, Justin Singh Kang, Yigit Efe Erginbas, Abhineet Agarwal, Bin Yu, Kannan Ramchandran Understanding the behavior of complex machine learning systems, particularly Large Language Models (LLMs), is a critical challenge in modern artificial intelligence. Interpretability research aims to make the decision-making process more transparent to model builders and impacted humans, a step toward
Simulated Large Hadron Collider CMS particle detector data depicting a Higgs boson produced by colliding protons decaying into hadron jets and electrons. Reproduced under a CC BY-SA 3.0 licence. Daniel Whiteson is a particle physicist, who uses machine learning and statistical tools to analyze high-energy particle collisions. He is also a dedicated science communicator, having
#AAAI2026 invited talk: machine learning for particle physics Read More »
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 delved into the history of RoboCup, learned about time series, studied multiplicity, and found out more about Theory of Mind. Manuela Veloso on the history
AIhub monthly digest: March 2026 – time series, multiplicity, and the history of RoboCup Read More »
We’re excited to launch our new series, where we’ll be speaking with leading researchers to explore the breakthroughs driving AI and the reality of the future promises – to give you an inside perspective on the headlines. Our first interviewee is Ross King, who created the first robot scientist back in 2009. He spoke to
