Interview with Yezi Liu: Trustworthy and efficient machine learning

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In this interview series, we’re meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. Yezi Liu is working on trustworthy and efficient machine learning. We asked her about her research to date, what she has found particularly interesting, plans for future work, and what is was that inspired her to study AI. Tell us … Read More

Advanced AI models are not always better than simple ones

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Elise Racine / Toy Models I / Licenced by CC-BY 4.0 By Tanya Petersen Understanding genetic perturbations, when scientists intentionally alter genes to see how this affects cells, is key to understanding what our genes do and how they are controlled. This knowledge has important applications in cell engineering and in developing new treatments. Today, scientists can test many different … Read More

The Machine Ethics podcast: Autonomy AI with Adir Ben-Yehuda

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Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology’s impact on society. Autonomy AI with Adir Ben-Yehuda This episode Adir and I chat about Autonomy.ai – AI automation for frontend web development, where human-machine interface could be going, … Read More

Using generative AI, researchers design compounds that can kill drug-resistant bacteria

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Alan Warburton / Medicine / © BBC. By Anne Trafton With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research team designed more than 36 million possible compounds and computationally screened them for antimicrobial properties. The top candidates they … Read More

#IJCAI2025 distinguished paper: Combining MORL with restraining bolts to learn normative behaviour

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Image provided by the authors – generated using Gemini. For many of us, artificial intelligence (AI) has become part of everyday life, and the rate at which we assign previously human roles to AI systems shows no signs of slowing down. AI systems are the crucial ingredients of many technologies — e.g., self-driving cars, smart urban planning, digital assistants — … Read More

#ICML2025 outstanding position paper: Interview with Jaeho Kim on addressing the problems with conference reviewing

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At this year’s International Conference on Machine Learning (ICML2025), Jaeho Kim, Yunseok Lee and Seulki Lee won an outstanding position paper award for their work Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards. We hear from Jaeho about the problems they were trying to address, and their proposed author feedback mechanism and reviewer reward system. … Read More

AIhub monthly digest: August 2025 – causality and generative modelling, responsible multimodal AI, and IJCAI in Montréal and Guangzhou

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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 dive into the world of agents, learn about responsible multimodal AI, apply generative AI to computer networks, and dig into the RoboCup@Work League. Agentic AI The AIhub coffee corner captures … Read More

Interview with Benyamin Tabarsi: Computing education and generative AI

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In this interview series, we’re meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. In this latest interview, Benyamin Tabarsi tells us about his research at the intersection of generative AI and computing education. We find out more about what he’s investigated so far during his PhD, what is particularly interesting about this research … Read More