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 monthly digest


Scientists develop new method to generate protein datasets for training AI

AIHub

Protein engineering is a field primed for artificial intelligence research. Each protein is made up of amino acids; to optimize a protein function, researchers modify proteins by switching out one of 20 different amino acids for another. For a protein that is just 50 amino acids in length, this leads to approximately 1.13 10 potential combinations to test. This number of potential combinations, impossible to test in the lab, makes protein engineering an ideal challenge for AI. Modeling which of these combinations will give the best results is a perfect problem for the technology's massive computing power.


What's coming up at #RoboCup2026?

AIHub

This year, RoboCup will be held in Incheon, South Korea, from 2-6 July. The event will see teams take part in competitions, training sessions, and a symposium. It's an exciting time for RoboCup, as there have been some updates to the leagues and competition format . Most prominently, the soccer leagues will have a primary focus on humanoid robots. A workshop focused on sharing projects, experiences, and innovations in educational robotics.


AI model used to generate complete models of proteins in motion

AIHub

Many drug and antibody discovery pathways focus on intricately folded cell membrane proteins. When molecules of a drug candidate bind to these proteins, like a key going into a lock, they trigger chemical cascades that alter cellular behavior. Understanding how proteins fold and move is therefore essential for developing drugs that interact well with their targets. Artificial intelligence (AI) is a very useful tool to generate novel protein structures, but most systems - including Google DeepMind's AlphaFold - focus on producing static'snapshots' of proteins. Subtle rearrangements of atoms in structures called side chains, which influence a protein's interactions with other molecules, are not captured.


Three ways to avoid being fooled by AI slop

AIHub

Global society makes billions of images and uploads hundreds of thousands of hours of video on the internet every day. The problem is, some of this content is misleading or downright wrong. And when it's in visual form, it can be particularly convincing . Take the Met Gala that happened earlier this month in New York. While photographers snapped photos of Rhianna, Beyoncé and Nicole Kidman as they strutted their stuff, others saw "photos" of celebrities, such as Rosalía, Lady Gaga and Jacob Elordi, who were actually elsewhere (the images in the below Instagram carousel are AI generated).


Engineering Out Loud: S13E1 – How many robots can a single human supervise?

AIHub

Engineering Out Loud: S13E1 - How many robots can a single human supervise? Will swarms of autonomous aerial vehicles be able to aid humans in wildland firefighting or package delivery? Research summarized in a new paper in Field Robotics represents a big step towards realizing such a future. In this interview, Professor Julie A Adams describes the research showing that one person can supervise more than 100 autonomous ground and aerial robots. "Engineering Out Loud" is a podcast from the College of Engineering at Oregon State University.


AAAI presidential panel – AI agents

AIHub

The Future of AI Research report, published in March 2025, aims to clearly identify the trajectory of AI research in a structured way. The report was led by outgoing AAAI President Francesca Rossi and covers 17 different AI topics . Members of the report team, and other selected AI practitioners, are taking part in a series of video panel discussions covering selected chapters from the report. In the fifth discussion in the collection, the three panellists tackle the topic of AI agents. How multi-agent systems evolved from rule-based systems to complex cooperative frameworks built on generative AI, and what is really different in the modern notion of an agentic AI system.


Design tweaks promote responsible AI use for environmental protection, research shows

AIHub

Artificial intelligence systems that ask users to pause to consider AI's energy consumption and environmental impacts are likely to reduce unnecessary AI use, new research by Oregon State University suggests. The findings, published in Science Communication, are important as AI is already using electricity on scales that can be meaningfully compared to households, factories and towns. For example, the electricity needed to train a large language model would power 120 homes for a year, the researchers note; one AI-generated image has roughly the same energy cost as charging a smartphone. With about 85% of the world's energy still coming from fossil fuels, every megawatt-hour that can be carved from AI's electricity profile is significant, says the study's leader, Cheng "Chris" Chen of the OSU College of Liberal Arts. "Despite AI's substantial environmental impacts, information about those impacts is rarely disclosed or effectively communicated to everyday users of AI systems," said Chen, assistant professor in the School of Communication.


Congratulations to the #AAMAS2026 best paper award winners

AIHub

The AAMAS 2026 best paper awards were presented at the 25th International Conference on Autonomous Agents and Multiagent Systems, which took place from 25-29 May 2025 in Paphos, Cyprus. Lucy Smith is Senior Managing Editor for AIhub. Lucy Smith is Senior Managing Editor for AIhub. Eleanor Drage speaks with Tara Merk about how community-owned data centers could transform digital ownership and challenge the dominance of Big Tech. We find out more about multi-agent research for the allocation of scarce societal resources.


Forthcoming machine learning and AI seminars: June 2026 edition

AIHub

This post contains a list of the AI-related seminars that are scheduled to take place between 1 June and 31 July 2026. All events detailed here are free and open for anyone to attend virtually. Franco Accordino and Monika Lanzenberger (European Commission) The Digital Humanism (DIGHUM) Initiative The talk will be livestreamed on YouTube here . K Madhava Krishna (IIIT Hyderabad) Robotics Café The Google Meet link is here . Gianfranco Polizzi (University of Birmingham) Raspberry PI Sign up here to join.


The Good Robot podcast: the battle over data centres with Tara Merk

AIHub

Hosted by Eleanor Drage and Kerry McInerney, The Good Robot is a podcast which explores the many complex intersections between gender, feminism and technology. How can communities take back control of the digital infrastructure that powers everyday life? In this episode, Eleanor Drage speaks with Tara Merk about how community-owned data centers could transform digital ownership and challenge the dominance of Big Tech. The conversation explores alternative models of internet infrastructure that prioritize local empowerment, sustainability, and cooperative governance over corporate control. Drawing on examples from Germany's renewable energy sector and community-led initiatives, Merk reflects on how decentralized ownership models can create fairer and more environmentally responsible technological systems.