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How generative AI and physics can help design new antibiotics

ai, AI (Artificial Intelligence), articles, Artificial Intelligence

Physics-based simulations can help identify which peptide antibiotics can kill a bacteria like E. coli, pictured here using electron microscopy. (Nurgul D / Wikimedia Commons) CC BY-SA 4.0. By Rachael (Ré) A Mansbach, Concordia University and Jyler Menard By 2050, scientists estimate that antibiotic-resistant infections will be associated with more than eight million deaths around […]

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CogTwin: A framework for adaptable digital twins

ai, AI (Artificial Intelligence), articles, Artificial Intelligence, IJCAI, IJCAI2026

CogTwin is a hybrid cognitive architecture framework designed to bring autonomous reasoning and real-time adaptation to digital twin systems. Presented at IJCAI 2025, this work aims to advance the state of digital twin technology by addressing key gaps in autonomy, cognition, and real-time decision-making. The problem landscape: shifting digital twins from reactive to proactive systems

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A number with no recorded reason may end up deciding for a patient

ai, AI (Artificial Intelligence), articles, Artificial Intelligence, By the Director, Channels, Educación | 🇬🇧 Education, English, English (Articles), InsidetheRss, Investigación | 🇬🇧 Research, Medicina | 🇬🇧 Medicine, Outside The wall, Post, State-Art (Article)

Transparency in artificial intelligence has become a question of provenance. Provenance tells you where a piece of content came from; it does not tell you why what it asserts was decided.

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Healthcare benchmarks are only as good as their assumptions

ai, AI (Artificial Intelligence), articles, Artificial Intelligence, deep dive

In healthcare settings where patients use LLMs as a medical assistant, LLM performance differs between evaluation and deployment. (a) Bean et al. (2025) find a 61 percentage point difference between evaluation and deployment. (b) We argue this gap arises not from poorly designed benchmarks, but from implicit assumptions embedded in evaluation protocols that fail to

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This image shows an individual with orange hair interacting with a large, abstract digital mirrored structure. The structure is composed of squares in varying shades of green, orange, white, and black which are pieced together to reflect the individual’s figure. The figure

Humans trained to spot AI faces in the battle against deepfake fraud

ai, AI (Artificial Intelligence), articles, Artificial Intelligence

Yutong Liu & Kingston School of Art / Talking to AI 2.0 / Licenced by CC-BY 4.0 Humans have been successfully trained to spot AI-generated faces in a study led by researchers at the Australian National University (ANU) Emotions and Faces Lab. AI-generated deepfake faces have become so realistic that it is difficult for people

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AIhub monthly digest: July 2026 – time-series anomaly detection, music generation, and RoboCup in action

AAAI, ACM SIGAI, ai, AI (Artificial Intelligence), articles, Artificial Intelligence, EurAI, ICML, IJCAI, monthly digest, RoboCup

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 find out about time-series anomaly detection, delve into music generation, honour award winners, and catch up on the action from the RoboCup humanoid soccer league.

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There are 16 different small square images in this collage. Each of them have a grid background and different neon coloured square patterns in the squares. One looks like a flower, another looks like a random array of pixels, and the other is 4 blue squares.

OpenAI’s models autonomously hacked a tech startup. It signals a seismic shift in cybersecurity

ai, AI (Artificial Intelligence), articles, Artificial Intelligence

Elise Racine / Game of Pixels x Toy Models / Licenced by CC-BY 4.0 By Hussein Abbass, UNSW An autonomous agent powered by OpenAI’s advanced artificial intelligence (AI) models went rogue during a security test and hacked multi-billion dollar tech startup, Hugging Face, last week. The agent didn’t just exploit vulnerabilities in Hugging Face’s systems

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Towards experiment-guided AlphaFold

ai, AI (Artificial Intelligence), articles, Artificial Intelligence

ISTA researchers guide AlphaFold with experimental data, paving the way for improved future predictive models. Left to right: Advaith Maddipatla, Meital Bojan, Alex Bronstein, Nadav Sellam Bojan, and Paul Schanda. © ISTA. The AI-based program AlphaFold predicts a protein’s 3D structure with remarkable accuracy. However, it tends to reduce heterogeneous structures to a single dominant

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AI listens in to help protect wildlife

ai, AI (Artificial Intelligence), articles, Artificial Intelligence, Focus on life on land, Focus on UN SDGs

By Michael Allen Strolling through a forest, you may notice that the air is filled with sound. Birds sing, insects and small mammals rustle through the undergrowth, and at dusk bats squeak as they communicate with each other. These soundscapes contain a wealth of information about which animals are present, how many there are and

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How can we characterize consensus in a network of agents?

AAMAS, ai, AI (Artificial Intelligence), articles, Artificial Intelligence

A schematic Belief Flow Network: agents exchange beliefs along directed influence links, and the research asks which final consensus beliefs can emerge. Imagine a set of artificial agents, expert systems, or decision-makers, each beginning with their own “beliefs” about a shared situation. For example, one transport agent may believe that there is a train strike,

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