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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 […]
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
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
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,
How can we characterize consensus in a network of agents? Read More »
Marcin Wilkowski / AI paper mills / Licenced by CC-BY 4.0 By Nan Li, University of Wisconsin-Madison A photograph of Earth glowing in deep space, the Moon’s cratered horizon stretching across its foreground, caught many people’s eyes in April 2026. Astronauts captured the image while aboard NASA’s Artemis II mission, and like the famous Apollo
Imagine you want to teach a robot to push an object on a table. The standard recipe in robot learning is to collect hundreds of expert demonstrations on a real robot, train an imitation learning policy on that data, and then evaluate the policy by running it many times on the same real robot. Both
Interactive World Simulator for Robot Policy Training and Evaluation Read More »
Large language models (LLMs) are designed to generate answers to user prompts, which often drives them to respond even when uncertainty is high, information is incomplete, or a refusal would be more appropriate. In healthcare, this tendency can be dangerous: confidently stated but inaccurate medical advice can cause significant harm, making the ability to abstain
By Aimee Levitt In brief People often make decisions through “satisficing,” gathering just enough information to make a satisfactory prediction of a likely outcome. A series of experimental games shows that people also employ satisficing to learn social rules and conventions. This finding offers new insight into social learning and reveals a key difference between
The secret to human ‘brilliance’ that AI just can’t match Read More »
Systems for diagnosis, prognosis and imaging have repeatedly been deployed or promoted on the strength of performance that proved fragile under independent testing. A model that performs well in the hospital where it was born has proven only one thing: that it works at home. Consider the most instructive failure in recent clinical AI. The
External validation is not a bureaucratic detail Read More »
In 2019, a research team led by the physician and economist Ziad Obermeyer reverse-engineered a commercial algorithm already running quietly across the United States health system. The tool, sold by Optum, helped decide which patients — out of a population of roughly 200 million a year — would be flagged for extra medical attention. To
A medical algorithm must not confuse cost with health Read More »
