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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 »
Task construction as the control surface in continued pretraining. A construction rule maps each unlabeled example into a self-supervised prediction problem , such as one-hot next-token prediction in language modeling or paired views and targets in DINO-style vision SSL. Standard continued pretraining fixes this rule before training, whereas V-pretraining replaces it with a feedback-trained designer
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Adaptive parallel reasoning: the next paradigm in efficient inference scaling Read More »
The process of generating protein activity data (top) and reading the output and training AI models (bottom). Credit: Linqi Cheng/Rice University. By Rachel Leeson 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
Scientists develop new method to generate protein datasets for training AI Read More »
A simulated protein backbone (yellow) augmented with AI-generated snapshots. Image credit: LPCS LTS2 EPFL CC BY SA. By Celia Luterbacher 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
AI model used to generate complete models of proteins in motion Read More »
