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Clinicians could be fooled by biased AI, despite explanations
  1. Clinicians could be fooled by biased AI, despite explanations

    Regulators pinned their hopes on clinicians being able to spot flaws in explanations of an AI model’s logic, but a study suggests this isn’t a safe approach.

  2. Understanding attention in large language models

    How do chatbots based on the transformer architecture decide what to pay attention to in a conversation? They’ve made their own machine learning algorithms to tell them.

  3. Biases in large image-text AI model favor wealthier, Western perspectives

    AI model that pairs text, images performs poorly on lower-income or non-Western images, potentially increasing inequality in digital technology representation.

  4. New energy

    Once derided as “forever 30 years away,” fusion energy has a new swagger. Will it last?

  5. Green chemistry award: Professor recognized for sustainable silicon metal production method

    Richard Laine is the academic category winner in a national EPA contest.

  6. Building Flint’s trust in its drinking water

    Even with lead service line replacement, the city’s water has issues that require public education.

  7. Building a chemical ‘GPT’ to help design a key battery component

    Taking inspiration from the word-predicting large language models, a U-M team is kickstarting an atom-predicting model with 200,000 node hours on Argonne’s Polaris.

  8. Choosing exoskeleton settings like a Pandora radio station

    Using a simple and convenient touchscreen interface, the algorithm learns the assistance preferences of the wearer.

  9. U-M’s MI-Hydrogen to participate in new Midwest hydrogen hub

    The U.S. Department of Energy announced today that the Midwest Alliance for Clean Hydrogen is selected as regional clean hydrogen hub.

  10. NASA advances U-M’s Mission Concept Study to photograph entire auroras from space

    Two satellites could join NASA’s fleet studying the Sun and its impacts on Earth’s magnetic field.