• A technique to estimate emotional valence and arousal by analyzing images of human faces

    Credit: CC0 Public Domain In recent years, countless computer scientists worldwide have been developing deep neural network-based models that can predict people’s emotions based on their facial expressions. Most of the models developed so far, however, merely detect primary emotional states such as anger, happiness and sadness, rather than more subtle aspects of human emotion. Past psychology research, on the other hand, has delineated numerous dimensions of emotion, for instance, introducing measures such as valence (i.e., how positive an emotional display is) and arousal (i.e., how calm or excited someone is while expressing an emotion). While estimating valence and arousal simply by looking at people’s faces is easy for most…

  • Researchers develop a system that can recommend personalized and healthy recipes

    Figure summarising the researchers’ personalized food recommendation architecture: Given a user query in natural language, along with the user’s context (comprising dietary preferences and health guidelines), the system finds top-ranked and personalized answers from the FoodKG food knowledge graph. QE, KA and CM stand for Query Expansion, Knowledge Graph Augmentation and Constraint Modeling, respectively. Positive constraints are in red, negative constraints in gray, and non-constraints in black. KBQA refers to the underlying knowledge graph question answering system. Credit: Chen et al. Researchers at Rensselaer Polytechnic Institute and IBM Research in New York have recently created pFoodReQ, a system that can recommend recipes tailored around the preferences and dietary needs of…

  • New approach to AI offers more certainty in the face of uncertainty

    Credit: Pixabay/CC0 Public Domain A new method to reason about uncertainty might help artificial intelligence to find safer options faster, for example in self-driving cars, according to a new study to be published shortly in AAAI involving researchers at Radboud University, the University of Austin, the University of California, Berkeley, and the Eindhoven University of Technology. The researchers have defined a new approach to so-called ‘uncertain partially observable Markov decision processes,” or uPOMDPs. In layman’s terms, these are models of the real world that estimate the probability of events. A self-driving car, for example, will face many unknown situations when it starts driving. To validate the artificial intelligence of self-driving…

  • When a story is breaking, AI can help consumers identify fake news

    Credit: CC0 Public Domain Warnings about misinformation are now regularly posted on Twitter, Facebook, and other social media platforms, but not all of these cautions are created equal. New research from Rensselaer Polytechnic Institute shows that artificial intelligence can help form accurate news assessments—but only when a news story is first emerging. These findings were recently published in Computers in Human Behavior Reports by an interdisciplinary team of Rensselaer researchers. They found that AI-driven interventions are generally ineffective when used to flag issues with stories on frequently covered topics about which people have established beliefs, such as climate change and vaccinations. However, when a topic is so new that people…

  • AI trained to read electric vehicle charging station reviews to find infrastructure gaps

    This graphical abstract shows how AI can be used to improve electric vehicle charging station infrastructure. Credit: Ha et al./Patterns Although electric vehicles that reduce greenhouse gas emissions attract many drivers, the lack of confidence in charging services deters others. Building a reliable network of charging stations is difficult in part because it’s challenging to aggregate data from independent station operators. But now, researchers reporting January 22 in the journal Patterns have developed an AI that can analyze user reviews of these stations, allowing it to accurately identify places where there are insufficient or out-of-service stations. “We’re spending billions of both public and private dollars on electric vehicle infrastructure,” says…

  • Designing customized ‘brains’ for robots

    MIT researchers have developed an automated way to design customized hardware, or “brains,” that speeds up a robot’s operation. Credit: Jose-Luis Olivares, MIT Contemporary robots can move quickly. “The motors are fast, and they’re powerful,” says Sabrina Neuman. Yet in complex situations, like interactions with people, robots often don’t move quickly. “The hang up is what’s going on in the robot’s head,” she adds. Perceiving stimuli and calculating a response takes a “boatload of computation,” which limits reaction time, says Neuman, who recently graduated with a Ph.D. from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). Neuman has found a way to fight this mismatch between a robot’s “mind”…