NEWS    Anoop Cherian gives a podcast interview with AI Business

Date released: November 10, 2023


  •  NEWS    Anoop Cherian gives a podcast interview with AI Business
  • Date:

    September 26, 2023

  • Where:

    Virtual

  • Description:

    Anoop Cherian, a Senior Principal Research Scientist in the Computer Vision team at MERL, gave a podcast interview with award-winning journalist, Deborah Yao. Deborah is the editor of AI Business -- a leading content platform for artificial intelligence and its applications in the real world, delivering its readers up-to-the-minute insights into how AI technologies are currently affecting the global economy and society. The podcast was based on the recent research that Anoop and his colleagues did at MERL with his collaborators at MIT; this research attempts to objectively answer the pertinent question: are current deep neural networks smarter than second graders? The podcast discusses shortcomings in the recent artificial general intelligence systems with regard to their capabilities for knowledge abstraction, learning, and generalization, which are brought out by this research.

  • External Link:

    https://aibusiness.com/ml/mitsubishi-scientist-are-deep-neural-networks-smarter-than-second-graders-

  • MERL Contact:
  • Research Areas:

    Artificial Intelligence, Computer Vision, Machine Learning

    •  Cherian, A., Peng, K.-C., Lohit, S., Smith, K., Tenenbaum, J.B., "Are Deep Neural Networks SMARTer than Second Graders?", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), March 2023, pp. 10834-10844.
      BibTeX TR2023-014 PDF Data Software Presentation
      • @inproceedings{Cherian2023mar,
      • author = {Cherian, Anoop and Peng, Kuan-Chuan and Lohit, Suhas and Smith, Kevin and Tenenbaum, Joshua B.},
      • title = {Are Deep Neural Networks SMARTer than Second Graders?},
      • booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2023,
      • pages = {10834--10844},
      • month = mar,
      • publisher = {CVF},
      • url = {https://www.merl.com/publications/TR2023-014}
      • }