5253 search results found

  • Hermano
    I
    Krebs

    Principal Research Scientist
    Primary DLC
    Department of Mechanical Engineering

    Contact

    3-137
    (617) 253-8112
    hikrebs@mit.edu

    Assistant

    Katey Stewart
    (617) 253-5338
    kstew@mit.edu

  • 4.5.23-AI-Karaman

    April 5, 2023Conference Video Duration: 29:11
    Future of Aerial Vehicles Enabled by Agile Autonomy 

  • Ann
    M
    Graybiel

    Institute Professor
    Primary DLC
    Department of Brain and Cognitive Sciences

    Contact

    46-6133
    (617) 253-5785
    graybiel@mit.edu

  • George
    M
    Church

    HST Affiliated Faculty
    Primary DLC
    Harvard-MIT Program in Health Sciences and Technology

    Contact

    HARVARD_MS-000
    (617) 432-7562
    gchurch@genetics.med.harvard.edu

  • Bernardo
    Zacka

    Associate Professor of Political Science
    Primary DLC
    Department of Political Science

    Contact

    E53-429
    (617) 324-5652
    nardoz@mit.edu

  • 2024 MIT Digital Technology & Strategy Conference: Generative Models as a Data Source for AI Systems

    September 17, 2024Conference Video Duration: 44:17

    Generative Models as a Data Source for AI Systems

  • We'll Know It When We Sense It

    July 30, 2020MIT Faculty Feature Duration: 12:19

    Ariel Furst
    Assistant Professor of Chemical Engineering

  • Using Computational Tools for Molecule Discovery

    May 6, 2021MIT Faculty Feature Duration: 27:31

    Connor Coley
    Assistant Professor of Chemical Engineering

  • 10.25.23-Digital-Acemoglu

    October 25, 2023Conference Video Duration: 43:8
    Can We Have Pro-Human AI? 

  • Advanced Design and Manufacturing: Utilizing AI for Advanced Design

    October 10, 2024Conference Video Duration: 26:27
     
    Utilizing AI for Advanced Design
    Faez Ahmed
    ABS Career Development Assistant Professor, MIT Department of Mechanical Engineering
    Generative AI is reshaping many industries by offering innovative content-creation approaches. While tools like ChatGPT have proven effective in multimedia, their application in engineering faces unique challenges, such as maintaining precision under varying requirements. This talk will explore some of these challenges, with an emphasis on achieving designs that are innovative, feasible, and achieve high functional performance. We will examine case studies across various engineering disciplines, such as kinematic design.  Furthermore, we will explore how precision-focused generative AI can transcend mere mimicking statistical patterns to address performance, constraints, and innovation in engineering. The talk will show examples of AI-drive design co-pilots for engineering tasks, along with covering methods that effectively combine multimodal generative models with engineering optimization and tools, highlighting how this fusion augments the design process. The presentation will conclude by highlighting the broader impact of generative AI in facilitating design democratization and fostering rapid innovation across the engineering sector.