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  • Ecosystem-2018
    Tue, May 15, 2018 | Conference

    2018 MIT Startup Ecosystem - Innovating in AI, Data, and Hard Tech

    MIT Campus

    The annual MIT Startup Ecosystem Conference features 25 of the most promising startups from across MIT. These startups are all part of STEX25, an accelerator run by MIT Startup Exchange, an integrated program of MIT Corporate Relations.

  • Past Deadline: Apr 30, 2019

    Brazil's Retail Giant seeks Startups for Sao Paulo Conference

    speaker

    B2W/LASA - Brazil's major retailer (e-commerce, brick&mortars, and marketplace) seeks 3-4 startups to present at its two-day marketplace conference in Sao Paulo -- July 4-5th.

  • Past Deadline: Jan 20, 2025

    Presentation opportunity on Smart Cities & Urban Development webinar

    speaker

    The MIT Startup Exchange team is seeking 3 startups to present on the MIT’s Leading Edge Webinar - Smart Cities & Urban Development. 

  • Andy Wang

    5.5.22-Efficient-AI-Prescient

    May 5, 2022 | Startup Exchange Video | Duration: 4:37
    Edge-to-cloud data automation
  • Julie Choi

    5.5.22-Efficient-AI-MosaicML

    May 5, 2022 | Startup Exchange Video | Duration: 4:53
    Making ML training efficient
  • Di Wu

    5.5.22-Efficient-AI-OmniML

    May 5, 2022 | Startup Exchange Video | Duration: 5:19
    Get smaller and faster ML models
  • Mark Tibbetts

    5.5.22-Efficient-AI-Arundo

    May 5, 2022 | Startup Exchange Video | Duration: 5:12
    Automatic data extraction and digitization of industrial diagrams
  • 5.5.22-Efficient-AI-UbiCept

    May 5, 2022 | Startup Exchange Video | Duration: 3:54
    Computer vision in challenging scenarios
  • Matt Cherewka headshot

    4.5.23-AI-Vecna-Robotics

    April 5, 2023 | Startup Exchange Video | Duration: 4:35
    Robotics Startup for Autonomous Forklifts
  • Breaking down bias in AI applications

    August 2, 2022 | Startup Exchange Video | Duration: 9:57

    Applications built on machine learning algorithms are entrenching themselves everywhere, but they often bring major weaknesses that aren't discovered until after they are deployed.

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