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3889 search results found
  • November 14, 2024 ILP Faculty Feature

    Metallurgy Made New: Transforming a Branch of Science That is Thousands of Years Old

    C Cem Tasan

  • Cagri Hakan Zaman
    April 6, 2023 ILP Faculty Feature

    Telling Stories in Space

    Cagri Zaman

  • 04.02-04.24-Chile-Symposium-Elsa-Olivetti-Jeffrey-Grossman-QA

    April 4, 2024Conference Video Duration: 10:14

    Q&A with Elsa Olivetti and Jeffrey Grossman

  • 5.9.22-Energy-Welcome-Session-Introduction

    May 9, 2022Conference Video Duration: 10:2
    Robert Armstrong
    Director, MIT Energy Initiative (MITEI)
    Chevron Professor of Chemical Engineering, MIT Energy Initiative (MITEI)
  • 5.5.22-Efficient-AI-Song-Han

    May 5, 2022Conference Video Duration: 26:40
    Song Han
    Assistant Professor, Department of Electrical Engineering and Computer Science, MIT EECS
  • 2024 MIT R&D Conference: Track 6 - Quantum 2.0 - Compiling Machine Intelligence onto (Quantum) Optoelectronic Systems

    November 19, 2024Conference Video Duration: 19:7
    Compiling Machine Intelligence onto (Quantum) Optoelectronic Systems
    Dirk Englund
    Associate Professor, MIT Department of Electrical Engineering and Computer Science

    The world of quantum mechanics holds enormous potential to address unsolved problems in communications, computation, precision measurements, and machine learning/AI. Dr. Englund's QP-Group at MIT pursues experimental and theoretical research towards machine learning hardware and critical quantum technologies (computing, networking, sensing) by precision control of photons and atomic systems, combining techniques from atomic physics, optoelectronics, and modern semiconductor devices. In this talk, Dr. Englund will share some of the latest research conducted by his group at MIT and their potential applications.

  • Sili Deng
    September 8, 2021 ILP Faculty Feature

    Combustion tech pivots to clean energy future

    Sili Deng

  • Marzyeh Ghassemi Hero
    July 7, 2022 ILP Faculty Feature

    Updating the State of the Art

    Marzyeh Ghassemi

  • 2024 MIT R&D Conference: Track 5 - AI - Efficient Multi-modal LLM on the Edge

    November 19, 2024Conference Video Duration: 20:30
    Efficient Multi-modal LLM on the Edge
    Song Han
    Associate Professor, MIT Electrical Engineering & Computer Science Department
    This talk presents efficient multi-modal LLM innovations with algorithm and system co-design. I’ll first present VILA, a visual language model deployable on the edge. It is capable of visual in-context learning, multi-image reasoning, video captioning and video QA. Followed by SmoothQuant and AWQ for LLM quantization, which enables VILA deployable on edge devices, bringing new capabilities for mobile vision applications. Second, I’ll present StreamingLLM, a KV cache optimization technique for long conversation and QUEST, leveraging sparsity for KV cache compression.
  • April 7, 2008

    UAVs Helping a Human Supervisor Map An Area That Has Just Experienced a Chemical/Biological/Radiological/Nuclear (CBRN) Incident

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