Brenda Rubenstein | Storage and Computation Using Small Molecules and Their Reaction Networks

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  • เผยแพร่เมื่อ 4 ก.ค. 2024
  • Apply to join Foresight Molecular Machines program: foresight.org/molecular-machi...
    A group of scientists, entrepreneurs, and institutional allies who cooperate to advance molecular machines, applications in energy, medicine, and material science, and long-term progress toward Richard Feynman’s vision of nanotechnology.
    Brenda Rubenstein | Computing with Molecules: Storage and Computation Using Small Molecules and Their Reaction Networks
    As transistors near the size of molecules, computer engineers are increasingly finding
    themselves asking a once idle question: how can we compute using chemistry? In this talk, I
    will discuss recent progress my Brown Molecular Informatics team and I have made
    demonstrating how mixtures of small, unordered molecules can process information. During the
    first portion of this talk, I will illustrate how combinatorial chemical synthesis combined with high
    resolution mass spectrometry can be harnessed to store GBs of information in small molecules
    and metabolites. I will then turn to describing how basic principles of chemistry, such as mixing,
    complementarity, chemical reaction networks, and autocatalysis, can be exploited to realize fully
    molecular neural networks for machine learning and image processing. I will end with a
    discussion of the challenges molecular computation faces that may be resolved with clever
    doses of synthetic and theoretical chemistry, and the connections molecular computation has to
    the development of intelligent molecular machines.
    Biography:​
    Dr. Brenda Rubenstein is currently an Associate Professor of Chemistry and Physics at Brown
    University. While much of her group works on electronic structure theory, computational
    biophysics, and quantum computing, she is also deeply engaged in rethinking computing
    architectures. Prior to arriving at Brown, she was a Lawrence Distinguished Postdoctoral Fellow
    at Lawrence Livermore National Laboratory. She received her Sc.B.s in Chemical Physics and
    Applied Mathematics at Brown University, her M.Phil. in Computational Chemistry while a
    Churchill Scholar at the University of Cambridge, and her Ph.D. in Chemical Physics while a
    DOE Computational Science Graduate Fellow at Columbia University.
    rubenstein.group/
    Timecodes
    00:00 Introduction to Molecular Machines Group
    00:25 Brenda Rubenstein's Background and Research Focus
    00:46 Computing with Small Molecules
    03:47 Challenges and Opportunities in Molecular Computing
    07:18 Molecular Storage Techniques
    14:57 High Throughput Molecular Storage
    17:42 AI and Molecular Data Analysis
    20:14 Applications and Future Directions
    23:45 Introduction to Molecular Computation
    26:14 Combining Chemicals for Image Recognition
    26:33 Training Neural Networks with Chemistry
    27:24 Exploring Autocatalytic Reactions
    30:41 Implementing Dual Rail Encoding
    33:27 Challenges and Future Directions
    36:20 Q&A Session
    ══════════════════════════════════════
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ความคิดเห็น • 4

  • @Valgween
    @Valgween 4 วันที่ผ่านมา

    hope this catches on would love to see where this technology is in a few decades.

    • @26denterprises
      @26denterprises 3 วันที่ผ่านมา

      Like inverting the entire blockchain into a .2ml vial?

    • @Valgween
      @Valgween 3 วันที่ผ่านมา

      ​@@26denterprises no something like running doom in random liquids.

    • @26denterprises
      @26denterprises 3 วันที่ผ่านมา

      @@Valgween 🤣