rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Radar talks
    part name: Rachel Roumeliotis on AI adoption in the enterprise 2022
  name:
    name part: Roumeliotis, Rachel
    role:
      role term: author.
  name:
    name part: O'Reilly (Firm)
    role:
      role term: publisher.
  type of resource: moving image
  genre: videorecording
  genre: Instructional films.
  genre: Internet videos.
  genre: Nonfiction films.
  origin info:
    place:
      place term: xx
    date issued: 2022
    edition: [First edition].
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (1 video file (59 min.)) : sound, color.
  abstract: In this edition of Radar Talks, O'Reilly VP of content strategy Rachel Roumeliotis explores the state of AI adoption in 2022. See how your company compares with your peers in the research, adoption, and deployment of AI. You'll get a glimpse into the tools that AI experts are using, how they're using them, where they're hitting bottlenecks, and more. Recorded on July 11, 2022. See the original event page for resources for further learning or watch recordings of other past events. The O'Reilly Radar Talks series brings you expert opinions on emerging topics through hour-long interactive events. In conversation with some of the industry's top minds, you'll look at the early signals indicating significant trends and new technologies that will shape the future--and discover how to begin forging these technologies now. Share your own predictions and ask your questions while gaining insight into our experts' unique outlooks for the future.
  note: Rachel Roumeliotis, presenter.
  subject:
    topic: Artificial intelligence
    topic: Industrial applications
  subject:
    topic: Artificial intelligence
    topic: Industrial applications
  classification: TA347.A78
  classification: 006.3
  identifier: 0636920751915 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: ORMDA
    record creation date: 220725
    record change date: 20260128205855.6
    record identifier: in00004672026
    language of cataloging:
      language term: eng