• Meta's AI Power Play: Llama 2 408b, Reel Search

  • Jul 23 2024
  • Duración: 31 m
  • Podcast

Meta's AI Power Play: Llama 2 408b, Reel Search  Por  arte de portada

Meta's AI Power Play: Llama 2 408b, Reel Search

  • Resumen

  • Summary

    In this episode, Dalton Anderson discusses Meta's upcoming release of their 408 billion parameter model. He mentions that the model will be open source but the model weights may not be released. He also talks about Meta's new feature on their Meta AI website that allows users to search for reels. Dalton shares his experience using the feature for fashion inspiration and discusses the potential use cases for the feature. He also provides updates on the progress of his home remodeling project.

    Keywords

    Meta, 408 billion parameter model, open source, model weights, Meta AI, reels, fashion inspiration, use cases, home remodeling

    Takeaways

    Meta is set to release a 408 billion parameter model that will be open source.
    Meta's new feature on their Meta AI website allows users to search for reels, providing inspiration and ideas for various topics.
    The 408 billion parameter model is positioned as an enterprise-level model that will compete with other advanced models in the market.
    Open source models allow for greater transparency, collaboration, and faster bug fixes.
    Dalton shares updates on his home remodeling project, including electrical work, closet installations, and plumbing challenges.

    Sound Bites

    "Meta's exciting release: the 408 billion parameter model."
    "Meta's new feature on their Meta AI website allows you to search reels."
    "The 408 billion parameter model is an enterprise-level model that competes with other advanced models."

    Chapters

    00:00 Meta's Upcoming Release: The 408 Billion Parameter Model
    03:24 The Benefits of Open Source AI Models
    13:19 Exploring Meta's Reel Search Feature on Meta AI
    25:13 Updates on Home Remodeling and Plumbing Scare
    31:11 Preview: Live Demo of the 408 Billion Parameter Model

    Más Menos
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