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The AI Paper Club

By: Deeper Insights
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  • Summary

  • Are you interested in the fascinating world of data science and artificial intelligence? Then you have come to the right podcast! We've hand-picked some of the most knowledgeable and experienced experts from Deeper Insights, a UK AI consultancy, to join our hosts in discussing the latest academic papers, research, and theories in the field. From hands-on experience developing and working with machine learning models to mastering unstructured data management and computer vision, our guests have it all. And with their in-depth insights and knowledge, The AI Paper Club is the perfect podcast for anyone looking to expand their understanding of AI.
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Episodes
  • 17: Meta’s Chameleon: Redefining Data Integration with Mixed-Modal AI

    17: Meta’s Chameleon: Redefining Data Integration with Mixed-Modal AI
    Jun 27 2024
    In this episode of the AI Paper Club Podcast, hosts Rafael Herrera and Sonia Marques are joined by Andrew Eaton, an AI Solutions Consultant from Deeper Insights, to explore Meta’s latest paper, “Chameleon: Mixed Modal Early Fusion Foundation Models.” This paper marks Meta’s first steps into the mixed modal AI space, combining text, images, and other data types from the start for a more integrated understanding.

    The podcast explores how, unlike traditional models that process text and images separately before combining them, Chameleon integrates these modalities right from the beginning. This early fusion method promises enhanced performance in tasks like image captioning and interleaved text-image outputs, setting new benchmarks in the field.

    We also extend a special thank you to the research team at Meta for developing this month’s paper. If you are interested in reading the paper for yourself, please check this link: https://arxiv.org/abs/2405.09818.

    For more information on all things artificial intelligence, machine learning, and engineering for your business, please visit www.deeperinsights.com or reach out to us at thepaperclub@deeperinsights.com.
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    28 mins
  • 16: Infini-Attention: Google's Solution for Infinite Memory in LLMs

    16: Infini-Attention: Google's Solution for Infinite Memory in LLMs
    May 22 2024
    In this episode of the AI Paper Club Podcast, hosts Rafael Herrera and Sonia Marques welcome Leticia Fernandes, a Deeper Insights Senior Data Scientist and Generative AI Ambassador. Together, they explore the groundbreaking "Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention" paper from Google. This paper addresses the challenge of fitting infinite context into large language models, introducing the Infini-attention method. The trio discusses how this approach works, including how it uses linear attention and employs compressive memory to store key-value pairs, enabling models to handle extensive contexts.

    We also extend a special thank you to the research team Google for developing this month’s paper. If you are interested in reading the paper for yourself, please check this link: https://arxiv.org/pdf/2404.07143.pdf

    For more information on all things artificial intelligence, machine learning, and engineering for your business, please visit www.deeperinsights.com or reach out to us at thepaperclub@deeperinsights.com.
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    23 mins
  • 15: The AI Composer: Meta AI’s Innovations in Music and Melody

    15: The AI Composer: Meta AI’s Innovations in Music and Melody
    Apr 23 2024
    This month's episode of the AI Paper Club Podcast covers AI Music! Hosts Rafael and Sonia welcome Deeper Insights Data Scientist Joan Rosello to discuss the paper "Simple and Controllable Music Generation" from Meta AI. He introduces us to Meta AI's model that not only generates audio from text prompts but also introduces a novel feature—melody conditioning. This allows the creation of music that adheres to a provided melody, pushing the boundaries of AI in music generation. We also explore the technical concepts involved in creating AI music today, including residual vector quantization used in this model.

    We also extend a special thank you to the research teams at Meta AI for developing this month’s paper. If you are interested in reading the paper for yourself, please check this link: https://arxiv.org/pdf/2306.05284.pdf

    For more information on all things artificial intelligence, machine learning, and engineering for your business, please visit www.deeperinsights.com or reach out to us at thepaperclub@deeperinsights.com.
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    24 mins
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