The AI Paper Club Por arte de portada

The AI Paper Club

De: Deeper Insights
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  • Resumen

  • 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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Episodios
  • 18: The Future of Sport: AI-Generated Soccer Commentary

    18: The Future of Sport: AI-Generated Soccer Commentary
    Jul 23 2024
    In the latest AI Paper Club Podcast episode, hosts Rafael Herrera and Sonia Marques welcome Dr. Catarina Carvalho, Senior Data Scientist and Computer Vision SME from Deeper Insights, to discuss, "Match Time: Towards Automatic Soccer Game Commentary Generation". This paper introduces a method for generating engaging soccer commentary from video sequences using advanced AI techniques.

    The episode explores the importance of data quality, the innovative pipeline for dataset curation, and the perceiver-like architecture ensuring temporal coherence. It also covers broader applications, such as in cooking shows or assisting the hearing impaired. Tune in to discover how AI is revolutionising sports commentary and how you can try these techniques at home.

    We also extend a special thank you to the research teams from Shanghai University and Shanghai AI Laboratory for developing this month’s paper. If you are interested in reading the paper for yourself, please check this link: https://arxiv.org/abs/2406.18530

    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 m
  • 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 m
  • 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 m
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