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761: Gemini Ultra: How to Release an A.I. Product for Billions of Users, with Google's Lisa Cohen

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Manage episode 403433419 series 2532807
Contenu fourni par Super Data Science: ML & AI Podcast with Jon Krohn and Jon Krohn. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Super Data Science: ML & AI Podcast with Jon Krohn and Jon Krohn ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
Google's Gemini Ultra takes the spotlight this week, as host Jon Krohn welcomes Lisa Cohen, Google's Director of Data Science and Engineering, for a conversation about the launch of Gemini Ultra. Discover the capabilities of this cutting-edge large language model and how it stands toe-to-toe with GPT-4. Lisa shares her insights on the development, rollout, and potential of Gemini Ultra in reshaping various sectors. Whether you're a data science professional, tech enthusiast, or curious about the future of AI, this episode offers a deep dive into one of the most significant advancements in artificial intelligence. This episode is brought to you by Ready Tensor, where innovation meets reproducibility (https://www.readytensor.ai/), and by Intel and HPE Ezmeral Software Solutions (https://hpe.com/ezmeral/chatbots). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. In this episode you will learn: • Google’s Gemini model family and Lisa's key responsibilities [04:55] • How LLMs will transform the practice of Data Science [19:47] • Lisa on prompt engineering and reinforcement learning from human feedback [24:38] • How to fine-tune Gemini models with Google's Vertex AI [30:52] • How AI-assistants will transform life and work for everyone from data scientists to educators to children [47:14] • The challenges of developing a data-centric culture [57:31] • Centralized vs decentralized data science teams [1:03:50] Additional materials: www.superdatascience.com/761
  continue reading

786 episodes

Artwork
iconPartager
 
Manage episode 403433419 series 2532807
Contenu fourni par Super Data Science: ML & AI Podcast with Jon Krohn and Jon Krohn. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Super Data Science: ML & AI Podcast with Jon Krohn and Jon Krohn ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
Google's Gemini Ultra takes the spotlight this week, as host Jon Krohn welcomes Lisa Cohen, Google's Director of Data Science and Engineering, for a conversation about the launch of Gemini Ultra. Discover the capabilities of this cutting-edge large language model and how it stands toe-to-toe with GPT-4. Lisa shares her insights on the development, rollout, and potential of Gemini Ultra in reshaping various sectors. Whether you're a data science professional, tech enthusiast, or curious about the future of AI, this episode offers a deep dive into one of the most significant advancements in artificial intelligence. This episode is brought to you by Ready Tensor, where innovation meets reproducibility (https://www.readytensor.ai/), and by Intel and HPE Ezmeral Software Solutions (https://hpe.com/ezmeral/chatbots). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. In this episode you will learn: • Google’s Gemini model family and Lisa's key responsibilities [04:55] • How LLMs will transform the practice of Data Science [19:47] • Lisa on prompt engineering and reinforcement learning from human feedback [24:38] • How to fine-tune Gemini models with Google's Vertex AI [30:52] • How AI-assistants will transform life and work for everyone from data scientists to educators to children [47:14] • The challenges of developing a data-centric culture [57:31] • Centralized vs decentralized data science teams [1:03:50] Additional materials: www.superdatascience.com/761
  continue reading

786 episodes

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