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761: Gemini Ultra: How to Release an A.I. Product for Billions of Users, with Google's Lisa Cohen
Manage episode 504358930 series 2532807
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, and by Intel and HPE Ezmeral Software Solutions. 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
1016 قسمت
Manage episode 504358930 series 2532807
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, and by Intel and HPE Ezmeral Software Solutions. 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
1016 قسمت
همه قسمت ها
×1 935: Global Issues Accelerated by AI (with Solutions), feat. Stephanie Hare 1:17:27
1 933: Future-Proofing Your Career in the AI Era, feat. Sheamus McGovern 1:15:10
1 931: Boost Your Profits with Mathematical Optimization, feat. Jerry Yurchisin 1:13:12
1 929: Dragon Hatchling: The Missing Link Between Transformers and the Brain, with Adrian Kosowski 1:14:28
1 927: Automating Code Review with AI, feat. CodeRabbit’s David Loker 1:19:18
1 925: AI, Automation and the Future of Work, with Oxford’s Prof. Carl Benedikt Frey 1:10:06
1 923: Graph Algorithms, GraphRAG and Causal Graphs, with Graph Guru Amy Hodler 1:03:47
1 921: NPUs vs GPUs vs CPUs for Local AI Workloads, with Dell’s Ish Shah and Shirish Gupta 1:12:12
1 919: Hopes and Fears of AGI, with All-Time Bestselling ML Author Aurélien Géron 1:29:51
1 917: 8 Steps to Becoming an AI Engineer, with Kirill Eremenko 1:15:33
1 915: How to Jailbreak LLMs (and How to Prevent It), with Michelle Yi 1:09:33
1 913: LLM Pre-Training and Post-Training 101, with Julien Launay 1:15:16
1 909: Causal AI, with Dr. Robert Usazuwa Ness 1:22:27
1 907: Neuroscience, AI and the Limitations of LLMs, with Dr. Zohar Bronfman 1:21:16
1 905: Why RAG Makes LLMs Less Safe (And How to Fix It), with Bloomberg’s Dr. Sebastian Gehrmann 57:49
1 903: LLM Benchmarks Are Lying to You (And What to Do Instead), with Sinan Ozdemir 1:28:20
1 901: Automating Legal Work with Data-Centric ML (feat. Lilith Bat-Leah) 1:06:12
1 899: Landing $200k+ AI Roles: Real Cases from the SuperDataScience Community, with Kirill Eremenko 1:33:12
1 897: How to Enable Enterprise AI Transformation, with Strategy Consultant Diane Hare 1:02:42
1 895: The Future of Enterprise AI: Investor Shaun Johnson Reveals What Actually Works 1:16:26
1 893: How to Jumpstart Your Data Career (by Applying Like a Scientist), with Avery Smith 1:17:51
1 891: Conversational AI is Overhauling Data Analytics, with Martin Brunthaler 1:02:08
1 889: AI-Powered Virtual Reality: The Future of Education and Entertainment, with Mary Spio 1:06:59
1 887: Multi-Agent Teams, Quantum Computing and the Future of Work, with Dell’s Global CTO John Roese 1:02:04
1 885: Python Polars: The Definitive Guide, with Jeroen Janssens and Thijs Nieuwdorp 1:15:22
1 883: Blackwell GPUs Are Now Available at Your Desk, with Sama Bali and Logan Lawler 1:04:03
1 881: Beyond GPUs: The Power of Custom AI Accelerators, with Emily Webber 1:17:06
1 879: Serverless, Parallel, and AI-Assisted: The Future of Data Science is Here, with Zerve’s Dr. Greg Michaelson 1:07:14
1 877: The Neural Processing Units Bringing AI to PCs, with Shirish Gupta 1:09:32
1 875: How Semiconductors Are Made (And Fuel the AI Boom), with Kai Beckmann 1:10:29
1 873: Become Your Best Self Through AI Augmentation — feat. Natalie Monbiot 1:12:32
1 871: NoSQL Is Ideal for AI Applications, with MongoDB’s Richmond Alake 1:13:11
1 869: AI Should Make Humans Wiser (But It Isn’t), with Varun Godbole 1:19:42
1 867: LLMs and Agents Are Overhyped, with Dr. Andriy Burkov 1:33:12
1 863: TabPFN: Deep Learning for Tabular Data (That Actually Works!), with Prof. Frank Hutter 1:06:06
1 861: From Pro Athlete to Data Engineer: Colleen Fotsch’s Inspiring Journey 2:00:42
1 857: How to Ensure AI Agents Are Accurate and Reliable, with Brooke Hopkins 1:22:43
1 855: Exponential Views on AI and Humanity’s Greatest Challenges, with Azeem Azhar 1:28:12
1 853: Generative AI for Business, with Kirill Eremenko and Hadelin de Ponteves 1:29:00
1 851: Quantum ML: Real-World Applications Today, with Dr. Florian Neukart 1:11:51
1 849: 2025 AI and Data Science Predictions, with Sadie St. Lawrence 1:18:29
1 847: AI Engineering 101, with Ed Donner 1:12:14
1 845: Tech is Our New Religion And It Needs Reformation, with Greg Epstein 1:36:56
1 843: Safe, Fast and Efficient AI, with Protopia’s Dr. Eiman Ebrahimi 1:27:50
1 837: Career Success in the AI Era, with Deepali Vyas 1:10:26
1 835: AI Systems as Productivity Engines, with You.com’s Bryan McCann 1:33:04
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