229 episodes
The Data Exchange with Ben Lorica Ben Lorica
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- Technology
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4.9 • 213 Ratings
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A series of informal conversations with thought leaders, researchers, practitioners, and writers on a wide range of topics in technology, science, and of course big data, data science, artificial intelligence, and related applications. Anchored by Ben Lorica (@BigData), the Data Exchange also features a roundup of the most important stories from the worlds of data, machine learning and AI. Detailed show notes for each episode can be found on https://thedataexchange.media/ The Data Exchange podcast is a production of Gradient Flow [https://gradientflow.com/].
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DBRX and the Future of Open LLMs
In this episode, Hagay Lupesko, Senior Director of Engineering at Databricks MosaicAI, delves into the creation and aspirations behind DBRX, an innovative open Large Language Model (LLM) designed to bridge the gap between quality and cost-effectiveness for AI applications.
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Detailed show notes can be found on The Data Exchange web site. -
Monthly Roundup: New LLMs, GTC 2024, Constraint-Driven Innovation, Model Safety, and GraphRAG
Paco Nathan is the founder of Derwen, a boutique consultancy focused on Data and AI. This episode is part of our series of monthly roundups and covers: recently released large language models, Constraint-Driven Innovation, highlights from GTC 2024, and Lessons from the First AI Workload Security Exploit.
Subscribe to the Gradient Flow Newsletter: https://gradientflow.substack.com/
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Detailed show notes can be found on The Data Exchange web site. -
Automating Software Upgrades: How to Combine AI and Expert Developers
Steve Pike is a co-founder of Infield.ai, a startup building tools to help companies upgrade and maintain open source software dependencies, ensuring they stay up-to-date with the latest releases, features, and security fixes.
Subscribe to the Gradient Flow Newsletter: https://gradientflow.substack.com/
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Detailed show notes can be found on The Data Exchange web site. -
Generative AI in the Industrial Sphere
Chetan Gupta is the Head of AI Research at Hitachi. This episode explores the applications and challenges of generative AI in industrial settings.
Subscribe to the Gradient Flow Newsletter: https://gradientflow.substack.com/
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Detailed show notes can be found on The Data Exchange web site. -
The Intersection of LLMs, Knowledge Graphs, and Query Generation
Semih Salihoglu is an Associate Professor at University of Waterloo, and co-creator of Kuzu an open source embeddable property graph database management system. This episode explores the use of large language models (LLMs) for generating queries across different query languages like SQL and Cypher for graphs.
Subscribe to the Gradient Flow Newsletter: https://gradientflow.substack.com/
Subscribe: Apple • Spotify • Overcast • Google • AntennaPod • Podcast Addict • Amazon • RSS.
Detailed show notes can be found on The Data Exchange web site. -
Unlocking the Potential of Private Data Collaboration
Sadegh Riazi, CEO and co-founder of Pyte, a startup offering secure, encrypted data collaboration solutions, enabling partners to maximize insights without compromising privacy or data integrity.
Subscribe to the Gradient Flow Newsletter: https://gradientflow.substack.com/
Subscribe: Apple • Spotify • Overcast • Google • AntennaPod • Podcast Addict • Amazon • RSS.
Detailed show notes can be found on The Data Exchange web site.
Customer Reviews
Indispensable source of information about trends in all things Data
No one monitors the pulse of data trends better than Ben. This pod cast and his other Gradient Flow content are indispensable for those of us in the data world.
Incredible podcast!
This show is designed for people who want to learn, technology, science, data, data science, and AI, and is really helpful. Love this show 😊I'm very excited to hear more of her content !! The quality was really good. Highly recommend subscribing to it!
Really Good Interviews!
This podcast covers a lot of really interesting topics and features a really knowledgeable host. There is so much information out there about Data, Machine Learning, and AI. I still appreciate everything about this production. I suggest it when I can. Keep it up
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