The Data Exchange with Ben Lorica

A podcast by Ben Lorica - Thursdays

Thursdays

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270 Episodes

  1. A new storage engine for vectors

    Published: 10/20/2022
  2. Project Lightspeed: Next-generation Spark Streaming

    Published: 10/13/2022
  3. The Unreasonable Effectiveness of Speech Data

    Published: 10/6/2022
  4. Machine Learning Integrity

    Published: 9/29/2022
  5. Synthetic data technologies can enable more capable and ethical AI

    Published: 9/22/2022
  6. Confidential Computing for Machine Learning

    Published: 9/15/2022
  7. Applied NLP Research at Primer

    Published: 9/8/2022
  8. Using SQL to Retrieve Data from APIs and Web Services

    Published: 9/1/2022
  9. Machine Learning for Time Series Intelligence

    Published: 8/25/2022
  10. Unleashing the power of large language models

    Published: 8/18/2022
  11. Building production-ready machine learning pipelines

    Published: 8/11/2022
  12. Machine Learning at Gong

    Published: 8/4/2022
  13. Data Infrastructure for Computer Vision

    Published: 7/28/2022
  14. How DALL·E works

    Published: 7/21/2022
  15. Scalable, end-to-end machine learning, for everyone

    Published: 7/14/2022
  16. Orchestration and Pipelines for Data Scientists

    Published: 7/7/2022
  17. Dataframes at scale

    Published: 6/30/2022
  18. Software-Defined Assets

    Published: 6/23/2022
  19. Adversarial Machine Learning

    Published: 6/16/2022
  20. Orchestrating Machine Learning Applications

    Published: 6/9/2022

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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/].