80 episodes

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/].

The Data Exchange with Ben Lorica Ben Lorica

    • Technology
    • 4.8 • 17 Ratings

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/].

    Questioning the Efficacy of Neural Recommendation Systems

    Questioning the Efficacy of Neural Recommendation Systems

    This week’s guests are leading researchers in recommendation systems: Paolo Cremonesi is Professor of Computer Science and Maurizio Ferrari Dacrema is a Postdoc at Politecnico di Milano, where they are both part of the RecSys research group. Paolo is also the Reproducibility co-chair for the upcoming RecSys Conference.

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    Detailed show notes can be found on The Data Exchange web site.

    Subscribe to The Gradient Flow Newsletter.

    • 59 min
    Automation in Data Management and Data Labeling

    Automation in Data Management and Data Labeling

    This week’s guest is Hyun Kim, co-founder and CEO of Superb AI, a startup building tools to help companies manage data across the entire machine learning application lifecycle. This includes tools to label, store, and monitor data assets that power all computer vision applications. We also discussed emerging trends in machine learning and AI including synthetic data, reinforcement learning, and self-supervised learning.

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    Detailed show notes can be found on The Data Exchange web site.

    Subscribe to The Gradient Flow Newsletter.

    • 43 min
    Reinforcement Learning For the Win

    Reinforcement Learning For the Win

    This week’s guest is Nicolas (Nic) Hohn, Chief Data Scientist, McKinsey/QuantumBlack Australia. Nic led a team of data scientists charged with helping America’s Cup winning team,  Emirates Team New Zealand, test new designs for hydrofoils – important sailing boat components that could be modified based on rules set forth by race organizers. More precisely the QuantumBlack team used Ray RLlib to design an AI agent that could learn to sail the boat for a given design at an optimal speed, and this AI agent proved crucial during the design process.

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    Detailed show notes can be found on The Data Exchange web site.

    Subscribe to The Gradient Flow Newsletter.

    • 48 min
    How Companies Are Investing in AI Risk and Liability Minimization

    How Companies Are Investing in AI Risk and Liability Minimization

    In this episode of the Data Exchange I speak with Andrew Burt, co-founder and Managing Partner of BNH.ai, a new law firm focused on AI compliance, risk mitigation, and related topics.  BNH is the first law firm run by lawyers and technologists focused on helping companies identify and mitigate risks associated with machine learning and AI. 

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    Detailed show notes can be found on The Data Exchange web site.

    Subscribe to The Gradient Flow Newsletter.

    • 41 min
    The Future of Machine Learning Lies in Better Abstractions

    The Future of Machine Learning Lies in Better Abstractions

    This week’s guest is Travis Addair, he previously led the team at Uber that was responsible for building Uber’s deep learning infrastructure. Travis is deeply involved with two popular open source projects related to deep learning:
    He is maintainer of Horovod, a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.And Travis is a co-maintainer of Ludwig, a toolbox that allows users to train and test deep learning models without the need to write code.Subscribe: Apple • Android • Spotify • Stitcher • Google • RSS.

    Detailed show notes can be found on The Data Exchange web site.

    Subscribe to The Gradient Flow Newsletter.

    • 48 min
    Why You Should Optimize Your Deep Learning Inference Platform

    Why You Should Optimize Your Deep Learning Inference Platform

    In this episode of the Data Exchange, I speak with Yonatan Geifman, CEO and co-founder of Deci, as well as with Ran El-Yaniv, Chief Scientist and co-founder of Deci and Professor of Computer Science at Technion. 

    Subscribe: Apple • Android • Spotify • Stitcher • Google • RSS.

    Detailed show notes can be found on The Data Exchange web site.

    Subscribe to The Gradient Flow Newsletter.

    • 41 min

Customer Reviews

4.8 out of 5
17 Ratings

17 Ratings

Buck Trends ,

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.

Taylor/JOHN/ ,

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!

Moore,,98W ,

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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