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Artwork for The Data Exchange

The Data Exchange with Ben Lorica

Ben Lorica
Generative AI
Artificial Intelligence
Large Language Models
AI Agents
Machine Learning
Open Source Software
Knowledge Graphs
Graph Rag
Openai
Data Science
Natural Language Processing
Foundation Models
BAML
Language Models
Data Engineering
Cybersecurity
Automation
Data Quality
Cloud Computing
Unstructured Data

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. Detaile... more

PublishesWeeklyEpisodes356Founded7 years ago
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Artwork for The Data Exchange

Latest Episodes

Ben Lorica sits down with Evangelos Simoudis to unpack why open-weights models are closing the gap with frontier labs and pushing enterprises toward “corporate AI sovereignty.” They then apply an attenuation-funnel lens to AI coding tools — more code... more

Manos Koukoumidis, CEO of Oumi, returns to the podcast to make the case that most enterprises are wildly inefficient, using bloated generic AI models for tasks that demand specialized ones. He argues that companies should stop renting intelligence fr... more

Andrew Moore, CEO of Lovelace, former head of Google Cloud AI, and former dean of Carnegie Mellon’s School of Computer Science, joins the podcast to discuss YottaGraph, a knowledge graph growing by a billion facts a week that serves as a context engi... more

Ben Lorica speaks with Helen Gu, CEO of InsightFinder AI and professor at North Carolina State University, about why reliability is becoming a central challenge for enterprise AI. They discuss AI incident response, monitoring agents in production, do... more

Key Facts

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Contact Information
Podcast Host
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Find out how many people listen to this podcast per episode and each month.

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Recent Guests

Hamza Tahir
Founder of Kitaru
Kitaru
Episode: AI Agents Are Implemented, Not Adopted
Zhou Yu
Associate Professor of Computer Science at Columbia University; co-founder of Arklex AI
Columbia University; Arklex AI
Episode: Why Your AI Agent Isn't Ready to Ship (And How to Know When It Is)
Doris Xin
Co-founder of Disarray
Disarray
Episode: Why Foundation Models Haven’t Replaced Classical Machine Learning
Moustafa Abdelbaky
Co-founder of Disarray
Disarray
Episode: Why Foundation Models Haven’t Replaced Classical Machine Learning
Terrence Lee-St. John
Founder of Enli
Enli
Episode: When "Garbage In, Garbage Out" Gets It Wrong
Evan Marshall
CTO of Ito AI, focused on automated QA for pull requests
Ito AI
Episode: As Code Generation Speeds Up, Who Tests the Output?
Richard Garris
Databricks executive discussed on the show
Databricks
Episode: The Gap Between AI Hype and Enterprise Reality
Barry Dauber
Databricks executive discussed on the show
Databricks
Episode: The Gap Between AI Hype and Enterprise Reality
Nick Vasiloglou
VP of Research at Relational AI
Relational AI
Episode: Reading the Tea Leaves: What the World's Top AI Researchers Are Really Working On

Host

Ben Lorica
Host of The Data Exchange

Reviews

5.0 out of 5 stars from 856 ratings
  • I’ve been listening to Ben Lorica’s podcasts since 2015. At every stage in my career as a data scientist / engineer / architect, at every company and in every industry, his podcasts have kept me informed of advances that impact my team’s work and reduce my professional “blind-spots” / “unknown unknowns”.

    Audible
    5
    aces
    United Statesa year ago
  • Essential for data professionals

    I’ve been listening to Ben Lorica’s podcasts since 2015. At every stage in my career as a data scientist / engineer / architect, at every company and in every industry, his podcasts have kept me informed of advances that impact my team’s work and reduce my professional “blind-spots” / “unknown unknowns”.

    Audible
    5
    aces
    United Statesa year ago
  • Really Awesome interview!

    Love this show. Keep up the good woek!

    Apple Podcasts
    5
    Brandy-Thins
    France2 years ago
  • Great

    Hey man really great your show.Love it!

    Apple Podcasts
    5
    Riyaparvin76
    United States2 years ago
  • Most favourite!

    I listen this show again and again!

    Apple Podcasts
    5
    fazlerabbykhoks
    United States2 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

The host keeps conversations engaging and accessible for both practitioners and leaders.
Listeners appreciate the breadth of topics—from AI governance to enterprise AI—kept approachable.
Guests bring deep expertise, and the host draws practical takeaways for real-world work.
High-quality sound and thoughtful interview style are consistent strengths of the show.
A few episodes note room for improvement in technical depth or sound quality occasionally.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#200
United Kingdom/Technology
Apple Podcasts
#141
Chile/Technology
Apple Podcasts
#147
South Africa/Technology
Apple Podcasts
#177
Israel/Technology
Apple Podcasts
#217
New Zealand/Technology
Apple Podcasts
#246
Austria/Technology

Talking Points

Recent interactions between the hosts and their guests.

The Data Stack Wasn't Built for AI — Here's What Comes Next
Q: What workloads and teams are using Lance today?
LanceDB excels at managing large-scale AI data, including embeddings for search, data curation, feature extraction, and supporting GPU-heavy distributed training, making it suitable for organizations running large AI workloads.
The Data Stack Wasn't Built for AI — Here's What Comes Next
Q: So maybe give our listeners, Chang, a high level description of the Lance format and why it's become so popular.
Lance is a Lakehouse format that spans file, table, and indexing layers, designed for fast random access and optimized for AI datasets; it integrates with Parquet/Iceberg ecosystems but offers better support for multimodal data and ML workflows.
The Data Stack Wasn't Built for AI — Here's What Comes Next
Q: So Chang, at this point, do you think that more people are aware of this disconnect between those traditional tools and the kinds of tools they'll need moving forward?
Yes, there's broad recognition among data infrastructure professionals that the existing stack is insufficient for AI data and that a more integrated approach is needed to manage embeddings, metadata, and multimodal data across the lifecycle.
Why Foundation Models Haven’t Replaced Classical Machine Learning
Q: Why aren't foundation models replacing traditional ML for enterprise data tasks?
Foundation models struggle with non-language data, proprietary datasets, and the need for robust data integration and lineage; enterprise use cases require multimodal handling, context, and governance that localized, context-rich systems better provide.
Why Your AI Agent Isn't Ready to Ship (And How to Know When It Is)
Q: Can Arklex help after deployment, for example in incident response or CI/CD pipelines?
Yes. Arklex can monitor production traces, certify how things are performing, and integrate with CI/CD to add regression tests for new versions, though auto-fix is not currently part of the offering.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

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Location
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Professions
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Frequently Asked Questions About The Data Exchange

What is The Data Exchange about and what kind of topics does it cover?

A thoughtful tech-focused show featuring in-depth conversations with researchers, practitioners, and industry leaders about data, AI, and the evolving landscape of technology. Episodes frequently center on enterprise AI, data governance, AI tooling, and practical deployment patterns, with real-world anecdotes from finance, manufacturing, media, and software. A recurring strength is translating cutting-edge research into actionable insights for practitioners, with attention to governance, security, and cost when building production-grade AI and data systems. Notable is the host's ability to weave technical detail with accessible storytelling, and the show's emphasis on enabling listeners to apply concepts in their own organizations. This mix... more

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How many episodes of The Data Exchange are there?

The Data Exchange launched 7 years ago and published 356 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on The Data Exchange?

Recent guests on The Data Exchange include:

1. Hamza Tahir
2. Zhou Yu
3. Doris Xin
4. Moustafa Abdelbaky
5. Terrence Lee-St. John
6. Evan Marshall
7. Richard Garris
8. Barry Dauber

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