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Artwork for Vanishing Gradients

Vanishing Gradients

Hugo Bowne-Anderson
Machine Learning
Large Language Models
Data Science
Prompt Engineering
Generative AI
Artificial Intelligence
AI Agents
Context Engineering
Google Deepmind
AI Applications
Gemini 3
Software Development
Artificial General Intelligence
Natural Language Processing
Machine Learning Benchmarks
Structured Workflows
Error Analysis
Software Engineering
Multimodal Applications
Multimodal AI

A podcast for people who build with AI. Long-format conversations with people shaping the field about agents, evals, multimodal systems, data infrastructure, and the tools behind them. Guests include Jeremy Howard (fast.ai), Hamel Husain (Parlance Labs), Shreya Shankar (UC Berkeley), Wes McKinney (creator of pandas), Samuel Colvin (Pydantic) and more. hugobowne.substack.com

PublishesTwice monthlyEpisodes78Founded4 years ago
Number of ListenersCategories
ScienceTechnology

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Artwork for Vanishing Gradients

Latest Episodes

So I think we’re really at a historical moment, and the opportunity is massive. Almost 15 years ago, we were promised that data science was going to be this incredible thing and create all this value for people. And I think nowadays it’s mostly viewe... more

One thing that I don’t like about Claude is that you get into this weird mental state: oh, I think I trust the model. Let’s do the slot machine. Hit click, which puts you in an inactive mode of thinking. Maybe it’s better to use a worse model….

Vinc... more

> I almost don’t read code now. My approach with Roborev is it’s like my code reader. The mantra is: Roborev reads every line of code that is generated. It gets read multiple times. And so, whenever I push up a pull request, the branch gets re-review... more

There are a lot of reasons why we should do AI evals. For many companies doing AI evals is the way to build the feedback loop into the product development lifecycle. So it is like your compass. We’re using AI evals as a compass to guide product devel... more

Key Facts

Accepts Guests
Accepts Sponsors
Contact Information
Podcast Host
Number of Listeners
Find out how many people listen to this podcast per episode and each month.

Recent Guests

Thomas Wiecki
Co-creator of PyMC, PhD in computational psychiatry, leader at PyMC Labs
PyMC Labs
Episode: The Future of Agentic Data Science
Vincent Warmerdam
Senior data professional, engineer, researcher, Marimo founder/lead
Marimo
Episode: Agent-Harness.ipynb*
Wes McKinney
Creator of Pandas; principal architect at Posit
Posit
Episode: Agentic Engineering and the Lost Art of Verification
Jeremiah Lowin
Founder and CEO of Prefect
Prefect
Episode: Agentic Engineering and the Lost Art of Verification
Randy Olson
Co-founder and CTO of Good Eye Labs
Good Eye Labs
Episode: Agentic Engineering and the Lost Art of Verification
Stella Liu
AI evals practitioner and researcher, head of applied science at ASU, co-creator of the AI Evals and Analytics Playbooks course on Maven
Arizona State University
Episode: Next Level AI Evals for 2026
Eddie Landesberg
Staff data scientist at Google and causal AI expert
Google
Episode: Next Level AI Evals for 2026
Katharine Jarmul
Data and AI privacy expert, author of Practical Data Privacy
ThoughtWorks (former principal data scientist) / Cape Privacy (former)
Episode: Privacy Theater Is Not Privacy Engineering: What It Actually Takes to Ship Safe AI
Alex Strick van Linschoten
Machine Learning Engineer at ZenML and creator of the LMM Ops database
ZenML
Episode: Episode 70: 1,400 Production AI Deployments

Host

Hugo Bowne Anderson
Host of the show

Reviews

4.8 out of 5 stars from 48 ratings
  • Host may please consider to say more in less; the sweet spot is under 40 minutes.

    Podcast Addict
    3
    MrDaggubati
    3 months ago
  • Substantive!

    Practical, smart content from an industry veteran

    Apple Podcasts
    5
    eddielandes
    United States6 months ago
  • Best data science podcast to come out in a while

    [see title]

    Apple Podcasts
    5
    vishalthatsme
    United States4 years ago

Listeners Say

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

Substantive!
Best data science podcast to come out in a while
Practical, smart content from an industry veteran

Chart Rankings

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

Apple Podcasts
#41
Indonesia/Technology
Apple Podcasts
#173
Israel/Technology
Apple Podcasts
#197
South Korea/Technology
Apple Podcasts
#245
Ireland/Technology

Talking Points

Recent interactions between the hosts and their guests.

The Future of Agentic Data Science
Q: What are the core components of a robust agentic data science system?
A robust system comprises a harness (Daemon/Cloud Code), domain expertise and skills, orchestration for parallel runs, and observability/evals to monitor performance and guide continuous improvement.
The Future of Agentic Data Science
Q: How should practitioners start adopting agentic data science without getting overwhelmed?
Begin small with a single repeatable analysis, automate it as a skill, then progressively expand to more complex workflows while building observability and verification layers and maintaining a strong human-in-the-loop for critical decisions.
The Future of Agentic Data Science
Q: What is the current state of AI agent use in data science, and where are we headed?
Agents are moving from assisting mundane tasks like auto-generating code to enabling end-to-end decision workflows that embed governance, verification, and interactive inquiry, thereby making advanced methods more accessible and capable of influencing real business decisions.
Next Level AI Evals for 2026
Q: What is the future of AI evals in terms of standards and regulation?
There is a push toward industry standards for AI evals, with regulatory guidance that is currently high level; practitioners want concrete standards to ensure compliance and measurable impact in procurement and governance contexts.
Next Level AI Evals for 2026
Q: How should we think about offline vs online evals, and when to use each?
Offline evals are used to align with expectations and establish a baseline before costly experiments, while online evals and AB testing validate real-world impact; both are needed for a robust evaluation program, depending on stage and risk.

Audience Metrics

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

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Gender Skew
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Frequently Asked Questions About Vanishing Gradients

What is Vanishing Gradients about and what kind of topics does it cover?

A long-form tech interview show focused on how AI is built in production. Episodes frequently explore agentic AI, evaluation frameworks, data stacks, and tooling for deploying reliable systems at scale. Guests include researchers, engineers, and practitioners who speak to practical workflows, governance, and the human-in-the-loop aspects of building robust AI products. A standout throughline is the emphasis on verifiable, observable AI workflows—from notebooks and data pipelines to evals and privacy—combined with thoughtful discussions about reliability, safety, and production-readiness. The format tends to pair hands-on demos with strategic reflections, making it valuable for listeners who want concrete takeaways for deploying AI responsib... more

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Vanishing Gradients launched 4 years ago and published 78 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 Vanishing Gradients?

Recent guests on Vanishing Gradients include:

1. Thomas Wiecki
2. Vincent Warmerdam
3. Wes McKinney
4. Jeremiah Lowin
5. Randy Olson
6. Stella Liu
7. Eddie Landesberg
8. Katharine Jarmul

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