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Artwork for Vanishing Gradients

Vanishing Gradients

Hugo Bowne-Anderson
Machine Learning
Large Language Models
Data Science
Artificial Intelligence
Generative AI
Probable
Prompt Engineering
Fine Tuning
Visualization
Pre-Training
Open Source Collaboration
Scikit-Learn
Data Management
Fast.ai
Covid-19
Statistical Thinking
Open Source
Developer Tools
Conversational AI
Data Journalism

A podcast about all things data, brought to you by data scientist Hugo Bowne-Anderson. It's time for more critical conversations about the challenges in our industry in order to build better compasses for the solution space! To this end, this podcast will consist of long-format conversations between Hugo and other people who work broadly in the data science, machine learning, and AI spaces. We'll ... more

PublishesTwice monthlyEpisodes61Founded4 years ago
Number of ListenersCategory
Technology

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Artwork for Vanishing Gradients

Latest Episodes

Most AI teams find their multi-agent systems devolving into chaos, but ML Engineer Alex Strick van Linschoten argues they are ignoring the production reality. In this episode, he draws on insights from the LLM Ops Database (750+ real-world deployment... more

Most AI teams find "evals" frustrating, but ML Engineer Hamel Husain argues they’re just using the wrong playbook. In this episode, he lays out a data-centric approach to systematically measure and improve AI, turning unreliable prototypes into robus... more

John Berryman (Arcturus Labs; early GitHub Copilot engineer; co-author of Relevant Search and Prompt Engineering for LLMs) has spent years figuring out what makes AI applications actually work in production. In this episode, he shares the “seven dead... more

While most conversations about generative AI focus on chatbots, Thomas Wiecki (PyMC Labs, PyMC) has been building systems that help companies make actual business decisions. In this episode, he shares how Bayesian modeling and synthetic consumers can... more

Key Facts

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

Recent Guests

Alex Strick van Linschoten
Machine learning engineer at Zen ML
Zen ML
Episode: Episode 61: The AI Agent Reliability Cliff: What Happens When Tools Fail in Production
Bryan Bischof
Guest caller from Theory Ventures discussing failure analysis in AI.
Theory Ventures
Episode: Episode 60: 10 Things I Hate About AI Evals with Hamel Husain
John Berryman
Founder of Arcturus Labs, author of Prompt Engineering for LLMs, and early engineer on GitHub Copilot.
Arcturus Labs
Episode: Episode 59: Patterns and Anti-Patterns For Building with AI
Thomas Wiecki
Founder of PyMC Labs and co-author of PyMC
PyMC Labs
Episode: Episode 58: Building GenAI Systems That Make Business Decisions with Thomas Wiecki (PyMC Labs)
Shreya Shankar
PhD candidate in human-centered data management systems at UC Berkeley, with prior experience in ML engineering at major tech companies.
UC Berkeley
Episode: Episode 57: AI Agents and LLM Judges at Scale: Processing Millions of Documents (Without Breaking the Bank)
Zach Mueller
Technical Lead at Hugging Face, working on the Accelerate Framework and Transformer Trainer API.
Hugging Face
Episode: Episode 54: Scaling AI: From Colab to Clusters — A Practitioner’s Guide to Distributed Training and Inference
Samuel Colvin
Creator of Pydantic and founder of Logfire
Logfire
Episode: Episode 53: Human-Seeded Evals & Self-Tuning Agents: Samuel Colvin on Shipping Reliable LLMs
Eric Ma
Leads research data science in the data science and AI group at Moderna Therapeutics
Moderna Therapeutics
Episode: Episode 52: Why Most LLM Products Break at Retrieval (And How to Fix Them)
Philip Carter
Former Principal PM at Honeycomb and now Product Management Director at Salesforce
Salesforce
Episode: Episode 51: Why We Built an MCP Server and What Broke First

Host

Hugo Bowne-Anderson
Host and producer, Hugo Bowne-Anderson, is a data scientist with a wealth of experience in machine learning and AI. He facilitates long-form discussions that aim to illuminate complex topics in the realm of data science, making them accessible to a broad audience.

Reviews

4.9 out of 5 stars from 41 ratings
  • 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.

Listeners appreciate the critical and informative conversations, finding them valuable for both new and experienced professionals in the data space.
The podcast is noted for its depth and the quality of its guests, indicating a strong reputation within the industry.

Chart Rankings

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

Apple Podcasts
#98
Norway/Technology
Apple Podcasts
#176
India/Technology

Talking Points

Recent interactions between the hosts and their guests.

Episode 61: The AI Agent Reliability Cliff: What Happens When Tools Fail in Production
Q: Can you help me mind-meld these seemingly contradictory aspects of agent adoption and unreliability?
The growth in agent adoption is fueled by financial investments despite their unpredictability, suggesting a gap between marketing and operational realities.
Episode 61: The AI Agent Reliability Cliff: What Happens When Tools Fail in Production
Q: What are two to three lessons that jump off the page for you with respect to agents currently?
Keep things as simple as possible, track your application for failure modes, and ensure high-quality data for your LLM calls.
Episode 60: 10 Things I Hate About AI Evals with Hamel Husain
Q: What should teams prioritize when starting evaluations?
Begin with error analysis to inform what to prioritize and what evaluations to write.
Episode 60: 10 Things I Hate About AI Evals with Hamel Husain
Q: Can you define what evals are?
Evals are a systematic way of measuring an AI application.
Episode 60: 10 Things I Hate About AI Evals with Hamel Husain
Q: Why is it important to have evaluations (evals) for AI applications?
It's crucial for measuring performance and knowing if you're making progress.

Audience Metrics

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

Listeners per Episode
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?

Focus on critical discussions around data science, machine learning, and AI, this podcast explores the challenges and innovations shaping the field. Hosted by a seasoned data scientist, it features long-format conversations with experts who share their insights on various aspects of data, showcasing practical applications and emerging trends. Listeners can expect to learn from seasoned professionals, whether they are newcomers eager to understand the industry or veterans looking to discover different perspectives and the latest developments.

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How many episodes of Vanishing Gradients are there?

Vanishing Gradients launched 4 years ago and published 61 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. Alex Strick van Linschoten
2. Bryan Bischof
3. John Berryman
4. Thomas Wiecki
5. Shreya Shankar
6. Zach Mueller
7. Samuel Colvin
8. Eric Ma

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