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Artwork for The TWIML AI Podcast

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Sam Charrington
Machine Learning
Generative AI
Large Language Models
Artificial Intelligence
AI Agents
Reinforcement Learning
Robotics
Natural Language Processing
AI Orchestration
Smart Cities
Openai
AI Inference
Interpretability
Agentic AI
AWS
Llms
AI Applications
AI Research
Capital One
Edge Computing

Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentato... more

PublishesTwice monthlyEpisodes786Founded10 years ago
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Artwork for The TWIML AI Podcast

Latest Episodes

In this episode, Jure Leskovec, co-founder and chief scientist at Kumo and professor of computer science at Stanford, joins us to explore two fronts of his work: AI for science and relational deep learning. We begin with AI Virtual Cell, a multiscale... more

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In this episode, Scott Clark, co-founder and CEO of Distributional, joins us to explore how teams can reliably operate and improve complex LLM systems and agents in production. Scott introduces a Maslow’s hierarchy of observability: telemetry for log... more

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In this episode, Philip Kiely, head of AI education at Baseten, joins us to unpack the fast-evolving discipline of inference engineering. We explore why inference has become the stickiest and most critical workload in AI, how it blends GPU programmin... more

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In this episode, Rashmi Shetty, senior director of enterprise generative AI platform at Capital One, joins us to explore how the company is designing, deploying, and scaling multi-agent systems in a highly regulated environment. Rashmi walks us throu... more

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Recent Guests

Jure Leskovec
Co-founder and chief scientist at Kumo; Professor at Stanford University
Kumo; Stanford University
Episode: Relational Foundation Models for Enterprise Data with Jure Leskovec - #768
Scott Clark
Co-founder and CEO of Distributional
Distributional
Episode: How to Find the Agent Failures Your Evals Miss with Scott Clark - #767
Philip Kiely
Head of AI Education at Baseten
Baseten
Episode: How to Engineer AI Inference Systems with Philip Kiely - #766
Rashmi Shetty
Senior Director of Enterprise Generative AI Platform at Capital One
Capital One
Episode: How Capital One Delivers Multi-Agent Systems with Rashmi Shetty - #765
Stefano Ermon
CEO of Inception; Professor at Stanford University
Inception; Stanford University
Episode: The Race to Production-Grade Diffusion LLMs with Stefano Ermon - #764
Siddhant Pardeshi
Co-founder and CTO of Blitzy
Blitzy
Episode: Agent Swarms and Knowledge Graphs for Autonomous Software Development with Siddhant Pardeshi - #763
Sebastian Raschka
Independent LLM researcher
Independent
Episode: AI Trends 2026: OpenClaw Agents, Reasoning LLMs, and More with Sebastian Raschka - #762
Yejin Choi
Professor and senior fellow at Stanford University in the Computer Science Department and Institute for Human-Centered AI
Stanford University
Episode: The Evolution of Reasoning in Small Language Models with Yejin Choi - #761
Nikita Rudin
Co-founder and CEO of Flexion Robotics
Flexion Robotics
Episode: Intelligent Robots in 2026: Are We There Yet? with Nikita Rudin - #760

Host

Sam Charrington
Host of The TWIML AI Podcast

Reviews

4.8 out of 5 stars from 931 ratings
  • Great

    Great podcast for keeping abreast of the latest in AI, always focused on the research, interesting conversations. No BS!

    Apple Podcasts
    5
    eoaur
    Germanya year ago
  • Awesome!

    Sam is an amazing host! Technical, kind and gets the best out of each guest. 10 starssss out of 5.

    Apple Podcasts
    5
    anxnsodkcoapsjdj
    United Statesa year ago
  • Excellent technical AI podcast

    Finally the podcast I’ve been looking for. Technical yet practical and approachable. Well done.

    Apple Podcasts
    5
    IL iPhone Guy
    United States2 years ago
  • Incredible Host makes machine learning easier to understand

    This show is fantastic due to Sam’s charismatic nature & skills as an incredible interviewer. He has some brilliant guests & does a great job of teasing a conversation to get really great insights other hosts may miss. He also does a great job of making complex subjects easier to understand. One of my have eps so far is with Sasha at Hugging Face. Sam has conversations you just can’t find online else where which makes it one of my all round favourites! Papillon Luck

    Apple Podcasts
    5
    Papillon Luck
    United Kingdom2 years ago
  • Excellent discussions of technical advances in AI

    Reliably the best technical podcast on AI. The host brings a continual flow of cutting edge researchers who share their knowledge of the latest advances in AI methods and emerging applications. Sam, the host, brings penetrating questions to extract new and cross-disciplinary insights. A quick way to keep up-to-date on industry trends and fundamental advances.

    Apple Podcasts
    5
    camnndmami
    United States2 years ago

Listeners Say

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

Guests are world-class researchers and practitioners.
Listeners praise technical depth and practical AI insights.
Audio quality and pacing are common topics in feedback.

Chart Rankings

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

Apple Podcasts
#146
United States/Technology
Apple Podcasts
#143
Canada/Technology
Apple Podcasts
#170
United Kingdom/Technology
Apple Podcasts
#154
France/Technology
Apple Podcasts
#242
Italy/Technology
Apple Podcasts
#34
Saudi Arabia/Technology

Talking Points

Recent interactions between the hosts and their guests.

Relational Foundation Models for Enterprise Data with Jure Leskovec - #768
Q: What are the deployment options and who are the customers?
The system can be deployed as SaaS or in private/public clouds, with customers like DoorDash for recommendations, Reddit for ad performance, Coinbase for blockchain-scale fraud and transaction analysis, and Databricks/Snowflake for sales modeling.
Relational Foundation Models for Enterprise Data with Jure Leskovec - #768
Q: How does the relational foundation model actually work in practice?
A pre-trained, domain-agnostic model encodes raw relational data as sub-graphs and uses in-context learning to predict tasks specified by prompts, enabling fast, single-pass predictions without traditional training, while handling large-scale graphs and heterogeneous data.
Relational Foundation Models for Enterprise Data with Jure Leskovec - #768
Q: Tell us a little about your research focus.
The guest describes Stanford-based and industry-aligned efforts in relational deep learning, highlighting AI for Science projects like AI Virtual Cell, and the goal of building models that reason over complex, multi-scale biomedical data to accelerate discoveries such as cancer therapies and molecule design.
How to Engineer AI Inference Systems with Philip Kiely - #766
Q: What are the dominant models or setups you're seeing, and what drives a company to go from one setup to another?
Philip outlines a product maturity cycle: starting with pro-token providers, moving to hyperscalers for scale or capacity, then toward dedicated inference providers like Baseten, and finally to in-house or edge deployments depending on needs and constraints.
How to Engineer AI Inference Systems with Philip Kiely - #766
Q: Where do you draw the line between the beginning and end of inference and the broader model-serving set of requirements?
The guest clarifies that model-serving encompasses end-to-end user request handling, with inference focusing on the GPU-side execution, and emphasizes owning the entire user journey as part of an effective inference discipline.

Audience Metrics

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

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Frequently Asked Questions About The TWIML AI Podcast

What is The TWIML AI Podcast about and what kind of topics does it cover?

A technical AI-focused program that features in-depth conversations with researchers and industry practitioners about the latest advances in machine learning, AI tooling, and enterprise deployment. Episodes commonly explore topics like reasoning in large models, agentic AI and multi-agent workflows, inference systems, production-grade deployments, and practical applications in finance, robotics, and software development. Notable gaps and trends include real-world deployments, governance and observability in complex AI systems, and the evolving balance between cutting-edge research and scalable, cost-conscious production. The show often highlights how enterprises are applying AI tools to automate workflows, improve decision making, and deliv... more

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Which podcasts are similar to The TWIML AI Podcast?

These podcasts share a similar audience with The TWIML AI Podcast:

1. Practical AI
2. Super Data Science: ML & AI Podcast with Jon Krohn
3. No Priors: Artificial Intelligence | Technology | Startups
4. NVIDIA AI Podcast
5. This Day in AI Podcast

How many episodes of The TWIML AI Podcast are there?

The TWIML AI Podcast launched 10 years ago and published 786 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 TWIML AI Podcast?

Recent guests on The TWIML AI Podcast include:

1. Jure Leskovec
2. Scott Clark
3. Philip Kiely
4. Rashmi Shetty
5. Stefano Ermon
6. Siddhant Pardeshi
7. Sebastian Raschka
8. Yejin Choi

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