The AI Fundamentalists
By Dr. Andrew Clark & Sid Mangalik
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Image by Dr. Andrew Clark & Sid Mangalik
Category: Technology
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Episodes: 42
Description
A podcast about the fundamentals of safe and resilient modeling systems behind the AI that impacts our lives and our businesses.
| Episode | Date |
|---|---|
|
Big data, small data, and AI oversight with David Sandberg
|
Dec 09, 2025 |
|
Metaphysics and modern AI: What is space and time?
|
Nov 11, 2025 |
|
Metaphysics and modern AI: What is reality?
|
Oct 27, 2025 |
|
Metaphysics and modern AI: What is thinking? - Series Intro
|
Oct 07, 2025 |
|
AI in practice: Guardrails and security for LLMs
|
Sep 30, 2025 |
|
AI in practice: LLMs, psychology research, and mental health
|
Sep 04, 2025 |
|
LLM scaling: Is GPT-5 near the end of exponential growth?
|
Aug 19, 2025 |
|
AI governance: Building smarter AI agents from the fundamentals, part 4
|
Jul 22, 2025 |
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Linear programming: Building smarter AI agents from the fundamentals, part 3
|
Jul 08, 2025 |
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Utility functions: Building smarter AI agents from the fundamentals, part 2
|
Jun 12, 2025 |
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Mechanism design: Building smarter AI agents from the fundamentals, Part 1
|
May 20, 2025 |
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Principles, agents, and the chain of accountability in AI systems
|
May 08, 2025 |
|
Supervised machine learning for science with Christoph Molnar and Timo Freiesleben, Part 2
|
Mar 27, 2025 |
|
Supervised machine learning for science with Christoph Molnar and Timo Freiesleben, Part 1
|
Mar 25, 2025 |
|
The future of AI: Exploring modeling paradigms
|
Feb 25, 2025 |
|
Agentic AI: Here we go again
|
Feb 01, 2025 |
|
Contextual integrity and differential privacy: Theory vs. application with Sebastian Benthall
|
Jan 07, 2025 |
|
Model documentation: Beyond model cards and system cards in AI governance
|
Nov 09, 2024 |
|
New paths in AI: Rethinking LLMs and model risk strategies
|
Oct 08, 2024 |
|
Complex systems: What data science can learn from astrophysics with Rachel Losacco
|
Sep 04, 2024 |
|
Preparing AI for the unexpected: Lessons from recent IT incidents
|
Aug 20, 2024 |
|
Exploring the NIST AI Risk Management Framework (RMF) with Patrick Hall
|
Jul 30, 2024 |
|
Data lineage and AI: Ensuring quality and compliance with Matt Barlin
|
Jul 03, 2024 |
|
Differential privacy: Balancing data privacy and utility in AI
|
Jun 04, 2024 |
|
Responsible AI: Does it help or hurt innovation? With Anthony Habayeb
|
May 07, 2024 |
|
Baseline modeling and its critical role in AI and business performance
|
Apr 17, 2024 |
|
Information theory and the complexities of AI model monitoring
|
Mar 26, 2024 |
|
The importance of anomaly detection in AI
|
Mar 06, 2024 |
|
What is consciousness, and does AI have it?
|
Feb 13, 2024 |
|
Upskilling for AI: Roles, organizations, and new mindsets
|
Jan 25, 2024 |
|
Non-parametric statistics
|
Jan 10, 2024 |
|
AI regulation, data privacy, and ethics - 2023 summarized
|
Dec 19, 2023 |
|
Managing bias in the actuarial sciences with Joshua Pyle, FCAS
|
Dec 07, 2023 |
|
Model Validation: Performance
|
Nov 04, 2023 |
|
Model validation: Robustness and resilience
|
Oct 11, 2023 |
|
Digital twins in AI systems
|
Sep 20, 2023 |
|
Fundamentals of systems engineering
|
Aug 23, 2023 |
|
Synthetic Data in AI
|
Aug 08, 2023 |
|
Modeling with Christoph Molnar
|
Jul 25, 2023 |
|
Why data matters | The right data for the right objective with AI
|
Jun 27, 2023 |
|
Truth-based AI: LLMs and knowledge graphs - back to basics
|
May 31, 2023 |
|
Why AI Fundamentals? | AI rigor in engineering | Generative AI isn't new | Data quality matters in machine learning
|
May 11, 2023 |