We're taking a slight detour from modeling best practices to explore questions about AI and consciousness. With special guest Michael Herman, co-founder of Monitaur and TestDriven.io, the team discusses different philosophical perspectives on consciousness and how these apply to AI. They also discuss the potential dangers of AI in its current state and why starting fresh instead of iterating can make all the difference in achieving characteristics of AI that might resemble consciousness.
Episode 13. Data scientists, researchers, engineers, marketers, and risk leaders find themselves at a crossroads to expand their skills or risk obsolescence. The hosts discuss how a growth mindset and "the fundamentals" of AI can help.
Get ready for 2024 and a brand new episode! We discuss non-parametric statistics in data analysis and AI modeling. Learn more about applications in user research methods, as well as the importance of key assumptions in statistics and data modeling that must not be overlooked.
Episode 11. It's the end of 2023 and our first season. The hosts reflect on what's happened with the fundamentals of AI regulation, data privacy, and ethics. Spoiler alert: a lot! And we're excited to share our outlook for AI in 2024.
Episode 10. Joshua Pyle joins us in a discussion about managing bias in the actuarial sciences. Together with Andrew's and Sid's perspectives from both the economic and data science fields, this trio delivers an interdisciplinary conversation about bias that you'll only find here.
Episode 9. Continuing our series run about model validation. In this episode, the hosts focus on aspects of performance, why we need to do statistics correctly, and not use metrics without understanding how they work, to ensure that models are evaluated in a meaningful way.
Episode 8. This is the first in a series of episodes dedicated to model validation. Today, we focus on model robustness and resilience. From complex financial systems to why your gym might be overcrowded at New Year's, you've been directly affected by these aspects of model validation.
Episode 7. To use or not to use? That is the question about digital twins that the fundamentalists explore. Many solutions continue to be proposed for making AI systems safer, but can digital twins really deliver for AI what we know they can do for physical systems? Tune in and find out.
Episode 6. What does systems engineering have to do with AI fundamentals? In this episode, the team discusses what data and computer science as professions can learn from systems engineering, and how the methods and mindset of the latter can boost the quality of AI-based innovations.
Episode 4. The AI Fundamentalists welcome Christoph Molnar to discuss the characteristics of a modeling mindset in a rapidly innovating world. We hope you enjoy this enlightening discussion from a model builder's point of view.
Episode 3. Get ready because we're bringing stats back! An AI model can only learn from the data it has seen. And business problems can be solved with the right data. The Fundamentalists break down the basics of data from collection to regulation to bias to quality in AI.