Inside Probabilistic AI: Bayesian Modeling and PyMC with Thomas Wiecki

In this episode, we sit down with Thomas Wiecki, co-creator of PyMC and CEO of PyMC Labs, to explore the evolving frontier of probabilistic AI. With roots in computational psychiatry and a passion for Bayesian modeling, Thomas walks us through how probabilistic methods unlock better decision-making by quantifying uncertainty—something traditional AI often glosses over. We dive deep into real-world applications, from marketing mix modeling to synthetic consumers, and hear about Thomas's upcoming session at ODSC East. Whether you're a marketer, data scientist, or just AI-curious, this episode provides an illuminating perspective on building interpretable, trustworthy AI systems. Key Topics Covered Defining Probabilistic AI: What distinguishes probabilistic AI from traditional machine learning and generative models. Why uncertainty is a feature, not a bug—and how it enables better risk-aware decisions. Marketing Mix Modeling (MMM): How PyMC Labs applies Bayesian models to measure marketing effectiveness across channels. Real-world examples of ROI estimation, saturation detection, and spend optimization. AI Agents and Natural Language Interfaces: How PyMC Labs built AI agents to interpret and interact with complex statistical models. Bridging the gap between marketers and data scientists through conversational AI. Synthetic Consumers and Product Testing: Using LLMs to simulate consumer feedback and behavior before market release. How these systems complement surveys and reduce time-to-insight. Building Trustworthy AI: Why transparency and causal reasoning are critical for adoption in business. The role of PyMC in making statistical modeling accessible, powerful, and interpretable. Community and Open Source: The evolution of the PyMC ecosystem and the role of its global contributor base. How open-source collaboration leads to robust, production-ready tools. Scalability and Next-Gen Tooling: Leveraging GPUs, Apple Silicon, and frameworks like Aesara, JAX, and MLX to scale inference. The future of PyMC agents and integrations with platforms like Databricks and MLFlow. Memorable Outtakes “Probabilistic AI doesn’t just make predictions—it tells you how confident it is. That’s a game-changer for real-world decisions.” “The agent can now say, ‘I'm not sure about this prediction—you might want to collect more data.’ That’s the kind of reasoning we need from AI.” “Synthetic consumers sound like science fiction, but they’re a practical tool for product development today.” “We’ve moved from dashboards to conversations. Marketers can now ask a question—and get a data-driven, contextual answer back.” “Open source isn’t just about free tools. It’s about building the best ideas with the best minds from around the world.” Resources: - Thomas’s LinkedIn: https://www.linkedin.com/in/twiecki/ - Thomas’s Website: https://www.pymc-labs.com/ - Thomas’s GitHub: https://github.com/twiecki - PyMC: https://www.pymc.io/welcome.html - PyMC-Labs: https://www.pymc-labs.com/ - PyMC GitHub: https://github.com/pymc-devs/pymc - Marketing Mix Modeling Agent: https://www.pymc-labs.com/blog-posts/the-ai-mmm-agent/ - Thomas’s ODSC East session, “Automating Bayesian Marketing Mix Modeling with an AI-Powered Assistant,”: https://odsc.com/speakers/automating-bayesian-marketing-mix-modeling-with-an-ai-powered-assistant/ - Allen Downey’s (also with PyMC) ODSC East session, “Mastering Time Series Analysis with StatsModels: From Decomposition to ARIMA,”: https://odsc.com/speakers/mastering-time-series-analysis-with-statsmodels-from-decomposition-to-arima/ Sponsored by This episode was sponsored by: 🎤 ODSC East 2025 – The Leading AI Builders Conference – https://odsc.com/boston/ Join us from May 13th to 15th in Boston for hands-on workshops, training sessions, and cutting-edge AI talks covering generative AI, LLMOps, and AI-driven automation. 🔥 Use the exclusive code ODSCPodcast for an additional 10% off any ticket type!