#129 Bayesian Deep Learning & AI for Science with Vincent Fortuin

Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Intro to Bayes Course (first 2 lessons free)Advanced Regression Course (first 2 lessons free)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)Takeaways:The hype around AI in science often fails to deliver practical results.Bayesian deep learning combines the strengths of deep learning and Bayesian statistics.Fine-tuning LLMs with Bayesian methods improves prediction calibration.There is no single dominant library for Bayesian deep learning yet.Real-world applications of Bayesian deep learning exist in various fields.Prior knowledge is crucial for the effectiveness of Bayesian deep learning.Data efficiency in AI can be enhanced by incorporating prior knowledge.Generative AI and Bayesian deep learning can inform each other.The complexity of a problem influences the choice between Bayesian and traditional deep learning.Meta-learning enhances the efficiency of Bayesian models.PAC-Bayesian theory merges Bayesian and frequentist ideas.Laplace inference offers a cost-effective approximation.Subspace inference can optimize parameter efficiency.Bayesian deep learning is crucial for reliable predictions.Effective communication of uncertainty is essential.Realistic benchmarks are needed for Bayesian methodsCollaboration and communication in the AI community are vital.Chapters:00:00 Introduction to Bayesian Deep Learning06:12 Vincent's Journey into Machine Learning12:42 Defining Bayesian Deep Learning17:23 Current Landscape of Bayesian Libraries22:02 Real-World Applications of Bayesian Deep Learning24:29 When to Use Bayesian Deep Learning29:36 Data Efficient AI and Generative Modeling31:59 Exploring Generative AI and Meta-Learning34:19 Understanding Bayesian Deep Learning and Prior Knowledge39:01 Algorithms for Bayesian Deep Learning Models43:25 Advancements in Efficient Inference Techniques49:35 The Future of AI Models and Reliability52:47 Advice for Aspiring Researchers in AI56:06 Future Projects and Research DirectionsThank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade,...