767: Open-Source LLM Libraries and Techniques, with Dr. Sebastian Raschka

Jon Krohn sits down with Sebastian Raschka to discuss his latest book, Machine Learning Q and AI, the open-source libraries developed by Lightning AI, how to exploit the greatest opportunities for LLM development, and what’s on the horizon for LLMs. This episode is brought to you by the DataConnect Conference (https://www.dataconnectconf.com/dccwest/conference), and by Data Universe, the out-of-this-world data conference (https://datauniverse2024.com). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information. In this episode you will learn: • All about Machine Learning Q and AI [04:13] • Sebastian Raschka’s role as Staff Research Engineer at Lightning AI [19:21] • PyTorch Lightning’s and Lightning Fabric’s capabilities [39:32] • Large language models: Opportunities and challenges [43:35] • DoRA vs LoRA [48:56] • How to be a successful AI educator [1:34:18] Additional materials: www.superdatascience.com/767

Om Podcasten

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.