Today we’re joined by Sebastian Raschka, an assistant professor at the University of Wisconsin-Madison and lead AI educator at Grid.ai. In our conversation with Sebastian, we explore his work around AI education, including the “hands-on” philosophy that he takes when building these courses, his recent book Machine Learning with PyTorch and Scikit-Learn, his advise to beginners in the field when they’re trying to choose tools and frameworks, and more. We also discuss his work on Pytorch Lightning, a platform that allows users to organize their code and integrate it into other technologies, before switching gears and discuss his recent research efforts around ordinal regression, including a ton of great references that we’ll link on the show notes page below! The complete show notes for this episode can be found at twimlai.com/go/565

Sebastian Raschka discusses developing and training large language models (LLMs) from scratch, covering topics like prompt engineering, fine-tuning, and RAG systems. They explore the skills, resources, and hardware needed, the lifecycle of LLMs, live coding to create a spam classifier, and the importance of hands-on experience. They also touch on using PyTorch Lightning and fabric for managing large models, and reveal insights on techniques in natural language processing models and evaluating LLMs for classification problems.

Sebastian Raschka, a Senior Staff Research Engineer at Lightning AI and bestselling author, dives into the art of building large language models. He shares insights on two significant open-source libraries, PyTorch Lightning and LitGPT, that enhance LLM training and deployment. The discussion shifts to his new book, where he outlines essential steps in LLM training and contrasts models like GPT-2 with the latest Llama 3. Sebastian also explores the universe of multimodal LLMs and their potential, highlighting exciting developments on the horizon.

Sebastian Raschka, Lead AI Educator at Lightning and author, discusses learning ML, responsible AI, AGI, and more. Topics include his career background, working in academia vs industry, early ML projects, creating a book with Chat GPT, dangers of overconfidence in ML models, balancing learning from scratch with existing solutions, and the importance of having fun and being patient.

Sebastian Raschka, a staff research engineer at Lightning AI and AI educator, dives into the dynamic landscape of open language models. He discusses the evolution of Llama 3.1 and its implications for AI research. Sebastian shares insights from his experience as an Arxiv moderator, shedding light on the challenges of navigating academic papers. The conversation also covers advancements in model training techniques, the importance of ethics in AI, and how open access enhances AI education. Tune in for a fascinating look at the future of AI and language models!