Keynote- From Next Token Prediction to Reasoning and Beyond
Large Language Models (LLMs) have grown into prominence as some of the most popular technological artifacts of the day. This talk will provide a highly accessible and visual overview of LLM concepts relevant to today's data professionals. This includes looking at present-day Transformer architectures, tokenizers, reward models, reasoning LLMs, agentic trajectories, and the various training stages of a large language model including next-word prediction, instruction-tuning, preference-tuning, and reinforcement learning.
Saturday at 13:40 in the Grand Hall!
Jay Alammar is co-author of Hands-On Large Language Models, published by O'Reilly Media. and Director and Engineering Fellow at Cohere (a pioneering creator of large language models).
Through his popular AI/ML blog, Jay has helped millions of researchers and engineers visually understand machine learning tools and concepts (e.g., The Illustrated Transformers, BERT, DeepSeek-R1, and others).