Emmanuel Maggiori

Emmanuel Maggiori, an AI expert and author, dives into the pitfalls of AI in this insightful discussion. He explains why large language models (LLMs) can excel yet fail dramatically, particularly when handling basic tasks. Emmanuel details the common reasons behind AI project failures, emphasizing the importance of realistic AI adoption in businesses. He also highlights the concept of hallucinations in AI and shares advice for engineers to stay relevant in a rapidly evolving landscape. His perspective helps demystify the tech while grounding expectations.

Emmanuel Maggiori is an AI researcher and author whose work demystifies the intricacies of Large Language Models (LLMs). He explains how tokens are the building blocks of AI language processing and elaborates on context windows and embeddings that enable models to understand meaning. Emmanuel delves into the controversial training methods, including Reinforcement Learning with Human Feedback, and discusses the potential pitfalls like AI hallucinations and copyright issues. His insights make complex AI concepts accessible for developers.