Exclusive Industry Insights: Perspectives and Predictions from World Class Experts

As the journey of this book unfolds, exploring the vast expanse of natural language processing (NLP) and large language models (LLMs), we arrive at a pivotal juncture in Chapter 11. This chapter is not just a culmination of the themes and discussions that preceded it but also a bridge to the untapped potential and imminent challenges that lie ahead in the realm of NLP and LLMs. Our endeavor through the chapters has been to chart the evolution of NLP from its foundational concepts to the architectural marvels of LLMs, dissecting the intricacies of machine learning (ML) strategies, data preprocessing, model training, and the practical applications transforming industries and societal interactions.

The motivation for this chapter stems from an acute recognition of the pace at which NLP and LLM technologies are evolving and the multifaceted impact they wield on the fabric of our digital society. As we...

Overview of our experts

Let’s go through each of the experts’ introductions first.

Nitzan Mekel-Bobrov, PhD

Nitzan Mekel-Bobrov is the Chief AI Officer (CAIO) at eBay where he runs the company-wide strategy for AI and technology innovation. An R&D scientist by training, Nitzan has spent his career developing machine intelligence systems, directly integrated into mission-critical products. Having led enterprise AI organizations across multiple industries, including healthcare, financial services, and e-commerce, Nitzan is a thought leader in the delivery of transformational impact through real-time AI at scale, changing companies’ business models and core value propositions to their customers. Nitzan received his PhD from the University of Chicago and currently resides in New York City as the GM of eBay NYC.

David Sontag, PhD

David Sontag is a Professor of Electrical Engineering and Computer Science at MIT, part of both the Institute for Medical Engineering & Science and the Computer Science & Artificial Intelligence Laboratory. His research focuses on advancing ML and AI and using these to transform healthcare. Previously, he was an Assistant Professor of Computer Science and Data Science at New York University, part of the Computer Intelligence, Learning, Vision, and Robotics (CILVR) lab. He is also Co-Founder and CEO of Layer Health.

John D. Halamka, M.D., M.S.

John D. Halamka, M.D., M.S., President of the Mayo Clinic Platform, leads a transformative digital health initiative impacting 45 million people in 2023. With over 40 years in healthcare information strategy and emergency medicine, his work spans serving at Beth Israel Deaconess Medical Center (BIDMC), advising administrations from George W. Bush to Barack Obama, and teaching as a Harvard Medical School professor. A Stanford, UCSF, and UC Berkeley alumnus, Halamka is also a practicing Emergency Medicine Professor at Mayo Clinic College of Medicine and Science. An author of 15 books and hundreds of articles, he was elected to the National Academy of Medicine in 2020.

Xavier Amatriain, PhD

Xavier Amatriain was most recently VP of AI Product Strategy at LinkedIn, where he led company-wide generative AI efforts all the way from platform and infrastructure to product features. He is also a board member of Curai Health, a healthcare/AI start-up that he cofounded and was CTO of until 2022. Prior to this, he led engineering at Quora and was Research/Engineering Director at Netflix, where he started and led the Algorithms team building the famous Netflix recommendations. Xavier started his career as a researcher both in academia and industry. With over 100 research publications (and 6,000 citations), he is best known for his work on AI and ML in general, and recommender systems in particular.

Melanie Garson, PhD

Dr. Melanie Garson, Cyber Policy & Tech Geopolitics Lead at the Tony Blair Institute, delves into cyber policy, geopolitics AI, compute and the internet, the rise of tech companies as geopolitical actors, data governance, as well as the intersection of disruptive tech, foreign policy, defense, and diplomacy. At University College London, she’s an Associate Professor teaching on the impact of emerging technologies on conflict, negotiation, and tech diplomacy. A regular speaker at international forums and media, including BBC and CNN, Melanie’s background includes being an accredited mediator and solicitor at Freshfields Bruckhaus Deringer. She holds a PhD from University College London and a master’s from the Fletcher School of Law and Diplomacy.

Our questions and the experts’ answers

We had an opportunity to pick the brains of each of these experienced folks and learn about how their career intersects and leverage AI and LLMs. We tailored questions to each of them so to allow them to teach us through their insights and perspectives. We found these discussions to be rewarding as they shed light on topics that are common and would be valuable for anyone who reads this book. Let’s dive right in.

Nitzan Mekel-Bobrov

Nitzan brings the CAIO’s perspective as he and Ebay are encountering the vast potential that AI and LLM’s have to offer. He shares many diversified aspects that the CAIO has to address and decide on.

Let’s go through the questions and answers with Nitzan Mekel-Bobrov.

Q1.1 – Future of LLM – hybrid learning paradigms: In light of the evolving landscape of learning schemes, what do you envision as the next breakthrough in combining different learning paradigms...

Summary

In this concluding chapter of our exploration into the dynamic world of NLP and LLMs, we have had the privilege of engaging with experts across various fields. Their insightful discussions have illuminated intricate developments, legal considerations, operational approaches, regulatory influences, and emerging capabilities of LLMs. Through their expert lenses, we delved into pressing issues such as creating equitable datasets, advancing NLP technologies, navigating privacy protections in research, restructuring organizations around AI, and anticipating breakthroughs in learning paradigms.

The dialogue with these luminaries has underscored a common theme: the intersection of technological innovation with ethical, legal, and organizational considerations. As we ponder strategies to mitigate biases in datasets, envision the future of hybrid learning paradigms, and assess the impact of foundation models on data ownership, it becomes clear that the evolution of NLP and LLMs is...