Over the past few months, there has been colossal hype and speculation about the implications of large language models (LLMs) such as OpenAI’s ChatGPT and, most recently, GPT4. ChatGPT, in particular, reached 100 million users in two months, making it the fastest-growing consumer application of all time. 

It isn’t clear yet what kind of impact LLMs will have, and opinions vary hugely. Many experts argue that LLMs will have little impact (early academic research suggests that the capability of LLMs is restricted to formal linguistic competence) or that even a near-infinite volume of text-based training data is still severely limiting. 

Others argue the opposite, that is, the businesses that understand the significance of this change — and act on it first — will be at a considerable advantage.

What we do know now is that generative AI has captured the imagination of the wider public and that it can produce first drafts and generate ideas virtually instantaneously. We also know that it can struggle with accuracy. 

Despite the open questions about this new technology, companies are now searching for ways to apply it. 

Is there a way to cut through the polarising arguments, hype and hyperbole and think clearly about where the technology will hit home first? 

Our guest believes there is. 

Marc Ramos is the Chief Learning Officer of Cornerstone, a global leader in learning and talent management technologies. With over 25 years of experience as a learning leader, Marc has worked with Google, Microsoft, Accenture, Oracle, and more. His insights and expertise have helped organisations develop and implement effective learning strategies that drive business results. In this episode, we discuss the implications of large language models and explore Marc's perspective on the latest trends and innovations in learning and development.