Episode 28: Beyond Supervised Learning: The Rise of In-Context Learning with LLMs
Description
Hugo speaks with Alan Nichol, co-founder and CTO of Rasa, where they build software to enable developers to create enterprise-grade conversational AI and chatbot systems across industries like telcos, healthcare, fintech, and government.
What's super cool is that Alan and the Rasa team have been doing this type of thing for over a decade, giving them a wealth of wisdom on how to effectively incorporate LLMs into chatbots - and how not to. For example, if you want a chatbot that takes specific and important actions like transferring money, do you want to fully entrust the conversation to one big LLM like ChatGPT, or secure what the LLMs can do inside key business logic?
In this episode, they also dive into the history of conversational AI and explore how the advent of LLMs is reshaping the field. Alan shares his perspective on how supervised learning has failed us in some ways and discusses what he sees as the most overrated and underrated aspects of LLMs.
Alan offers advice for those looking to work with LLMs and conversational AI, emphasizing the importance of not sleeping on proven techniques and looking beyond the latest hype. In a live demo, he showcases Rasa's Calm (Conversational AI with Language Models), which allows developers to define business logic declaratively and separate it from the LLM, enabling reliable execution of conversational flows.
LINKS
The livestream on YouTube
Alan's Rasa CALM Demo: Building Conversational AI with LLMs
Alan on twitter.com
Rasa
CALM, an LLM-native approach to building reliable conversational AI
Task-Oriented Dialogue with In-Context Learning
'We don’t know how to build conversational software yet' by Alan Nicol
Vanishing Gradients on Twitter
Hugo on Twitter
Upcoming Livestreams
Lessons from a Year of Building with LLMs
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