Large Language Models (LLMs) are a hot Generative AI topic and everyone wants them in their WebRTC application! Use cases range from real-time in-call assistance to contact center agents, passing through post-call analysis, and even powering voice bots that are capable of answering calls without any human
In the previous posts of our Polybot.ai translator bot (“Polly”) series, we looked at AI + WebRTC product development, brand creation and UI, and also how to successfully build prompts for interacting with the Large Language Model (LLM). In this final post, we will take a look
Prompt engineering involves organizing text so that a Generative AI Large Language Model (LLM) can interpret input and generate an expected or desired output. Imagine a friend is making you a sandwich and you want them to prepare it just the way you like it. You say,
Voicebots offer efficient resolution of common customer inquiries, making them an indispensable component of today’s customer service flows. In previous posts, we have seen how you enhance the capabilities of voicebots using the power of LLMs and also integrate such capabilities in a web interface using WebRTC,
