The mad genius of using LLMs as classifiers with Katherine Munro, Swisscom

In this episode, Kane Simms is joined by Katherine Munro,
Conversational AI Engineer at Swisscom, for a deep dive into what
might sound like an odd pairing: using LLMs to classify customer
intents.


Large Language Models (LLMs) are powerful, multi-purpose tools.
But would you trust one to handle the precision of a
classification task?


It’s an unlikely fit for an LLM. Classifiers typically need to be
fast, accurate, and interpretable. LLMs are slow, random
black-boxes. Classifiers need to output a single label. LLMs
never stop talking.


And yet, there are good reasons to use LLMs for such tasks, and
emerging architectures and techniques. Many real-world use cases
need a classifier, and many data and product development teams
will soon find themselves wondering: could GPT handle that?


If that sounds like you, then check out this extended episode to
explore how Switzerland’s largest telecommunications provider
tackles this issue while building a next-generation AI
assistant. 





This episode is brought to you by NLX.


NLX is a conversational AI platform enabling brands to build
and manage chat, voice and multimodal applications. NLX’s
patented Voice+ technology synchronizes voice with digital
channels, making it possible to automate complex use cases
typically handled by a human agent. When a customer calls, the
voice AI guides them to resolve their inquiry through
self-service using the brand’s digital asset, resulting in
automation and CSAT scores well above industry average. Just
ask United Airlines.





Shownotes:


"The Handbook of Data Science and AI: Generate Value from Data
with Machine Learning and Data Analytics" - Available on Amazon:
https://a.co/d/3wNN9cv


Katherine's website: http://katherine-munro.com/


Subscribe to VUX World: https://vuxworld.typeform.com/to/Qlo5aaeW


Subscribe to The AI Ultimatum Substack:
https://open.substack.com/pub/kanesimms


Get in touch with Kane on LinkedIn:
https://www.linkedin.com/in/kanesimms/


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