How to match the right AI model with a functionality

LONDON, UNITED KINGDOM, October 23, 2023 /EINPresswire.com/ -- In an article published on Business Reporter, Yan Zhang, COO of PolyAI explains why generative AI shouldn’t be used indiscriminately for all the pain points and use cases that present themselves in a business context. Generative AI is similar to an overconfident employee who will never say they don’t know the answer but, instead, will improvise a seemingly plausible answer. Lacking the right level of consistency, large language models (LLMs) aren’t capable of providing reliable solutions to real-world problems by themselves. Nevertheless, generative AI will be a crucial part of the conversational AI technology stack, but its deployment has to be either limited to use cases that allow it to play to its strengths, or it should be leveraged in tandem with speech recognition and spoken language understanding technologies.

Generative AI, for example, can do a great job in procedural customer service transactions, such as booking a hotel room or a doctor’s appointment. It has great potential in summarising insights from customer conversations too. For more complex use cases, however, such as generating responses for less frequently asked questions, it needs to be augmented with other technologies. Meanwhile, in cases where intent-based models are faster, cheaper and more accurate, generative AI should stay on the sidelines. To help make the best choices, PolyAI’s orchestration engine enables businesses to determine whether a particular part of a conversation calls for an intent or a generative model to be handled the most effectively and reliably.

To find out more about how to choose between various AI models to address a use case, read the article.

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About PolyAI

PolyAI builds enterprise voice assistants that carry on natural conversations with customers to solve their problems. Its customers include some of the leading names in banking, hospitality, insurance, retail, and telecommunications. PolyAI voice assistants, which feel, sound, and speak like a human, use conversational AI to automate common customer support transactions, such as customer identification and verification – with 24/7 availability, no wait times and exhaustive data.

https://poly.ai/

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