Launched by OpenAI on November 30th, 2022, ChatGPT has already amassed 1 million users as the fastest-growing tech platform of all time, setting the internet on fire with next-level generative AI that’s captivating the imaginations of engineers, linguists, marketers, students, and more.
Those that will do this seamlessly—while prioritizing security and precision for their customers—will emerge as winners in the new age of generative and conversational AI. This is where the real magic happens for enterprises.Let’s explore what co-existence between current conversational AI solutions and ChatGPT looks like. First, we’ll cover what business-grade conversational AI requires for a successful deployment.
ChatGPT, and the LLM it’s based on, is rightfully impressive due to its ability to answer a slew of complex questions correctly, but it also generates a ton of inaccurate responses due to outdated data and the ability to be gamed into providing biased answers. When the assistant fails, there is no accountability – there’s no way of debugging the issue at hand or tracing/pinpointing the source of the inaccurate output.
Take the simple math example below. 2 is a natural number and integer, right? Not if you bias ChatGPT to think otherwise:ChatGPT can make up completely false answers which significantly reduces the trust in it. While originally expanding from chat via the website to voice via call centers, we had to undergo major alterations – optimizing length, adding context, and ensuring that we’d maximally reduced time to objective, or, time toWhile that may not seem long textually, the snippet above is actually a 45-second monologue when transferred to pure AI voice generation.