Q: Why is there so much hype about ChatGPT? What makes it different from previous innovations in conversational AI?
A: Well, anyone who has a a free account is posting on social media and that has caused quite a stir. But as a practical matter LLMs (large language models) are trained on internet data and present a great opportunity for prosumers and consumer-oriented creators to build stuff.
Now that being said, ChatGPT is an incredibly exciting development in Conversational AI. Chatbots allow interaction in a seemingly ‘intelligent’ conversational manner, however ChatGPT produces output that appears to have actually understood the question, the content and the context. This creates a very human-like natural interaction, often insightful, sometimes profound.
But it’s still nascent technology; ChatGPT in its current form is best used for creative endeavors like content creation and ideation. It is still not great at things like precise answers to internal content or complex math equations. ChatGPT should be seen as a glimpse of what is yet to come, namely, an exciting future for AI helping humans in meaningful ways.
Q: So is ChatGPT applicable to the enterprise? What are the challenges of LLMs?
A: While this is a great leap forward in language models and this should truly be commended, sufficiently large language models’ ability to be both generic and generative, indicates to me that there’s a substantial risk we do not yet fully understand when and if the model is trained on enterprise data. In the short term, I don’t see an enterprise customer feeding their employee data or for our healthcare customers, patient data into a large language model of this sort. The security and compliance will simply not pass muster at virtually any company in this stage of AI evolution for GPT-3 or any other large language models.
What is frequently lost in the shuffle in Silicon valley as we rave about these new developments is that enterprises are not dependent on internet data. Rather, they have their own proprietary data; customer records, patient records, medication records, IT ticket records, and they demand precise answers with utmost accuracy. The expectation is that companies like Avaamo run their AI models on this proprietary data and they are what they are — closed and carefully monitored. The price of wrong answers is very high. This last 10% is the hardest to do.
A case in point, one of the charming but flawed issues with large language models is a behavior called “stochastic parroting” or statistically analyzing text strings and “making thing up.” It sounds good, but it is false. Sam Altman, the CEO and Cofounder of OpenAI, admitted as much in a tweet over the weekend saying “it’s a mistake to be relying on it [ChatGPT] for anything important right now.”
ChatGPT is incredibly limited, but good enough at some things to create a misleading impression of greatness.
it’s a mistake to be relying on it for anything important right now. it’s a preview of progress; we have lots of work to do on robustness and truthfulness.
–Sam Altman, CEO and Co-founder of OpenAI
Q: OK, so what is Avaamo doing with ChatGPT capabilities?
A: There’s no denying that what is ground-breaking about ChatGPT is its human-like interactions and the way it understands content and context. Avaamo will be rolling this set of Generative AI capabilities to deliver a better human-like experience — is it human or AI? — but only after very careful evaluation on how it will affect enterprise security and compliance requirements as well as its applicability to enterprise data like PHI. We’re still in the early days — stay tuned.
Overall, while GPT-3 has the potential to be a game-changer in the field of natural language processing but it is important for enterprises to carefully consider the limitations and challenges of using the model before making any decisions. With the right approach, GPT-3 can be a valuable tool, but it is not a silver bullet.
About Avaamo
Avaamo is an omnichannel conversational AI platform that allows global enterprises to automate and deliver exceptional self-service experiences to customers, employees, and partners. Our patented artificial intelligence technology across a broad area of neural networks, speech synthesis, and deep learning, drives call center automation and supports self-service experiences in HR, IT service desk, and customer service. Avaamo facilitates more than 2 billion self-service interactions annually in over 30 languages and integrates with 150 of the most common business applications used in the enterprise today. Visit www.avaamo.ai to discover how Avaamo is helping build the next-generation conversational enterprise.
