Humanity’s shiny new toy, generative AI like ChatGPT, has shown to be very powerful at interpreting users’ natural language expressions to quickly produce a wide range of text responses, from copy-editing text to summarizing a dialog. While AI responses sound quite confident, we have gradually discovered the flaws in those responses. For example, I asked ChatGPT, “Who invented IBM System U and later known as IBM Personality Insights?” It gave me the following response with names of two people, who may or may not even exist. This phenomenon is referred to as “AI hallucination.”
ChatGPT and similar AI applications have given humankind a new tool. While this new tool is powerful, it may not always be reliable. Hence the term “AI hallucinations” is coined to refer to such unreliable AI performance.
Lately, it's nearly impossible to go a day without encountering headlines about generative AI technologies and their applications like ChatGPT or AutoGPT. AI has become red hot again, and its hotness is astonishing: suddenly almost everyone wants to jump on the AI bandwagon.
In my previous blog, I talked about what it takes to build a chatbot using GPT-4, including the engineering efforts required and a rough cost and time estimate. Although it is non-trivial to build a practical chatbot solution for real-world applications, with the right tools, one can build a custom chatbot solution quickly to take full advantage of the state-of-the-art large language models (LLMs) like GPT-4.
With the popularity of ChatGPT and more recently AutoGPT, more and more organizations (or individuals) are considering the adoption of a chatbot for their website or proprietary applications (e.g., a learning program website or a mobile healthcare application). The pressing question is: should I build or buy one?
