Doing, Not Just Chatting, Is the Next Stage of the AI Hype Cycle
Programs that purport to solve complicated real-life problems online have captivated early adopters, despite glaring limitations.
OpenAI’s ChatGPT is simple enough to use: You type in a request and get a response that may be helpful and sounds convincingly human. Yet it has severe limitations as a practical tool. It still generally doesn’t have access to the internet (and, in fact, its training data stops sometime in 2021), isn’t designed to remember queries from conversation to conversation, isn’t all that factually reliable, and can only generate a single answer for each prompt.
Where to next? Researchers and AI enthusiasts seeking the next phase of the current chatbot hype cycle have begun to coalesce around another idea: so-called AI agents, software that connects to large language models such as the one that powers ChatGPT (and perhaps various internet services or even payment methods, too) and, after being assigned a goal by a human, comes up with a series of tasks and carries them out on its own in an effort to reach that objective.