I think one of the biggest mistakes we have made as an industry is conflating the words “AI” and “LLMs.” The irony is right there on the surface. Naming is one of the hardest things to do in software, and we’ve done it poorly for the primary tool of software.
AI isn’t any one thing. It’s an extremely broad term. It simply refers to any system designed to perform a cognitive task that would normally require human intelligence. The chess opponent on an old Atari console is an AI. It’s an intelligent system - but only narrowly so. Narrow AI can have superhuman cognitive abilities, but only within the specific task it was built for, like playing chess.
A large language model like ChatGPT is also a narrow AI. It’s exceptionally good at what it was designed to do: generate natural-sounding language. It often gets things right - not because it knows anything, but because its training data contains a lot of correct information. That accuracy is an emergent byproduct of how it works, not its intended function.
What people expect from it, though, isn’t narrow intelligence - it’s general intelligence: the ability to apply cognitive ability across a wide range of domains, like a human can. That’s something LLMs simply can’t do - at least not yet. Artificial General Intelligence is the end goal for many AI companies, but AGI and LLMs are not the same thing, even though both fall under the umbrella of AI.
What is a “cognitive task”? At what point does fitting a straight line to data stop being a computer procedure and become cognitive? Is everything a computer does AI?