Comment by mordymoop
Your comment prompted me to check what kinds of definitions of AGI were actually in the air back in the mid 2010s. A lot of people conflate AGI with superintelligence. I'm not accusing you of doing that, but it's a common enough mistake that I wanted to assemble these quotes as a record that can be referred to.Here are some definitions of AGI from back then, quoted verbatim where possible, with my comments added.
Gubrud (1997), first recorded use: "By advanced artificial general intelligence, I mean AI systems that rival or surpass the human brain in complexity and speed ... " Modern LLMs completely blow us out of the water on speed and this has been true for over a year now. As for "complexity", we will forgive Gubrud, but that isn't really a meaningful concept. That said, the biggest modern LLMs are probably comparable to human brains in complexity at the level of analogizing synapse counts to parameter counts. Whether this is the right lens is up for debate.
Goertzel, Journal of AGI review (2014): AGI is a field building “general-purpose systems with intelligence comparable to that of the human mind.” Any leading model satisfies this definition easily, if only because "comparable" is a loose term. If modern LLMs can substitute for any expert in a knowledge work field and even directly teleoperate robots to perform complex tasks without prior training, that already sounds more than "comparable."
MIRI / Muehlhauser (2013): “the ability to achieve complex goals in complex environments using limited computational resources ... ” Well, I don't like this definition at all, but modern LLMs do satisfy it. They may be relatively inefficient in the training phase but they're incredibly efficient in the inference phase. (By "efficient" of course I mean information-efficient, not energy-efficient; this is surely the sense in which the definition was meant.)
Wikipedia in ~2016: “Artificial general intelligence (AGI) is the intelligence of a machine that could successfully perform any intellectual task that a human being can.” This is the most demanding definition of the bunch. But still, are there really any remaining intellectual tasks that cutting edge models can't achieve? If you think that you have an example one - are you sure it isn't just an example of a thing that nobody has bothered to ask, or bothered put a lot of compute behind? The operative concept here is could successfully perform, without regard for compute requirements. This may sound weaselly, but it is extremely relevant. To my mind, the question of "is it AGI or not" is about raw capabilities, not efficiency. Nobody writing sci-fi in the 2000s would have cared too much about the compute requirements of their speculative tech. In fact, a common trope was something like a gigantic mainframe that could be asked one question at a time. The modern instantiation of a gigantic mainframe that can hold 10 million parallel conversations was barely dreamed of.