I'm surprised that any of these companies consider what they are working on to be Artificial General Intelligences. I'm probably wrong, but my impression was AGI meant the AI is self aware like a human. An LLM hardly seems like something that will lead to self-awareness.
Nah, at best we found a way to make one part of a collection of systems that will, together, do something like thinking. Thinking isn’t part of what this current approach does.
What’s most surprising about modern LLMs is that it turns out there is so much information statistically encoded in the structure of our writing that we can use only that structural information to build a fancy Plinko machine and not only will the output mimic recognizable grammar rules, but it will also sometimes seem to make actual sense, too—and the system doesn’t need to think or actually “understand” anything for us to, basically, usefully query that information that was always there in our corpus of literature, not in the plain meaning of the words, but in the structure of the writing.
This seems like the most viable path to me as well (educational background in neuroscience but don't work in the field). The brain is composed of many specialised regions which are tuned for very specific tasks.
LLMs are amazing and they go some way towards mimicking the functionality provided by Broca's and Wernicke's areas, and parts of the cerebrum, in our wetware, however a full brain they do not make.
The work on robots mentioned elsewhere in the thread is a good way to develop cerebellum like capabilities (movement/motor control), and computer vision can mimic the lateral geniculate nucleus and other parts of the visual cortex.
In nature it takes all these parts working together to create a cohesive mind, and it's likely that an artificial brain would also need to be composed of multiple agents, instead of just trying to scale LLMs indefinitely.