AGI is absolutely possible with current technology - even if it's only capable of running for a single user per-server-farm.
ASI on the other hand...
https://en.m.wikipedia.org/wiki/Integrated_information_theor...
I thought this was because Go just wasn't studied nearly as much as chess due to none of the early computer pioneers being fans the way they were with Chess. The noise about "the uncountable number of possible board states" was always too reductive, the algorithm to play the game is always going to be more sophisticated than simply calculating all possible future moves after every turn.
(At least, no one I'm aware of.)
The claim is about artificial intelligence that matches or surpasses human intelligence, not how well it evolves into full-fledged humanity.
Does this mean our books and audio recordings are simply insufficient? Or is there some "soul" component that can't be recorded?
A typical argument for that is that humans process 1-3 orders of magnitude more multimodal data (in multiple streams being processed in parallel) in their first 4 years of life than the biggest LLMs we have right now do using a fraction of the energy (in a longer timeframe though), and a lot more in the next forming years. For example that accumulated "intelligence" eventually allows a teenager to learn how to drive in 18-24 hours of first-hand training. An LLM won't be able to do with that little training even if it has every other piece of human knowledge, and even if you get to train it with driving images-action pairs I wish you good luck if it is presented with an out-of-distribution situation when it is driving a car.
Humans learn to model the world, LLMs learn to model language (even when processing images or audio, it process them as a language: sequences of patches). That is very useful and valuable, and you can even model a lot of things in the world just using language, but is not the same thing.
For the last two years I've studied French every day, but only using language apps. Recently, I hired a one-on-one tutor. During lessons I find myself responding to what I think I heard with the most plausible response I can generate. Many times each session, my tutor asks me, "Do you really understand or not?" I have to stop and actually think if I do.
I don't have much multi-modal input and increasing it is challenging, but it's the best way I have to actually connect the utterances I make with reality.
Obviously not. Language is just a medium. A model of language is enough to describe how to combine words in legal sentences, not in meaningful sentences. Clearly LLMs learn much more than just the rules that allow to construct grammatically correct language, otherwise they would just babble grammatically correct nonsense such as "The exquisite corpse will drink the young wine". That knowledge was acquired via training on language, but is extra-linguistic. It's a model of the world.
PS: Plus, most reasoning/planning examples coming from LLM based systems rely in bandaids that work around said LLMs (rlhf'd CoT, LLM-Modulo, Logic-of-Thought, etc) to the point they're being differentiated by the name LRMs: Large Reasoning Models. So much for modelling the world via language just using LLMs.
In fact, if we plan to use them as a tool, then that's definitely not what we want, since it would imply many of the same flaws and limitations as humans.