When will there be AI superintelligence?
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@evan
In the context of "AI = LLM", never. In context of "AI = whatever we will find as technology" we will need decades to have the technology to simulate at least a simple brain (much simpler than a human brain).
The reason is that the neural networks that we map in silicon today make up only a fraction of a brain. Countless elements that make up our thinking, our consciousness, and our self-awareness are missing. Even our senses, which are necessary for these, can currently only be represented in a rudimentary way.
Currently, we only emulate knowledge through high speed and parallelization. But we have clear limits in this regard with ressources.
And knowledge is not intelligence. It is also only simulated.
@beandev you should check your math on that argument!
It's not going to take decades to have hardware and software systems with complexity equivalent to the number of neurons (86 billion) or synapses (100 trillion) in a human brain. Frontier models have about 0.5 trillion parameters, roughly equivalent to synapses. That's about 2 OOM from humans.
I think it's very interesting to ask what the difference between true intelligence and simulated intelligence is, though.
@evan
Thanks to the hint about the math. I completely forgot it 😅.
It would be nice to go deeper in the science behind neuronal networks, simulations and models and what that means. If you count transistors and compare it to the number of neurons, your math is completely wrong. Additionally you need synaptic connections. All the current simulations are based on reduced and simplified models. Typically only the electrical signal way, binary switches, heavily reduced synaptic connections, and spike signal population (to reduce energy, parallelization, and computation power). We are far away.
However, a nice read about the mathematics behind it, here a nice article:
https://www.golem.de/news/maschinentraeume-1-ki-und-der-mythos-der-emergenz-2606-209312.html
It's in German, but you can translate it. Well worth reading. 👍
@evan There won't. It's all a scam.
Explain! What part is impossible?
You don't think it's possible for an entity to be more intelligent than a human?
Or is it not possible for a *constructed* entity to be more intelligent than a human?
Or are *humans* not smart enough to make a constructed entity that is more intelligent than a human?
@bignose why are you confident in that? LLMs are great at a lot of things that computers haven't done well previously.
@evan
> LLMs are great at a lot of things that computers haven't done well previously.
I hear this claim a lot, but it's never substantiated verifiably.
In fields where I understand the LLM output, it is unreliable plagiarism or unreliable garbage.
In fields where I need to rely on others more knowledgeable, those who *aren't incentivised to hype the LLM* report LLMs are unreliable plagiarism or unreliable garbage.
They're okay at language patterns. What are you saying they're great at?
@evan define superintelligence? My first Athlon many years ago could do arithmetic a billion times faster than I could. Every computer and computer program is superhuman in some specific way, or we wouldn’t keep making them
@evan that’s fair. I’m probably just too primed for people playing definitional games about AI. “AI is better than humans at this one specific task, therefore -[rhetorical sleight-of-hand], therefore all the predictions from Bostrom’s book are coming true.” But that’s not on you, that’s on me for not leaving those parts of Reddit sooner. :p
@rxp OK. I find the idea that we can't have a conversation without rigorous definitions for every term grating. We can talk about vague topics; one of the benefits of intelligence.
@evan The planet will die first.
@boz because of all the water and the energy that AI uses?
@boz@mastodon.uno @evan@cosocial.ca
Pretty sure they mean like, in general
@boz@mastodon.uno @evan@cosocial.ca
Turning it to something more concrete: do you think AGI is achievable through the same base approach as current-day LLMs?
@evan
Later... Much later.