When will there be AI superintelligence?
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When will there be AI superintelligence?
@evan@cosocial.ca Unknown, but current hardware and software can only barely clear a minimal bar of cognition; forget any kind of intelligence. Conversational LLMs piggy back on human mentalisation cognitions to create the illusion of a mind, but it's even less real than the "people" that used to live in my head when I was a teenager.
We don't even have neuromorphic electronics that can remotely function like a nervous system. We can perform basic cognitions on neuromorphic hardware, but there is no reason to believe that anything like intelligence will magically emerge if you throw enough transistors at the problem.
A further problem is the gordian knot of trying to understand the brain, from its underlying physics to needing to understand the dynamical aspects of its anatomy; currently we're mostly stuck in correlating environmental or internal, conscious stimuli to metabolic activity in particular regions. Lesion studies are more problematic in terms of the accuracy of anatomical knowledge they provide.
Side thought, I think LLMs show one of the biggest weaknesses of attempting to create true AI. As soon as we have a system that can mimic the form of human speech, we are biased to inferring a mind into it through mentalisation cognition. It is going to be an important problem to be able to prove a priori that a system that produces language is doing so as a result of spontaneous self-reflection and motivated by social cognition. -
When will there be AI superintelligence?
@evan no such thing
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@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.
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@evan no such thing
@satuelisa there's no such thing as being more intelligent than humans?
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@evan
1) Which God?
2) False dichotomy.@draken whichever God! I meant, do you think there's something special about organic life that makes it possible for us to have intelligence and impossible for mechanical devices to have it?
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In other words, yes, quite possibly some form of "magic" compared to what we think today. There's so much we don't know about how the brain works, and so much has evolved in tangled complex ways over millions of years of evolution. There could be quantum effects involved in sentience for all we know. It could be much more difficult.
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@evan not in our lifetime
@hecate ha! I hope very much that my lifetime extends to the end of this poll.
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@evan You're smuggling in a premise that it will happen. When people say "na-hah" you shift the burden of proof onto them. If you think it's going to happen (including in the lifetime of some readers here) then the onus is on you to explain why you think that.
You're right! I try to get a lot out of the 4 choices Mastodon gives me.
https://evanp.me/pollfaq#never
On the topic of people who say never: nobody has to prove it to me! But I'm interested in why they say it. What part of artificial super intelligence do they think is impossible?
I think for a lot of people, they just assume that what tech billionaires say is by default a crock of shit. It's a good instinct!
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@evan@cosocial.ca Unknown, but current hardware and software can only barely clear a minimal bar of cognition; forget any kind of intelligence. Conversational LLMs piggy back on human mentalisation cognitions to create the illusion of a mind, but it's even less real than the "people" that used to live in my head when I was a teenager.
We don't even have neuromorphic electronics that can remotely function like a nervous system. We can perform basic cognitions on neuromorphic hardware, but there is no reason to believe that anything like intelligence will magically emerge if you throw enough transistors at the problem.
A further problem is the gordian knot of trying to understand the brain, from its underlying physics to needing to understand the dynamical aspects of its anatomy; currently we're mostly stuck in correlating environmental or internal, conscious stimuli to metabolic activity in particular regions. Lesion studies are more problematic in terms of the accuracy of anatomical knowledge they provide.
Side thought, I think LLMs show one of the biggest weaknesses of attempting to create true AI. As soon as we have a system that can mimic the form of human speech, we are biased to inferring a mind into it through mentalisation cognition. It is going to be an important problem to be able to prove a priori that a system that produces language is doing so as a result of spontaneous self-reflection and motivated by social cognition.@sandriver do you think intelligence can only arise in brain-like systems? Or is that just our easiest path to getting there, since we have an existence proof of it?
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You're right! I try to get a lot out of the 4 choices Mastodon gives me.
https://evanp.me/pollfaq#never
On the topic of people who say never: nobody has to prove it to me! But I'm interested in why they say it. What part of artificial super intelligence do they think is impossible?
I think for a lot of people, they just assume that what tech billionaires say is by default a crock of shit. It's a good instinct!
@evan I'm interested in why you're asking a loaded/biased question.
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@draken whichever God! I meant, do you think there's something special about organic life that makes it possible for us to have intelligence and impossible for mechanical devices to have it?
@evan
It's the fact that people are still designing both the hardware and the software, and we still don't correctly know HOW the human brain even works in the first place. -
@Mungencakes @evan
meret? Who is meret? -
@Mungencakes @evan
meret? Who is meret? -
@evan I'm interested in why you're asking a loaded/biased question.
@muddle I'm asking about super intelligence because it's been in the news lately.
https://www.cbsnews.com/news/ai-superintelligence-anthropic-jacob-coxon/
I don't think it's particularly loaded, except as you pointed out, I ask about when and not whether. I think doing both in one question is hard, so I asked the question I was interested in.
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@muddle I'm asking about super intelligence because it's been in the news lately.
https://www.cbsnews.com/news/ai-superintelligence-anthropic-jacob-coxon/
I don't think it's particularly loaded, except as you pointed out, I ask about when and not whether. I think doing both in one question is hard, so I asked the question I was interested in.
@evan That still doesn't answer my question about why.
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@muddle I'm asking about super intelligence because it's been in the news lately.
https://www.cbsnews.com/news/ai-superintelligence-anthropic-jacob-coxon/
I don't think it's particularly loaded, except as you pointed out, I ask about when and not whether. I think doing both in one question is hard, so I asked the question I was interested in.
@evan this is not just a casual interest for you. You crafted the questionnaire and your responses to it. Would I be correct in saying this?
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When will there be AI superintelligence?
Thanks everyone! I have to admit that I'm not sure. Here's my best guess.
One way to guess at whether a system can handle intelligence is to estimate the complexity of that system. The human brain has 86 billion neurons and about 100 trillion synapses, the connections between the neurons. So, we could make a claim that systems won't become intelligent until they're at least that complex. This is Ray Kurzweil's estimation method.
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Thanks everyone! I have to admit that I'm not sure. Here's my best guess.
One way to guess at whether a system can handle intelligence is to estimate the complexity of that system. The human brain has 86 billion neurons and about 100 trillion synapses, the connections between the neurons. So, we could make a claim that systems won't become intelligent until they're at least that complex. This is Ray Kurzweil's estimation method.
Currently the biggest LLMs have about 0.5 trillion parameters -- the weights between nodes in the neural network. They're simpler than synapses, but they serve about the same function.
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Currently the biggest LLMs have about 0.5 trillion parameters -- the weights between nodes in the neural network. They're simpler than synapses, but they serve about the same function.
Models are growing at about 2-3x per year. If it's possible for them to keep growing at that rate, it will be about 8-9 years before they get to 100 trillion.
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Currently the biggest LLMs have about 0.5 trillion parameters -- the weights between nodes in the neural network. They're simpler than synapses, but they serve about the same function.
@evan "they serve about the same function"
Citation? Naming them neural nodes doesn't count
