311–320 of 345 posts
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That human intelligence might just be token prediction evolving from successive small bit-width float matrix transformations is depressing to me.
> That human intelligence might just be token prediction I mean have you heard the word salad that comes out of so many people's mouths? (Including myself, admittedly)
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I am quite scared of human extinction in the face of AGI. I certainly didn't jump on it, though! I was gradually convinced by the arguments that Yudkowsky makes in "Rationality: from AI to Zombies" ( https://www.readthesequences.com/ ). Unfortunately they don't fit easily into an internet comment. Some of the points that stood out to me, though: - We are social animals, and take for granted that, all else being equal…
The human extinction due to would be "hard takeoff" of an AGI should be understood as a thought experiment, conceived in a specific age when the current connectionist paradigm wasn't yet mainstream. The AI crisis was expected to come from some kind of "hard universal algorithmic artificial intelligence", for example AIXItl undergoing a very specific process of runaway self-optimization. Current-generation systems aka…
But we are much more likely to get the Computer from Star Trek. Vastly intelligent, yet perfectly obedient. It will answer any question you ask it with the knowledge of billions of minds. Why is that more likely? Simply because creating agents is much harder than creating non-agent models, and the non-agents are more economically valuable: do you want to have an AI that always does what you tell it to, or do you want to have an AI that has its own desires? Our loss is clearly biased towards building the former kind of AI.
Why is that problematic? Imagine some malevolent group asked it “Show me how to create a weapon to annihilate humanity as efficiently as possible”. It don’t even require a singularity to be deadly.
We will probably be dead long before we can invent GLaDOS.
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I find it interesting that you have not put any kind of limit on how much can be spent to operate this AI. Or on what kinds of resources it would have access to. Could it, for instance, take its salary, and pay another human to do all or part of the job? [1] Or how about pay humans to answer questions for it? [2] [3] Helping it understand its assignments, by breaking them down into simpler explanations? Helping it im…
I said it has to manage all communications and do all the work, so no forwarding communications to third party humans. If it can convince other humans in the job to do all its work and coast that way it is fine though. > Does it have to make more than its total operational expenses, or could I spend ten or hundreds as much as its salary, to afford the compute resources to implement it? Yes, spend as much as you want…
Downforeveryoneorjust me says its just me -- tried a few different browsers, turned off ublock origin, etc.
edit: Worked when I turned off Wifi on my mobile..
It's interesting I so often see the discussion of AI in the context of what a singular model can or can't do. This seems myopic. Our own brains have specialized areas. Someone who has a stroke impacting Broca's region isn't going to have a fun time trying to do what that region was specialized for. And as a society, I don't think we'd have gotten very far if every individual was expected to perform every task. Where…
But Intelligence is one of those, and when people start calling naïvely calling "intelligence" its opposite "imprint", there is a problem. There are even the seeds of a social problem.
> orchestrating ... specialized models
Intelligence (ontology development) is one such specialized model which I have seen more faithfully and consciously attempted in classic AI as opposed to contemporary. Orchestration is crucial for the peripherals that allow the input/output. The study of "generalization" is none the less crucial, because we are to investigate the development of a system that can intrinsically, by its own nature, be exported to the largest number of relatable skills. Even with the highest specialization, up to physical, there is a matter of organicity: a hand is "specialized", yet a hook is not a hand.
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> - "AI/ML can't solve scientifically useful problems" - then AlphaFold changed the protein folding field AlphaFold is a big deal, but AI in science has been a really hot topic in the past almost decade. Also, I still wouldn’t call AlphaFold really “intelligence”, it’s doing structure prediction which is cool but it’s a long way to scientific intelligence
I wonder if you get how much we've moved the goalposts on "intelligence." Once upon a time, it was considered "intelligent" to be able to add. Then "intelligence" was tool use, which we thought only humans could do. Then we swore it took "intelligence" to play Go as well as a beginner human. What set of tasks would you, right now, consider to be demonstrative of "intelligence" if a computer can do them? Then we can l…
Nothing. Nothing that just looks like intelligence is intelligence - convincing appearances cannot make a nature. Either it is an judicial ontology refiner, or it is not intelligence.
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There's no evidence otherwise. You have to believe that the mind has a materialist basis or else you believe in woo woo magic.
There's evidence everywhere, every second of every day. It doesn't follow from the mind having a material basis that it is doing linear algebra calculations like a Python machine learning program. That's quite a leap.
It's clearly doing math and obviously no one actually believes its running python programs, you created a strawman.
Slowly but surely we're moving towards general AI. There is a marked split across general society and even ML/AI specialists between those who think that we can achieve AGI using current methods and those who dismiss the possibility. This has always been the case, but what is remarkable about today's environment is that researchers keep making progress contrary to the doubter's predictions. Each time this happens, th…
The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.
And the idea remains generally, contextually wrong, because the issue is with engineering "submarines that can swim". The idea will have credits when our submarines will be able to swim, and now they cannot.
Before you visualize a straight path between "a bag of cool ML tricks" and "general AI", try to imagine superintelligence but without consciousness. You might then realize that there is no obvious mechanism which requires the two to appear or evolve together. It's a curious concept, well illustrated in the novel Blindsight by Peter Watts. I won't spoil anything here but I'll highly recommend the book.
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I wonder if you get how much we've moved the goalposts on "intelligence." Once upon a time, it was considered "intelligent" to be able to add. Then "intelligence" was tool use, which we thought only humans could do. Then we swore it took "intelligence" to play Go as well as a beginner human. What set of tasks would you, right now, consider to be demonstrative of "intelligence" if a computer can do them? Then we can l…
> demonstrative of "intelligence" Nothing. Nothing that just looks like intelligence is intelligence - convincing appearances cannot make a nature. Either it is an judicial ontology refiner, or it is not intelligence.