231–240 of 388 posts
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In the General case* there is no functional brain without a functional body *One can nitpick yourself into creating a series of examples of fictional disabled people but let’s not bikeshed please
Can a blind person drive a car? Is a blind person not intelligent?
It seems to me that software developers are all too eager to attribute properties such as “intelligence,” to LLM’s which lead to strange, reductive conclusions that this is all humans are: token matching algorithms. There is much to intelligence that those who’ve been studying it in areas such as biology and ecology still do not understand. The role of emotions and how they work have a strong influence on our cogniti…
I don't think it is necessarily important how the human brain works. An interesting metaphor here is that aeroplanes don't work in a similar way to birds, the end goal is flight, not having wings that flap and are covered in feathers.
Researches seem fixated to create something like "a really smart person or intellectual slave", LLMs make it seem like we're close to that I guess?
Is there not a whole lot more usefulness in solving actual problems with "AI" without the potential risks and baggage of creating, I don't know, is it super capable idiot savant?
The approach deep mind was taking before entering this sort of "talking computer" arms race seemed actually quite useful and less "disruptive". Things like AlphaFold are more inline with what I was hoping to see going forwards. Now I just don't really know what the the plan is?
Is it to one day be able to sit at your computer and say things like: "I want you to solve cancer" and "replace my secretary, she's too expensive", "build as many paper clips as possible but don't hurt anyone?", and expect that it will kind of do it? Do we expect that everyone will freely have access to these systems or just a few people? Is this sustainable and practical long term?
In one interview I saw, Ilya Sutskever has claimed every town, state and country will have sort of AI representative, and in another basically stating we might not have to work and become "enlightened beings". Why on earth do we need an AGI to become "enlightened beings", has this gentlemen never read any literature on "enlightenment"?
I'm really struggling to see how the type of world some of these researchers seem to be gunning for is actually ideal or even wise even if achievable, especially given the mounting levels of anxiety around LLMs and their implications. Are the ethics ever actually considered?
It seems like "building AGI" is kind of like, building a something (loosely defined) which could have a lot of negative unintended side effects, but for what now? Just intellectual curiosity ? Fulfilling a Sci-Fi fetish?
Personally, I think this is what has spooked Geoff Hinton, he has seen an acceleration toward something, but he realizes we have zero idea what to do when or if when we build the "something". He now realizes the military or bad actors will take advantage of these AGI(?) and he might be alive to have to see the consequences of that.
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What do you mean exactly "besides math/logic"? Because logic underpins everything we think. For example it cannot identify musical chords because despite (I presume) ample training material including explanations of how exactly this works, it cannot reasonable represent this as an abstract rigorous rule, as humans do. So I ask what is C E G and it tells me C major correctly, as it presumably appears many times throug…
Sure. Let’s take quantum theory. There are lots of concepts that are based in math but can be reasoned about non-mathematically. The reason that chatGPT can write quantum computer programs to in any domain (despite the lack of existing programs!) is because it can deal with the concepts of quantum computing and the concepts in a domain (eg, predicting housing prices) and align them. Very little of human reasoning is…
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>You don't need non-linearities, an infinite series of sine functions is enough The sine function is nonlinear.
Ah so it is! I guess my point was that even this simple function is enough, you don't need any 'magic' beyond that. In particular, this continuous function can be used (infinitely) to represent discontinuous functions - the step function being the usual example. That is the more interesting and relevant mathematical fact I think.
You give sprinkle in a tiny nonlinearity (e.g. x^2 instead of x) and suddenly you can get infinite complexity by weighted composition - which is also the reason why we're so helpless with nonlinear functions and reach for linear approximations immediately (cf. gradient descent).
The other few things possible in next few years for past few years are: 1. Fusion 2. Self driving cars. 3. Ubiquitous, generally available and stable 8192 bit quantum computers. 4. High energy density grid scale batteries. Just few more "this maybe the... what could revolutionize..." articles away. What we forget is that it is in these people's business interest (executives making such statements) to state the exagge…
Grid scale energy storage is basically solved once you realize that hydrogen storage is an option already. It's in the same boat as when photovoltaics got very cheap, but skeptics continued to deny that possibility for some years afterwards.
The other few things possible in next few years for past few years are: 1. Fusion 2. Self driving cars. 3. Ubiquitous, generally available and stable 8192 bit quantum computers. 4. High energy density grid scale batteries. Just few more "this maybe the... what could revolutionize..." articles away. What we forget is that it is in these people's business interest (executives making such statements) to state the exagge…
I think we'll have full-blown AGI before fusion and before world-changing levels of quantum computing. Which is to say, we won't be around to see fusion and world-changing quantum :( But there's still time for robo-taxis!
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> ChatGPT does this very well Lol, this is precisely what chatgpt doesn't do well at all! It fails to understand simple concepts, logical inference, simple math, etc.
It’s terrible and math and logic, but ChatGPT is amazing at concepts—that’s why it is so powerful. It doesn’t work programmatically—that’s why it fails at logic. But it can reason inductively very very well. Do you have an example besides logic/math where it doesn’t understand simple concepts?
All the time. It often fails to understand simple concepts. It doesn't really seem to understand anything.
For example, try to get it to write some code for a program in a moderately obscure programming language. It's terrible: it will confidently produce stuff, but make errors all over the place.
It's unable to understand that it doesn't know the language, and it doesn't know how to ask the right questions to improve. It doesn't have a good model of what it's trying to do, or what you're trying to do. If you point out problems it'll happily try again and repeat the same errors over and over again.
What it does is intuit an answer based on the data it's already seen. It's amazingly good at identifying, matching, and combining abstractions that it's already been trained on. This is often good enough for simple tasks, because it has been trained on so much of the world's output that it can frequently map a request to learned concepts, but it's basically a glorified Markov model when it comes to genuinely new or obscure stuff.
It's a big step forward, but I think the current approach has a ceiling.
Is this like when the Google self driving car director Chris Urmson said in 2015 his 11 year old son would never need to take a drivers exam? I have a hunch when they decide who to hire for upper management, they select for whoever promises the moon. The person making the promises may not even believe it.
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I don't think it is necessarily important how the human brain works. An interesting metaphor here is that aeroplanes don't work in a similar way to birds, the end goal is flight, not having wings that flap and are covered in feathers.
You forgot to quote Max Tegmark? :) It was a good talk…