[HN Gopher] Nvidia predicts AI models 1,000,000X more powerful t...
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       Nvidia predicts AI models 1,000,000X more powerful than ChatGPT
       within 10 years
        
       Author : CharlesW
       Score  : 31 points
       Date   : 2023-02-25 18:01 UTC (5 hours ago)
        
 (HTM) web link (www.pcgamer.com)
 (TXT) w3m dump (www.pcgamer.com)
        
       | fidgewidge wrote:
       | In this case "powerful" means faster chips. It's not clear that
       | this translates into 1,000,000 smarter given that current AI
       | might end up bottlenecked on availability of text and information
       | to train it on. I guess if you could speed things up by a
       | million-fold though, you could have way bigger context windows
       | and you could potentially set a LLM talking to itself as it
       | explores a problem through web search, writing and running
       | programs, etc. Exciting times.
        
         | pixl97 wrote:
         | If I had to make a guess, I would think that text based LLMs
         | will run into that wall sooner than later. But the rapid
         | increase in compute availability wouldn't limit us to text
         | either. Also imagine the models working on image input, sound
         | data, video, temperature, touch, and whatever other inputs you
         | could encode and present to them. This brings it more in line
         | with the human experience of inputs.
        
       | weinzierl wrote:
       | Not saying it could no be true, but that's exactly what a company
       | like Nvidia would say. Do we have any reasonably unbiased info on
       | what the boundaries of the current approach are and when we will
       | reach them?
        
         | rhtgrg wrote:
         | "More powerful" here just means larger (another commenter says
         | faster chips, but you don't even need that if you spend the
         | next ten years training a model, although that could be a more
         | accurate representation of what Nvidia is trying to say, since
         | the alternative is a no-brainer). AI isn't really "smart," and
         | it seems unlikely we're going to get there anytime soon (in
         | other words, the "singularity" is still firmly out of our
         | grasp). What we're seeing today is the fruit of training models
         | with large swaths of data, and the limits of this approach are
         | predictably based on the availability of such data and the
         | resources required to convert them into these gigantic models.
         | Framed in those terms, the "limit" we should be considering
         | ought to be more about utility than how many resources we can
         | afford to throw at models that might ultimately have no use.
         | 
         | Discussions around these topics tend to get dramatized, though.
         | In my opinion we haven't made a lick of qualitative progress in
         | recent years in the "IQ" of AI, but we do get better at
         | utilizing what we have, and making quantitative progress in
         | building ever larger models.
        
           | pixl97 wrote:
           | Please lay out your definition of smart?
           | 
           | For the task they are given, take textual tokens as input and
           | make coherent output, the models seem 'smart enough' for me.
           | 
           | The problem here is all the text in the world is still one
           | dimension of information. The emergence of human
           | intelligence, at least I believe, isn't from one dimensional
           | information, but from being able to get feedback and prune
           | the bits of information that are inconsistent with reality.
           | There is no continuous feedback loop in our current LLMs to
           | prune/down weight bad information in that fashion that the
           | mind works in. There is also the "the LLM universe is what
           | humans tell it", if we feed it bad data that's incorrectly
           | weighted, then we'll get bad output. There is currently no
           | scientific method model internal for the AI to test its
           | predictions on reality.
           | 
           | I believe all the above issues are solvable, but no idea on
           | the time and resources necessary to accomplish them.
        
             | rhtgrg wrote:
             | > Please lay out your definition of smart?
             | 
             | Firstly, I agree that "smart enough" is what we should
             | focus on here, as I tried to emphasize with my focus on
             | utility.
             | 
             | Secondly, I'm assuming your intent is to ask me when I
             | would consider an AI to be "smart" in the context of my
             | comment. I think I should avoid that question, and perhaps
             | even retract my statement. There is plenty of evidence that
             | ChatGPT is smarter than _some_ humans. All of your
             | 'problems', as you might realize, are equally applicable to
             | some people.
             | 
             | Putting _that_ aside, a model would need to at least be
             | able to internalize any corrections made (by a user, and
             | not necessarily only in the context of training) and
             | reliably produce results consistent with such an
             | internalization, for me to consider it smart- _er_ (i.e.,
             | an improvement on today 's AI IQ). To be _smart_ without
             | qualification, it would need to go further, into the realm
             | of being able to hold opposing ideas while functioning
             | consistent to a given user 's expectations (this one will
             | be big, because it will act as a defense against trolls and
             | misinformation). Bonus points if it's able to improve upon
             | its own learning algorithms and ruminate on ideas
             | (unsupervised learning that is inspired by previous input
             | and not stochastic in nature) without necessitating
             | constant external dialogue.
        
               | pixl97 wrote:
               | Ya, as Bing showed us AI rampency is an issue that we've
               | not tackled even in a tiny prompt space. Going to be
               | interesting to see how we figure out how to deal with
               | that.
        
       | CharlesW wrote:
       | This is hyperbolic, of course. But it makes Kurzweil's 2045
       | prediction of the singularity not as outlandish as it first
       | seemed. https://www.smithsonianmag.com/air-space-
       | magazine/reaching-s...
        
         | oneoff786 wrote:
         | Still outlandish. Not especially well defended either.
        
       | junglistguy wrote:
       | ok
        
       | Temporary_31337 wrote:
       | Translation: nVidia is talking up the hype that can increase its
       | stock price (now that the cryptocurrency hype is over)
        
       | A_D_E_P_T wrote:
       | As Scott Alexander at ACX recently said:
       | 
       | "AGE OF MIRACLES AND WONDERS: We seem to be in the beginning of a
       | slow takeoff. We should expect things to get very strange for
       | however many years we have left before the singularity. So far
       | the takeoff really is glacially slow (everyone talking about the
       | blindingly fast pace of AI advances is anchored to different
       | alternatives than I am) which just means more time to gawk at
       | stuff. It's going to be wild."
       | 
       | Any model even just one or two orders of magnitude more powerful
       | than ChatGPT is going to make for a wild future. 10^6x is hard to
       | imagine. And the implications for the philosophy of mind are
       | staggering.
        
         | uejfiweun wrote:
         | Gradually, then suddenly.
        
         | sdwr wrote:
         | _These are the days of miracle and wonder
         | 
         | This is the long-distance call
         | 
         | The way the camera follows us in slo-mo
         | 
         | The way we look to us all_
        
         | throwuwu wrote:
         | It always seems slow until you're on the right hand side of the
         | elbow
        
       | abudabi123 wrote:
       | Could Ai learn from 3D mapping daytime soap operas and trace
       | character development along the narrative arc? Then it has to
       | function in the real world.
        
       | [deleted]
        
       | epups wrote:
       | There is not enough written text to scale a model like ChatGPT at
       | even 10x its current parameters, so improvements will have to
       | come from optimizations and/or longer training (at diminishing
       | returns).
        
         | motoxpro wrote:
         | Enough data wont really be a problem.
         | https://us.sganalytics.com/blog/2-5-quintillion-bytes-of-dat...
         | 
         | I wouldn't be surprised if we create more data in one year than
         | is in the entire internet from the start
        
           | KeplerBoy wrote:
           | quintillion bytes of social media probably have very limited
           | value.
        
             | motoxpro wrote:
             | Really? All of humanity imparting everything they think and
             | know publicly seems incredibly valuable. 100% serious.
        
               | BooneJS wrote:
               | If you're looking to make a tweet generator, sure. If
               | you're looking to harness the power of facts, no.
        
         | ThrowawayTestr wrote:
         | How do you know that? There are thousands upon thousands of
         | books that haven't been digitized.
        
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