Pretty sure I read that Goldman itself is currently creating its own internal models using its proprietary data to help its analysts, IT and investors.
Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
31–40 of 52 posts
Re: Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
#32Except for a short window around the release of GPT-4 (especially the inflated claims around beating expert trained humans at legal and math tests, as well as "replacing google"), I think people have more or less right-sized their expectations for large language models and generative AI. Clearly it can do interesting and impressive things but it's not superintelligence, and the folks predicting we're just around the…
> and the folks predicting we're just around the corner have been recognized once again as shysters, hucksters, and charlatans Why? Can you see the future? No one (serious) was claiming that GPT-4 is superintelligence, it’s about the rate of improvement. There has only been 6 years between GPT-1 and GPT-4, and each iteration brought more and more crazy emergent behaviour. We still don’t see any sign of the scaling la…
I'm pretty good at estimating the future; I started working in ML around 1993 and my last work in ML was on TPU hardware at Google (helping researchers solve deep problems when hardware goes wonky), and a number of my ideas (like AlphaFold's capabilities) were predicted by me at CASP in ~2003.
I just continue to think that Vinge was a bit optimistic both on the timeline and acceleration rate. Everybody who cares about this should read https://edoras.sdsu.edu/~vinge/misc/singularity.html and consider whether we will reach the point where ML is actively improving its own hardware (after all, we do use ML to design next gen ML hardware, but with humans in the loop).
Re: Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
#33Earlier quoted context omitted.
I don't think anyone thought it was super intelligence. I think it's impressive that we went from LLMs not being useful at all to GPT3.5 shocking the world to GPT4 becoming super useful for many things in around 7 months time. LLM progress have slowed down a bit. But I think we're just getting started. It's still really early. It's only been 1 year since GPT4 came out. Even at the level of GPT4, scaling it would have…
My text written above makes it quite clear that I don't think most people were saying GPT-4 was superintelligence, but the implication, especially from the charlatans, was there. I'm referring to the OpenAI white paper on GPT4 that shows exam results. https://cdn.openai.com/papers/gpt-4.pdf figure 4, and surrounding text. Clearly not superintelligence, as I would define it (see my other comment about scientific disco…
No one said it was super intelligence. I've never seen anyone say that about GPT4 in the media or on Hacker News/Reddit/X.
Yes, I'm sure if you google "GPT4 super intelligence", you'll find a stupid source that says it is. But I've never seen anyone reputable say it is.
Re: Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
#34Except for a short window around the release of GPT-4 (especially the inflated claims around beating expert trained humans at legal and math tests, as well as "replacing google"), I think people have more or less right-sized their expectations for large language models and generative AI. Clearly it can do interesting and impressive things but it's not superintelligence, and the folks predicting we're just around the…
>and the folks predicting we're just around the corner have been recognized once again as shysters, hucksters, and charlatans. Do you think Sutskever,Hinton or Sutter are charlatans?
I think Sutskever is a charlatan outside of his area of expertise, Hinton (with whom I worked loosely at Google) is a bit of a charlatan (again, outside his area of expertise; clearly he and LeCun both did absolutely phenomenal work) and I don't know who Sutter is.
If I wanted to predict the next ten years, I'd bring in Demis Hassabis, Noam Shazeer, and Vincent Vanhoucke, from what I've read of Demis's work, and my interactions with the latter, they seem to have very realistic understanding and are not prone to hype (Demis being the most ambitious of the three, Vincent being the one who actually cracked voice recognition, and Noam because ... his brain is unmatched).
Re: Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
#35Ironically, AI still sucks at accurately parsing PDFs.
Re: Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
#36Earlier quoted context omitted.
> and the folks predicting we're just around the corner have been recognized once again as shysters, hucksters, and charlatans Why? Can you see the future? No one (serious) was claiming that GPT-4 is superintelligence, it’s about the rate of improvement. There has only been 6 years between GPT-1 and GPT-4, and each iteration brought more and more crazy emergent behaviour. We still don’t see any sign of the scaling la…
I'm pretty good at estimating the future; I started working in ML around 1993 and my last work in ML was on TPU hardware at Google (helping researchers solve deep problems when hardware goes wonky), and a number of my ideas (like AlphaFold's capabilities) were predicted by me at CASP in ~2003. I just continue to think that Vinge was a bit optimistic both on the timeline and acceleration rate. Everybody who cares abou…
Sure, you can think a lot of people are too optimistic (and as stated in my previous post I agree with you), but calling them shysters, hucksters, and charlatans implies a hidden motive to lie for personal gains, which isn’t there (again, in the ML research side).
No one working on GPT-2 thought it would be such a leap on GPT-1, no one working on GPT-3 knew that that was the scale at which 0 shot would start emerging, no one working on GPT-4 thought it was going to be so good, so let’s just not pretend we now what GPT-5 or 6 scale model will and won’t do. We just don’t know, we all have our guesses but that’s just what it is, a guess. People making a different guess might be wrong ultimately, that doesn’t make them charlatans.
Re: Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
#37There is a paradox. To build the future requires irrational belief. And to sell that vision.
Perhaps the difference between insanity and visionary, "scam" and genius is simply the outcome.
When someone like Sam Altman declares optimistically that we will get AGI and talks about what kind of society we will need to build... It's kind of hard to tell what mix of those 4 is at work. But certainly it will be perceived differently based upon the outcome not the sincerity of the effort.
Re: Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
#38Earlier quoted context omitted.
>and the folks predicting we're just around the corner have been recognized once again as shysters, hucksters, and charlatans. Do you think Sutskever,Hinton or Sutter are charlatans?
I think Sutskever is a charlatan outside of his area of expertise, Hinton (with whom I worked loosely at Google) is a bit of a charlatan (again, outside his area of expertise; clearly he and LeCun both did absolutely phenomenal work) and I don't know who Sutter is. If I wanted to predict the next ten years, I'd bring in Demis Hassabis, Noam Shazeer, and Vincent Vanhoucke, from what I've read of Demis's work, and my i…
I think Sutskever is a charlatan outside of his area of expertise, Hinton (with whom I worked loosely at Google) is a bit of a charlatan (again, outside his area of expertise; clearly he and LeCun both did absolutely phenomenal work) and I don't know who Sutter is.
What do you think of Vizzini?
Re: Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
#39Except for a short window around the release of GPT-4 (especially the inflated claims around beating expert trained humans at legal and math tests, as well as "replacing google"), I think people have more or less right-sized their expectations for large language models and generative AI. Clearly it can do interesting and impressive things but it's not superintelligence, and the folks predicting we're just around the…
I’ve been looking at it in the same sense as something like Docker. When containers first became a big hype, everyone everywhere was using them for everything, including things like trying to containerize full desktop environments, which outside of a couple niche businesses makes almost no sense.
Similar to containers, my feeling is that the truth is LLMs are wildly overkill for almost everything going on today. You don’t need an LLM to sort some already structured data when a basic python library or something will work equally fast, predictably, and with less black box magic. There’s probably a small number of use cases that it makes sense for but for everyone else it’s just silly to try and force the technology. It doesn’t help that the people who are selling the shovels in this gold rush are extremely good at extending the hype train every few months, but eventually when these models stop being sold at a loss and businesses have to start facing down with the bill to run them and/or make these API calls, it will correct itself real fast.
Re: Goldman on Generative AI: doesn't justify costs or solve complex problems [pdf]
#40Pretty sure I read that Goldman itself is currently creating its own internal models using its proprietary data to help its analysts, IT and investors.
The likes of Goldman have been doing ML stuff (which is generally marketed as ‘AI’ as of a few years ago) for decades, but it’s generally not generative AI.