4 ms·

Coming from someone who has never been a "true believer", I agree that the pushback is a bit harsh, but to be honest they brought it on themselves. When GPT-4 w

• mountainriver 3y ago
  Lots of people are answering that question today, LLMs are being worked into production systems at an incredible pace
  • jacquesm 3y ago
    But not without trouble. Getting consistent, reproducible and only good results is really hard, plenty of examples of companies that would love to take it into production but that seem to be stuck in a loop where as long as the AI stuff goes off the rails in non-brand safe ways they aren't going to get a green light. And I haven't seen any major change there over the last two months or so, what I have seen is that there are now better test suits and better tooling.
• skepticATX 3y ago
  The problem really kicked off with the "Sparks" paper. Microsoft Research joined the Marketing department and suddenly Eric Horvitz is co-authoring a paper that "proves" AGI is here because GPT-4 can draw a unicorn. I wish that ML folks were more concerned with doing actual science (I know some are) and less about hype. Most of pushback is only a natural reaction to this, I believe.
  • qsort 3y ago
    Disclaimer: I don't doubt that most ML folk are doing their job and are doing it well -- as a matter of fact, my company regularly does projects with our local university, so I know that, first hand. With that out of the way, I said it then and I'll say it now: a paper where Microsoft describes how well Microsoft products perform on benchmarks designed by Microsoft employees isn't science, and can't become science even if you write it in latex and put it on arxiv.
  • famouswaffles 3y ago
    The paper is fine. It doesn't "prove" anything. But it does show along with other recent insights that people who have a testable definition of general intelligence that is inclusive of humans and say 4 isn't don't have any leg to stand on. The biggest indicator that we have something here is that no one wants to argue results anymore because then the arguments fall apart. Suddenly it's "4 isn't AGI because it isn't doing "real" reasoning" instead of "4 isn't AGI because it can't do this intelligent task all humans can"
  • lewhoo 3y ago
    AGI is here because GPT-4 can draw a unicorn Seeing how random gpt performs this task nowadays I became much more skeptical towards this (https://gpt-unicorn.adamkdean.co.uk/ https://gpt-unicorn.adamkdean.co.uk/). Even if you argue the model is somehow crippled due to computation costs I'd still expect that gpt-4 could SOMETIMES draw something like a unicorn with vector shapes but perhaps not all the time. Certainly a one prompt one result conclusion seems to me really weird.
    • famouswaffles 3y ago
      >Seeing how random gpt performs this task nowadays I became much more skeptical towards this In the paper, they say RLHF GPT performs worse on the task so it's not too surprising
  • visarga 3y ago
    That paper did a number on me... I was dizzy for a day. Couldn't process the implications fast enough. It was really a dangerous paper to read, you need deep de-hyping when you finish.
• sanderjd 3y ago
  Yep, absolutely with you here. I feel like lately my mantra has become "the metric is usefulness", not just with this, but everything. So many things seem to end up in these never-ending debates that boil down to essentially just peoples' differing aesthetics. But to me, I just want to know how useful things are. I see this all over the place now, not just technical things related to my work, but stuff like culture and politics too. Of course, you could say it's still aesthetics, and my aesthetic just happens to be usefulness. And I think that's right!
  • JuanPosadas 3y ago
    > I just want to know how useful things are. LLMs are somewhere between very useful to game-changing for me. But spammers will get far more utility and value out of LLMs than I can.
    • sanderjd 3y ago
      I agree! My point is that this is where both the hypers and the dismissers have gotten it wrong for me. So many hypers are just talking about something that isn't what I'm interested in; about whether it's AGI, rather than whether it's useful. And the dismissers are just missing or denying that it is useful, and for me, it definitely is. Both of these groups just seem to be talking past each other and focusing on the wrong metrics, from my perspective.
  • xpe 3y ago
    I agree in some ways. Still, you can’t escape the uncertainty and complexity by seeking ‘usefulness’, at least to the degree that the term is undefined and contingent. Usefulness of LLMs (and whatever we combine with them) depends on research, funding, investment, attention, and applications. People who talk about usefulness or ethics or politics too often fail to specify key details, such as a time frame and/or discount rate. Not to mention risk preferences.
    • deleted 3y ago
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• hannasanarion 3y ago
  I think the fact that the hype cycle was so short is evidence in LLM's favor as a revolutionary technology. Hype-bubble technologies live off their hype forever, and need to accelerate the hype to get more investment in a technology that doesn't actually have that many applications. The hype cycles are long, escalatory, and recurrent. Think blockchain, NFTs, IoT, AR, etc. When a technology is really revolutionary, there's a big surge of interest at the hype level, and then it quickly becomes mundane as people stop talking about it because they're too busy actually using it. Think the internet, smartphones, social media, wikipedia, youtube, etc
  • qsort 3y ago
    I don't think we can get much useful signal out of these observations. By the same logic one could argue that AI is the quintessential recurring hype cycle that always turns out to be a nothing-burger. It's a particularly hard nut to crack because whether or not LLMs will turn out to be useful depends on future developments, particularly on whether there is a way to get them to behave consistently and predictably. Computers are useful because they are stupid pieces of junk that do always the same thing when given the same input. If it turns out there isn't a viable solution to this, we are forever doomed to use LLMs pseudo-interactively, which is something, but a far cry from even the low end of what LLM proponents are promising. (e.g. all the current LLM "integrations" are very thin layers on top of the raw model). It's fundamentally impossibile to tell, imho.
    • hannasanarion 3y ago
      > whether or not LLMs will turn out to be useful depends on future developments But LLMs are already useful. All kinds of people are using them to improve their writing, they now ship with grammar-check tools like Grammarly. All the big tech firms are working on integrating them into their virtual assistants. Every developer is using github copilot now. StackOverflow is in crisis because chatgpt is the perfect rubber duck. There are tons of applications in marketing, from drafting ad copy to keeping tabs on consumer buzz. If the question you're trying to interrogate is "will LLMs become AGI", then yeah, that's a big open question, but also that's a bar that's much higher than "whether or not it'll be useful" or even "whether or not it'll be game-changing", and it already is undeniably both of those things.
• simonw 3y ago
  "the sooner we can start asking the real question: how can we take this technology, limitations and all, and actually use it in a production system? Where is it useful and where is it useless?" I just published a talk I gave on Friday at WordCamp US where I tried to cover pretty much exactly this: the actual practical things you can do with existing LLM technology right now. https://simonwillison.net/2023/Aug/27/wordcamp-llms/ https://simonwillison.net/2023/Aug/27/wordcamp-llms/
• skybrian 3y ago
  Yes, promoters and dismissive skeptics react to each other in an unproductive cycle. We can try to do better. One trap to avoid is thinking of this cycle as a rough sort of justice. “They brought it on themselves” sort of hints at that? Ideally, someone else’s bad take shouldn’t be taken as an excuse for writing an opposing bad take, even though it often does provoke that sort of reaction. Noisy, polarized discussions make thing worse for everyone. Bad takes do often make for a good writing prompt. Just about everything I write is reacting to things I read online. But usually it works out better to look for an indirect, non-opposing response that doesn’t feed the polarization cycle.
  • bemusedthrow75 3y ago
    > Yes, promoters and dismissive skeptics react to each other in an unproductive cycle. We can try to do better. True. But I think I can make the case that dismissive skeptics have greater value than promoters: they can counter the worst of the promoters (e.g. the hucksters and idiots who only recently deleted their tweets promoting crypto and NFTs). Despite what people think, there is rarely a particular downside to not being first to a technology: early adopters do not routinely make truly excess profits, they just get to take advantage of a wide-eyed, uncynical marketplace. Skeptics tend to moderate over time, and are a little better at spotting the sustainable opportunities than the boosters. There is a particular downside to being an early victim of a scam or a lie in a new field. The scams are worse, more painful, more humiliating, and often happen before regulation creates meaningful penalties. The tech world is negative about skeptics for no good reason, when you consider that robust technology itself is much like harnessed skepticism. Code that doesn't trust its inputs, test harnesses, margins of error, etc. The cycle I think that is the most dangerous is the hype cycle that starts where developers don't talk sales and marketing people out of their worst claims (because it is in our short term interest not to have to get involved with all that stuff while we are working).
    • skybrian 3y ago
      By "dismissive skepticism" I was thinking of the repetitive, lazy, nearly content-free kind, like linking to "killed by Google" every time there's a topic about a Google product, spelling Microsoft as Micro$oft (back in the day), anyone talking about "techbros," or calling an LLM a glorified Markov chain. If you can post it off the top of your head and everyone can predict that someone will say it, is it worth saying? Something to be particularly wary of is reasoning by crude analogy. These people are all the same. These companies are all the same. By contrast, there are skeptics who do research, like investigative journalism and the kind of short seller that digs up dirt and publishes it. This sort of research is often valuable.