12 ms·

AI chatbots are having their “tulip mania” moment

76 points by williamstein 4y ago

h2odragon 4y ago
The cryptocurrency boom wasnt a bubble for major media until after it popped. This headline may be the best indicator that there's actual fire under all the smoke for AI.
- fullshark 4y ago
  It's just one article by one writer about a few anecdotal examples of ChatGPT failures which highlight current limitations that anyone interested in the space should be aware of. It's useless noise and not an indicator of anything.
- roncesvalles 4y ago
  Many were saying crypto/blockchain/NFT (will refer to the cluster as "web3") was a bubble all along. Most notably, the Hacker News "hivemind" had a markedly anti-web3 lean for at least the last four years. It might've seemed like there were more positive voices for web3 because many people stood to gain monetarily from it. It was more "democratized" in that way. With AI, there is a bigger moat and it's unclear whether there's big money to be made by anyone other than those who already own the underlying tech or have tens of billions to catch up.
  - paulgb 4y ago
    > It might've seemed like there were more positive voices for web3 because many people stood to gain monetarily from it. Yeah, I think people underestimate the prevalence of this effect. At one point I tried figure out the origins of a story (covered by MSNBC) that the web3 game Axie Infinity was lifting people out of poverty in the Philippines. Every story was sourced back to the same report by a related party of the game. (Axie ended up imploding catastrophically. I haven’t seen any stories about what happened to all the Filipinos dragged along into it)
- BaseballPhysics 4y ago
  > The cryptocurrency boom wasnt a bubble for major media until after it popped. You clearly weren't paying attention to the media over the past 5-10 years.
snek_case 4y ago
I think Google just had an "oh shit" moment as it dawned onto everyone that we now (almost) have the technology to build personal assistants that actually work, and this could be the new tech that disrupts Google's business. But now that the dust is settling, people are realizing that this technology is not flawless. We haven't fully 100% mastered it, there are unsolved problems, and maybe it's not quite ready for a broad deployment just yet. That's normal. It's just the way the hype cycle works. People (and the media) quickly get really excited and build unrealistic expectations, then they become aware of the flaws and limitations. That doesn't mean these kinds of systems can't be better and even more useful in 1-2 years. There's a lot of really smart people working on them with many possible paths to address the current limitations.
- dmitriid 4y ago
  > we now (almost) have the technology to build personal assistants that actually work That parenthetical "almost" is doing an awful lot of heavy lifting.
- throwaway5752 4y ago
  Alphabet probably has more IP on ML than any group on the planet. There's the Deepmind and AlphaGo, AlphaZero, and AlphaFold but much more practically I can type a sentence into Chrome and get a page for of useful and general correct lines that provide what I want. It would be trivial for Google to summarize the results in some sort of written form instead of a list of links to other places. They could have done that a decade ago.
  - l33tman 4y ago
    The current state of the first 10 results on a google search is quite sorry. It's 5 irrelevant ads and 5 SEO-autogenerated sites (probably using GPT3 in the first place). Try it with any kind of IT-problem or IT-product review question. No amount of AI is going to summarize that load of crap into anything better. This is googles problem. The underlying abstraction of knowledge is going to change - knowledge has to be built and served while severely filtering away "noise" up to 90%. Maybe their traditional algos can do this, maybe it requires GPT+++, but it is broken as it is now and has been for more than a year.
akritrime 4y ago
Calling something tulip mania is the lazy way out. Tulip Mania was very limited in scale and didn't really affect much. Comparing each and every new trend, either legitimate or not, to tulips is nothing more than buzzword pattern matching.
- bonsaibilly 4y ago
  > Comparing each and every new trend, either legitimate or not, to tulips is nothing more than buzzword pattern matching. Must've been written by one of these "AI"s, then.
zoklet-enjoyer 4y ago
Everything is tulips
rvz 4y ago
This AI hype mania is once again a repeat of the GPT-3 hype and it amounted to using an AI SaaS as the so-called next revolution with everyone and their parrots screaming that they are also an 'AI company' which is total nonsense, just like ChatGPT would hallucinate. Again. This mania will subside just like the Clubhouse mania did.
vannevar 4y ago
Tulips were not one of the greatest scientific advances in human history. AI that can write and converse intelligently on virtually any subject is. When the chief complaint about AI is that it lies too much, that's a massive breakthrough.
- thundergolfer 4y ago
  It's a great engineering advancement, but scientific advancement implies some kind of gain in human knowledge, and that hasn't happened to a great extent. We still don't understand how these models really work, at least not in a way that teaches us anything about language or about humanity.
  - pixl97 4y ago
    >implies some kind of gain in human knowledge I find that a strange take. Almost all scientific advancement ends in one thing. Another set of unanswered questions. Quite often we gain more knowledge, but know less because we realize there are thousands more questions we should have been asking. For example, theory of mind being observed out of just processing language is a big arrow that we may have been thinking about many things wrong in the past and open new avenues for 'scientific' tests that give us answers.
    - ianmcgowan 4y ago
      It's got to have shaken up the field of cognitive research or people studying mind/consciousness. Is there a "hacker news" of theory of mind researchers? Probably some interesting conversations happening over there.
  - dd36 4y ago
    We’ve absolutely gained knowledge. We’ve learned how good these models can be. We’ve effectively made like a general teenager that can be up-trained for specific tasks. It’s super useful if you know how to use it.
  - boringg 4y ago
hcks 4y ago
> LLMs are mere text generators. Trained on unimaginable amounts of text, they string together words in coherent sentences based on statistical probability of words following other words. But they are not "intelligent" in any real way — they are just automated calculators that spit out words. These kind of takes are getting tiring fast. I’d even go as far as to qualify them as midwit takes. Yes you can reduce LLMs to their output channels, or trivialise what their doing by using words as « statistical ». Facts: ChatGPT, a rough demo based on a model that is already obsolete, is nearly indistinguishable from the average college student.
theandrewbailey 4y ago
ChatGPT and similar technologies are on the slope up to the peak of inflated expectations.[0] (Or are we on the way down already? Damn, the peak happened fast.) I eagerly await the next parts of its hype cycle, and wonder how they will go down. [0] https://en.wikipedia.org/wiki/Gartner_hype_cycle https://en.wikipedia.org/wiki/Gartner_hype_cycle
- ghaff 4y ago
  As of mid-2022, Gartner had emerging AI technologies (somewhat surprisingly to me) early in the cycle--so on the way up but near the beginning.
dragonwriter 4y ago
The quality of the article is sonewhat telegraphed by the way it messes up even the name of the (currently most publicly populat) LLM it references in the first sentence, blending the names of two different OpenAI products. Which, I suppose, even if the specific facts and arguments in it are wrong does support the headline thesis; every commentary outlet feeling so desperate to say something about it, even if it means rushing hot garbage out the door, is certainly indicative of something of a “tulip mania” moment.
MuffinFlavored 4y ago
To me, tulip mania implies "people are going crazy over it when they shouldn't (because tulips didn't really have much value in hindsight)" and I don't know if I'd agree with that. I pay $20/mo for ChatGPT. I find myself using it every day. I have long conversations with it. It's basically "Google/blogspam summarizer that you can dive into with context". I feel it allows you to go deep.
- elicash 4y ago
  I just used ChatGPT to help me code something in a day that would have taken me weeks and lots of StackOverflow previously. So I mostly agree with you. But consider that I didn't use Github Copilot only because I wasn't sure if it was free (and ChatGPT functioned well enough). This, even though I kept hitting limits in the system. It's still the case that for a lot of these use cases that people are using ChatGPT for that a chat interface is pretty inefficient for getting things done. I do think the chat UI is probably overdone right now. But that's just because there's a multi-year usability learning process that still needs to happen. It's why Microsoft is building GPT into each of their products differently and others will do the same. Chat is a short-term design trend for many use cases, just for the moment. That said, the tech is expanding so quickly that we'll likely see more chat rather than less even as other UIs have even more room to grow.
  - throwaway4aday 4y ago
    They're both superpowers but they're different. ChatGPT: 24/7 pair programming partner, universal documentation wizard and instant Stack Overflow answerer. Also good at translating from lang A to lang B. CoPilot: Autocomplete and suggestions on steroids, on the fly template and boilerplate generator and master refactorer.
    - elicash 4y ago
      I agree. But right now, it's so easy (and fun, I've done it myself) to spin up chatbots that there aren't enough folks doing the more difficult UI work for the various use cases, in my view.
ilaksh 4y ago
They couldn't even get the name right. Called it "ChatGPT-3". Saying that it doesn't understand words is ridiculous.
xchip 4y ago
The same points could be made from anything new. Prob it is a copy and paste from when gun powder was discovered.
its-summertime 4y ago
Suggesting that people shouldn't invest because of the current product and not because of the potential future product, is silly. "automated calculators", are calculators not insanely useful, especially earlier on in their history? "but how many companies will be willing to jeopardize their reputation by giving their customers incorrect information?" Yet links to companies doing exactly that. "carbon emissions" Yet datacenters all together put out 1% of total emissions globally, once again linked. - - - The article feels almost like a list of dotpoints which then get elaborated on, regardless of if they are notably relevant, la ChatGPT.
Hyption 4y ago
I already saw ml (dall e 2 and chatgpt and gpt3) as impressive. But I actually played around with chatgpt just today and holy shit. I never ever talked to a bot like I talked to chatgpt. Is it perfect? Not at all but I already was able to use it for practical things. It feels tremendously natural. This is so close to everything I'm looking for in an AI that it shows all the potential already without much fantasy. This will not go away. It will transform every aspect. I wish I would be in university right now. This thing can explain things. This thing understands context. And it's multilingual out of the box. The coherence chatgpt already shows let me believe that it does create an internal model which is more than just doing basic statistics. Alexa was great to experience because it showed me already how a voice interface feels like. But Alexa and chatgpt? Chatgpt trained on documentation! Chatgpt / ml like this will be the universal knowledge library the Rosetta stone. We are experiencing the creation of the Alexandria library. Let's see how long it will take to combine dall e/Stabel Diffusion, got, chatgpt together with other things like voice synthesis and voice recognition.
- zehaeva 4y ago
  It can explain things, but it gets a ton of things wrong, very wrong. Using this is college would be a recipe for disaster, you'd ask chatgpt to explain a thing to you and you, being a student, don't know if it's getting the explanation correct or wrong. You don't know if it's reasoning is correct. ChatGPT isn't telling you the truth or how the world is, it's just spitting out the statistically more likely next word. It's far enough on this side of the uncanny valley so you think it's a conscious human unless you know enough about the subject to realize that it's not.
- pwinnski 4y ago
  It's a text prediction engine, and clearly people are impressed. I suggest saving your statements here, like "This will not go away. It will transform every aspect. This thing understands context." and so on, and revisit them in a few years when the hype balloon has been punctured. Perhaps "will not go away" will still seem plausible, but I think the rest will age poorly.
  - 4y ago
pfdietz 4y ago
Let's ask ChatGPT about this! > Write an essay about AI chatbots having their "tulip mania" moment. > The Tulip Mania of the 17th century was a period in which tulip bulbs in the Netherlands were traded at exorbitant prices, resulting in a speculative bubble that eventually burst. The phenomenon is often used as an example of irrational economic behavior, with investors caught up in a frenzy of buying and selling without considering the actual value of the commodity they were trading. > In a similar way, it is possible that AI chatbots could experience their own "tulip mania" moment in the future. Chatbots are becoming increasingly popular in many areas of business and communication, from customer service to healthcare. They offer the promise of cost savings, improved efficiency, and 24/7 availability. However, there are concerns that the hype surrounding chatbots could lead to unrealistic expectations and irrational investment. > One potential trigger for an AI chatbot tulip mania could be a breakthrough in the technology that makes them significantly more capable. For example, if a chatbot was developed that could convincingly mimic human conversation and intelligence, it could generate a wave of excitement and investment. This could result in a rush to develop and implement chatbots in every industry, regardless of whether they are truly effective or necessary. > Another potential trigger could be a high-profile success story of a chatbot that generated a significant return on investment. If a company or organization was able to demonstrate that a chatbot had dramatically improved their customer service or reduced costs, it could create a rush to invest in similar solutions. This could lead to a flood of new chatbots being developed and implemented without sufficient testing or consideration of their actual effectiveness. > However, just as with tulip bulbs in the 17th century, the hype surrounding AI chatbots is unlikely to last forever. There are already concerns about the limitations of chatbot technology, including the difficulty of programming them to understand complex or ambiguous language, the potential for biases to be introduced, and the risk of chatbots making errors or providing inaccurate information. These limitations could become more apparent as chatbots become more widespread, leading to a burst of the hype bubble. > In conclusion, it is possible that AI chatbots could experience their own tulip mania moment in the future, driven by hype and unrealistic expectations. While chatbots offer many potential benefits, it is important for investors, businesses, and developers to approach them with a critical eye and evaluate their actual effectiveness and value. Only by doing so can we ensure that chatbots fulfill their potential as a useful tool for communication and customer service, rather than a passing fad.
kenjackson 4y ago
Of course AI doesn’t understand words. It has never interacted with the world. But that’s a weird test to use. AI systems that do facial recognition don’t actually know what faces are either. And when they classify a plate as a face we don’t get too worked up about it. We just continue to tune it or make the next big advance.
throwaway4aday 4y ago
We haven't even scratched the surface yet. "chatbot" isn't the killer app, AI in the loop is. https://twitter.com/lemonodor/status/1628270074074398720 https://twitter.com/lemonodor/status/1628270074074398720 https://twitter.com/lemonodor/status/1628420476136730624?cxt=HHwWgMDRkfPyp5ktAAAA https://twitter.com/lemonodor/status/1628420476136730624?cxt...
xg15 4y ago
> Experts regard ChatGPT-3 and Google’s LaMDA as equally unimpressive. Investors don't seem to understand this What is "ChatGPT-3" and which experts exactly regard LLMs as unimpressive? MY feeling so far is more that laymen are less impressed of them than experts - because for people not from the field, the fact that they produce so much bullshit seems to trump all other aspects. Whereas I think for people who have kept track of AI developments a bit more, the fact just how coherent the bullshit is is still extremely impressive. We've had random text generators for decades, starting with markov chains way back. Up until a few years ago, you were amazed if those things produced gramatically correct sentences - not even dreaming of producing any kind of coherent meaning. In the potentially more difficult field of understanding text, there are a million small subfields, but nothing that could parse arbitrary english text and extract actionable, semantic meaning, in the face of idioms, figures of speech, complicated coreferences, etc. Compare this to today, where you can give an LLM a written instruction in freeform and it will just execute that instruction - the answer may be glaringly incorrect, but it's exactly the kind of answer that fits your question. In the field of understanding text, this is a progress which had seemed largely impossible before.
- bonsaibilly 4y ago
  > MY feeling so far is more that laymen are less impressed of them than experts - because for people not from the field, the fact that they produce so much bullshit seems to trump all other aspects. The NYT literally just published an embarrassingly credulous account of how the Bing AI wanted to seduce the author away from his wife and commit various acts of violence, that fully took all of the interactions at face value. The non-experts are imagining full-on sentience where the experts correctly recognize mere word association shenanigans. Your feelings, in short, are ass backwards.
  - fullshark 4y ago
    That author was playing dumb for the good of his story, in particular to help it go viral. This is what news media is in 2023.
  - anonzzzies 4y ago
CuriouslyC 4y ago
This article is silly. It's taking LLMs that were trained on statistical token -> token probabilities without any concept of truth or accuracy, and implying that LLMs are hyped bullshit that is incapable of truth or accuracy. LLMs can easily be trained on (token -> .. -> token, factual_accuracy) annotated data, we just need to build a "fact check" data set for common token sequences. That data set will be expensive to build, but we could always build a fact check app that gamifies the process to help build it instead of just paying turks.
- BaseballPhysics 4y ago
  If they could do that they already would have. Frankly, I think you're massively underestimating the difficulty in what you're describing (assuming what you're describing would actually work, and I'm not sure it would). To do what you're suggesting, you'd need a human to evaluate and feed into one of these LLMs every known fact. Good luck with that. And that's ignoring the issue of maintaining that model as those facts change.
  - CuriouslyC 4y ago
    That's not true at all. Right now there's a tension in ML between hoovering up as much data as possible (since more data, even if it's bad, tends to improve the model in general even if it poisons certain parts of it) and curating/annotating data sets to improve answer quality and consistency. Data set annotation is expensive and time consuming, and it's a hard sell to shareholders to spend a billion dollars on data set annotation when there's still more data that can be cheaply obtained, and the liability or cost for producing incorrect answers is intangible or low. After Google's massive share hit from Bard's exoplanet flub though, I don't think the costs are quite as intangible as they were, and I expect accuracy will become a new push in models over the next few years.
    - deleted 4y ago
      [deleted]
    - BaseballPhysics 4y ago
victorp13 4y ago
$ Write an opinion article entitled 'AI chatbots are having their "tulip mania" moment'
turkeygizzard 4y ago
Yes, there's a lot of hype around AI right now, and yeah sure it looks like some crypto grifters rotated into AI - but overall, I really don't get how people can look at all the progress and think there isn't something important here? I see a spectrum of responses to GPT, but the really important thing is the rate of change. Even if GPT somehow doesn't impress you currently, why do you think things won't be improved in 6 months? What about 5-10 years from now? I can understand thinking that transformers are maxing out on their sigmoid curve of progress, but every time people complain about perceptrons, RNNs, CNNS, etc - another team invents something new and blows out all the benchmarks. These things won't get worse, so even if you assume a pessimistic rate of change, how different will things look soon? The observation that these AIs are "mere text generators" is a testament to how insane they are IMO. The fact that they're just predicting the next token and are still this powerful is paradigm-shifting for how I viewed human intelligence. I don't think these things are sentient, but if they can replace me at work in 10 years or less, who cares?
- BaseballPhysics 4y ago
  > Even if GPT somehow doesn't impress you currently, why do you think things won't be improved in 6 months? What about 5-10 years from now? Need I remind you of the AI winter? Progress isn't linear. You want to believe progress will continue at its current pace. I'd suggest it's every bit as reasonable to assume progress will stall out as current techniques plateau, just as they did in the past.
  - Teever 4y ago
    Everything ends, it's true. But there's no reason to believe that this technique will plateau before some noteworthy results are obtained. Other than being connected by the term 'AI' what makes you believe that the past performance of researchers is indicative of future performance? Are any of the limitations of the Apollo program inherent limitations of space exploration? How are they connected?
    - BaseballPhysics 4y ago
fwlr 4y ago
“Someone, I think Bertrand Russell, said we compare the mind to whatever is the most complex machine we know. Clocks, steam engines, telephone relays, digital computers. For AI, it’s the opposite: as capabilities increase, and our understanding of AI systems decreases, the analogies become more and more dismissive. … Machines you can use for free today pass the Turing test, these are called ‘stochastic parrots’, which is dismissive, but at least parrots are living things that engage in goal-directed activity. Every single day machines do something that if you were told of it not one year ago you would have called it witchcraft, but LLMs are ‘blurry JPEGs’. Yesterday I heard ‘Markov chain on steroids’. When the first computer wakes up we’ll call it a pile of sed scripts. …” https://borretti.me/article/and-yet-it-understands https://borretti.me/article/and-yet-it-understands
tyronehed 4y ago
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76 points by williamstein 4y ago

The cryptocurrency boom wasnt a bubble for major media until after it popped. This headline may be the best indicator that there's actual fire under all the smoke for AI.

fullshark 4y ago
It's just one article by one writer about a few anecdotal examples of ChatGPT failures which highlight current limitations that anyone interested in the space should be aware of. It's useless noise and not an indicator of anything.
roncesvalles 4y ago
Many were saying crypto/blockchain/NFT (will refer to the cluster as "web3") was a bubble all along. Most notably, the Hacker News "hivemind" had a markedly anti-web3 lean for at least the last four years. It might've seemed like there were more positive voices for web3 because many people stood to gain monetarily from it. It was more "democratized" in that way. With AI, there is a bigger moat and it's unclear whether there's big money to be made by anyone other than those who already own the underlying tech or have tens of billions to catch up.
- paulgb 4y ago
  > It might've seemed like there were more positive voices for web3 because many people stood to gain monetarily from it. Yeah, I think people underestimate the prevalence of this effect. At one point I tried figure out the origins of a story (covered by MSNBC) that the web3 game Axie Infinity was lifting people out of poverty in the Philippines. Every story was sourced back to the same report by a related party of the game. (Axie ended up imploding catastrophically. I haven’t seen any stories about what happened to all the Filipinos dragged along into it)
BaseballPhysics 4y ago
> The cryptocurrency boom wasnt a bubble for major media until after it popped. You clearly weren't paying attention to the media over the past 5-10 years.

snek_case 4y ago

I think Google just had an "oh shit" moment as it dawned onto everyone that we now (almost) have the technology to build personal assistants that actually work, and this could be the new tech that disrupts Google's business. But now that the dust is settling, people are realizing that this technology is not flawless. We haven't fully 100% mastered it, there are unsolved problems, and maybe it's not quite ready for a broad deployment just yet. That's normal. It's just the way the hype cycle works. People (and the media) quickly get really excited and build unrealistic expectations, then they become aware of the flaws and limitations. That doesn't mean these kinds of systems can't be better and even more useful in 1-2 years. There's a lot of really smart people working on them with many possible paths to address the current limitations.

dmitriid 4y ago
> we now (almost) have the technology to build personal assistants that actually work That parenthetical "almost" is doing an awful lot of heavy lifting.
throwaway5752 4y ago
Alphabet probably has more IP on ML than any group on the planet. There's the Deepmind and AlphaGo, AlphaZero, and AlphaFold but much more practically I can type a sentence into Chrome and get a page for of useful and general correct lines that provide what I want. It would be trivial for Google to summarize the results in some sort of written form instead of a list of links to other places. They could have done that a decade ago.
- l33tman 4y ago
  The current state of the first 10 results on a google search is quite sorry. It's 5 irrelevant ads and 5 SEO-autogenerated sites (probably using GPT3 in the first place). Try it with any kind of IT-problem or IT-product review question. No amount of AI is going to summarize that load of crap into anything better. This is googles problem. The underlying abstraction of knowledge is going to change - knowledge has to be built and served while severely filtering away "noise" up to 90%. Maybe their traditional algos can do this, maybe it requires GPT+++, but it is broken as it is now and has been for more than a year.

akritrime 4y ago

Calling something tulip mania is the lazy way out. Tulip Mania was very limited in scale and didn't really affect much. Comparing each and every new trend, either legitimate or not, to tulips is nothing more than buzzword pattern matching.

bonsaibilly 4y ago
> Comparing each and every new trend, either legitimate or not, to tulips is nothing more than buzzword pattern matching. Must've been written by one of these "AI"s, then.

zoklet-enjoyer 4y ago

Everything is tulips

rvz 4y ago

This AI hype mania is once again a repeat of the GPT-3 hype and it amounted to using an AI SaaS as the so-called next revolution with everyone and their parrots screaming that they are also an 'AI company' which is total nonsense, just like ChatGPT would hallucinate. Again. This mania will subside just like the Clubhouse mania did.

vannevar 4y ago

Tulips were not one of the greatest scientific advances in human history. AI that can write and converse intelligently on virtually any subject is. When the chief complaint about AI is that it lies too much, that's a massive breakthrough.

thundergolfer 4y ago
It's a great engineering advancement, but scientific advancement implies some kind of gain in human knowledge, and that hasn't happened to a great extent. We still don't understand how these models really work, at least not in a way that teaches us anything about language or about humanity.
- pixl97 4y ago
  >implies some kind of gain in human knowledge I find that a strange take. Almost all scientific advancement ends in one thing. Another set of unanswered questions. Quite often we gain more knowledge, but know less because we realize there are thousands more questions we should have been asking. For example, theory of mind being observed out of just processing language is a big arrow that we may have been thinking about many things wrong in the past and open new avenues for 'scientific' tests that give us answers.
  - ianmcgowan 4y ago
    It's got to have shaken up the field of cognitive research or people studying mind/consciousness. Is there a "hacker news" of theory of mind researchers? Probably some interesting conversations happening over there.
- dd36 4y ago
  We’ve absolutely gained knowledge. We’ve learned how good these models can be. We’ve effectively made like a general teenager that can be up-trained for specific tasks. It’s super useful if you know how to use it.
- boringg 4y ago

hcks 4y ago

> LLMs are mere text generators. Trained on unimaginable amounts of text, they string together words in coherent sentences based on statistical probability of words following other words. But they are not "intelligent" in any real way — they are just automated calculators that spit out words. These kind of takes are getting tiring fast. I’d even go as far as to qualify them as midwit takes. Yes you can reduce LLMs to their output channels, or trivialise what their doing by using words as « statistical ». Facts: ChatGPT, a rough demo based on a model that is already obsolete, is nearly indistinguishable from the average college student.

theandrewbailey 4y ago

ChatGPT and similar technologies are on the slope up to the peak of inflated expectations.[0] (Or are we on the way down already? Damn, the peak happened fast.) I eagerly await the next parts of its hype cycle, and wonder how they will go down. [0] https://en.wikipedia.org/wiki/Gartner_hype_cycle https://en.wikipedia.org/wiki/Gartner_hype_cycle

ghaff 4y ago
As of mid-2022, Gartner had emerging AI technologies (somewhat surprisingly to me) early in the cycle--so on the way up but near the beginning.

dragonwriter 4y ago

The quality of the article is sonewhat telegraphed by the way it messes up even the name of the (currently most publicly populat) LLM it references in the first sentence, blending the names of two different OpenAI products. Which, I suppose, even if the specific facts and arguments in it are wrong does support the headline thesis; every commentary outlet feeling so desperate to say something about it, even if it means rushing hot garbage out the door, is certainly indicative of something of a “tulip mania” moment.

MuffinFlavored 4y ago

To me, tulip mania implies "people are going crazy over it when they shouldn't (because tulips didn't really have much value in hindsight)" and I don't know if I'd agree with that. I pay $20/mo for ChatGPT. I find myself using it every day. I have long conversations with it. It's basically "Google/blogspam summarizer that you can dive into with context". I feel it allows you to go deep.

elicash 4y ago
I just used ChatGPT to help me code something in a day that would have taken me weeks and lots of StackOverflow previously. So I mostly agree with you. But consider that I didn't use Github Copilot only because I wasn't sure if it was free (and ChatGPT functioned well enough). This, even though I kept hitting limits in the system. It's still the case that for a lot of these use cases that people are using ChatGPT for that a chat interface is pretty inefficient for getting things done. I do think the chat UI is probably overdone right now. But that's just because there's a multi-year usability learning process that still needs to happen. It's why Microsoft is building GPT into each of their products differently and others will do the same. Chat is a short-term design trend for many use cases, just for the moment. That said, the tech is expanding so quickly that we'll likely see more chat rather than less even as other UIs have even more room to grow.
- throwaway4aday 4y ago
  They're both superpowers but they're different. ChatGPT: 24/7 pair programming partner, universal documentation wizard and instant Stack Overflow answerer. Also good at translating from lang A to lang B. CoPilot: Autocomplete and suggestions on steroids, on the fly template and boilerplate generator and master refactorer.
  - elicash 4y ago
    I agree. But right now, it's so easy (and fun, I've done it myself) to spin up chatbots that there aren't enough folks doing the more difficult UI work for the various use cases, in my view.

ilaksh 4y ago

They couldn't even get the name right. Called it "ChatGPT-3". Saying that it doesn't understand words is ridiculous.

xchip 4y ago

The same points could be made from anything new. Prob it is a copy and paste from when gun powder was discovered.

its-summertime 4y ago

Suggesting that people shouldn't invest because of the current product and not because of the potential future product, is silly. "automated calculators", are calculators not insanely useful, especially earlier on in their history? "but how many companies will be willing to jeopardize their reputation by giving their customers incorrect information?" Yet links to companies doing exactly that. "carbon emissions" Yet datacenters all together put out 1% of total emissions globally, once again linked. - - - The article feels almost like a list of dotpoints which then get elaborated on, regardless of if they are notably relevant, la ChatGPT.

Hyption 4y ago

I already saw ml (dall e 2 and chatgpt and gpt3) as impressive. But I actually played around with chatgpt just today and holy shit. I never ever talked to a bot like I talked to chatgpt. Is it perfect? Not at all but I already was able to use it for practical things. It feels tremendously natural. This is so close to everything I'm looking for in an AI that it shows all the potential already without much fantasy. This will not go away. It will transform every aspect. I wish I would be in university right now. This thing can explain things. This thing understands context. And it's multilingual out of the box. The coherence chatgpt already shows let me believe that it does create an internal model which is more than just doing basic statistics. Alexa was great to experience because it showed me already how a voice interface feels like. But Alexa and chatgpt? Chatgpt trained on documentation! Chatgpt / ml like this will be the universal knowledge library the Rosetta stone. We are experiencing the creation of the Alexandria library. Let's see how long it will take to combine dall e/Stabel Diffusion, got, chatgpt together with other things like voice synthesis and voice recognition.

zehaeva 4y ago
It can explain things, but it gets a ton of things wrong, very wrong. Using this is college would be a recipe for disaster, you'd ask chatgpt to explain a thing to you and you, being a student, don't know if it's getting the explanation correct or wrong. You don't know if it's reasoning is correct. ChatGPT isn't telling you the truth or how the world is, it's just spitting out the statistically more likely next word. It's far enough on this side of the uncanny valley so you think it's a conscious human unless you know enough about the subject to realize that it's not.
pwinnski 4y ago
It's a text prediction engine, and clearly people are impressed. I suggest saving your statements here, like "This will not go away. It will transform every aspect. This thing understands context." and so on, and revisit them in a few years when the hype balloon has been punctured. Perhaps "will not go away" will still seem plausible, but I think the rest will age poorly.
- 4y ago

pfdietz 4y ago

Let's ask ChatGPT about this! > Write an essay about AI chatbots having their "tulip mania" moment. > The Tulip Mania of the 17th century was a period in which tulip bulbs in the Netherlands were traded at exorbitant prices, resulting in a speculative bubble that eventually burst. The phenomenon is often used as an example of irrational economic behavior, with investors caught up in a frenzy of buying and selling without considering the actual value of the commodity they were trading. > In a similar way, it is possible that AI chatbots could experience their own "tulip mania" moment in the future. Chatbots are becoming increasingly popular in many areas of business and communication, from customer service to healthcare. They offer the promise of cost savings, improved efficiency, and 24/7 availability. However, there are concerns that the hype surrounding chatbots could lead to unrealistic expectations and irrational investment. > One potential trigger for an AI chatbot tulip mania could be a breakthrough in the technology that makes them significantly more capable. For example, if a chatbot was developed that could convincingly mimic human conversation and intelligence, it could generate a wave of excitement and investment. This could result in a rush to develop and implement chatbots in every industry, regardless of whether they are truly effective or necessary. > Another potential trigger could be a high-profile success story of a chatbot that generated a significant return on investment. If a company or organization was able to demonstrate that a chatbot had dramatically improved their customer service or reduced costs, it could create a rush to invest in similar solutions. This could lead to a flood of new chatbots being developed and implemented without sufficient testing or consideration of their actual effectiveness. > However, just as with tulip bulbs in the 17th century, the hype surrounding AI chatbots is unlikely to last forever. There are already concerns about the limitations of chatbot technology, including the difficulty of programming them to understand complex or ambiguous language, the potential for biases to be introduced, and the risk of chatbots making errors or providing inaccurate information. These limitations could become more apparent as chatbots become more widespread, leading to a burst of the hype bubble. > In conclusion, it is possible that AI chatbots could experience their own tulip mania moment in the future, driven by hype and unrealistic expectations. While chatbots offer many potential benefits, it is important for investors, businesses, and developers to approach them with a critical eye and evaluate their actual effectiveness and value. Only by doing so can we ensure that chatbots fulfill their potential as a useful tool for communication and customer service, rather than a passing fad.

kenjackson 4y ago

Of course AI doesn’t understand words. It has never interacted with the world. But that’s a weird test to use. AI systems that do facial recognition don’t actually know what faces are either. And when they classify a plate as a face we don’t get too worked up about it. We just continue to tune it or make the next big advance.

throwaway4aday 4y ago

We haven't even scratched the surface yet. "chatbot" isn't the killer app, AI in the loop is. https://twitter.com/lemonodor/status/1628270074074398720 https://twitter.com/lemonodor/status/1628270074074398720 https://twitter.com/lemonodor/status/1628420476136730624?cxt=HHwWgMDRkfPyp5ktAAAA https://twitter.com/lemonodor/status/1628420476136730624?cxt...

xg15 4y ago

> Experts regard ChatGPT-3 and Google’s LaMDA as equally unimpressive. Investors don't seem to understand this What is "ChatGPT-3" and which experts exactly regard LLMs as unimpressive? MY feeling so far is more that laymen are less impressed of them than experts - because for people not from the field, the fact that they produce so much bullshit seems to trump all other aspects. Whereas I think for people who have kept track of AI developments a bit more, the fact just how coherent the bullshit is is still extremely impressive. We've had random text generators for decades, starting with markov chains way back. Up until a few years ago, you were amazed if those things produced gramatically correct sentences - not even dreaming of producing any kind of coherent meaning. In the potentially more difficult field of understanding text, there are a million small subfields, but nothing that could parse arbitrary english text and extract actionable, semantic meaning, in the face of idioms, figures of speech, complicated coreferences, etc. Compare this to today, where you can give an LLM a written instruction in freeform and it will just execute that instruction - the answer may be glaringly incorrect, but it's exactly the kind of answer that fits your question. In the field of understanding text, this is a progress which had seemed largely impossible before.

bonsaibilly 4y ago
> MY feeling so far is more that laymen are less impressed of them than experts - because for people not from the field, the fact that they produce so much bullshit seems to trump all other aspects. The NYT literally just published an embarrassingly credulous account of how the Bing AI wanted to seduce the author away from his wife and commit various acts of violence, that fully took all of the interactions at face value. The non-experts are imagining full-on sentience where the experts correctly recognize mere word association shenanigans. Your feelings, in short, are ass backwards.
- fullshark 4y ago
  That author was playing dumb for the good of his story, in particular to help it go viral. This is what news media is in 2023.
- anonzzzies 4y ago

CuriouslyC 4y ago

This article is silly. It's taking LLMs that were trained on statistical token -> token probabilities without any concept of truth or accuracy, and implying that LLMs are hyped bullshit that is incapable of truth or accuracy. LLMs can easily be trained on (token -> .. -> token, factual_accuracy) annotated data, we just need to build a "fact check" data set for common token sequences. That data set will be expensive to build, but we could always build a fact check app that gamifies the process to help build it instead of just paying turks.

BaseballPhysics 4y ago
If they could do that they already would have. Frankly, I think you're massively underestimating the difficulty in what you're describing (assuming what you're describing would actually work, and I'm not sure it would). To do what you're suggesting, you'd need a human to evaluate and feed into one of these LLMs every known fact. Good luck with that. And that's ignoring the issue of maintaining that model as those facts change.
- CuriouslyC 4y ago
  That's not true at all. Right now there's a tension in ML between hoovering up as much data as possible (since more data, even if it's bad, tends to improve the model in general even if it poisons certain parts of it) and curating/annotating data sets to improve answer quality and consistency. Data set annotation is expensive and time consuming, and it's a hard sell to shareholders to spend a billion dollars on data set annotation when there's still more data that can be cheaply obtained, and the liability or cost for producing incorrect answers is intangible or low. After Google's massive share hit from Bard's exoplanet flub though, I don't think the costs are quite as intangible as they were, and I expect accuracy will become a new push in models over the next few years.
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  - BaseballPhysics 4y ago

victorp13 4y ago

$ Write an opinion article entitled 'AI chatbots are having their "tulip mania" moment'

turkeygizzard 4y ago

Yes, there's a lot of hype around AI right now, and yeah sure it looks like some crypto grifters rotated into AI - but overall, I really don't get how people can look at all the progress and think there isn't something important here? I see a spectrum of responses to GPT, but the really important thing is the rate of change. Even if GPT somehow doesn't impress you currently, why do you think things won't be improved in 6 months? What about 5-10 years from now? I can understand thinking that transformers are maxing out on their sigmoid curve of progress, but every time people complain about perceptrons, RNNs, CNNS, etc - another team invents something new and blows out all the benchmarks. These things won't get worse, so even if you assume a pessimistic rate of change, how different will things look soon? The observation that these AIs are "mere text generators" is a testament to how insane they are IMO. The fact that they're just predicting the next token and are still this powerful is paradigm-shifting for how I viewed human intelligence. I don't think these things are sentient, but if they can replace me at work in 10 years or less, who cares?

BaseballPhysics 4y ago
> Even if GPT somehow doesn't impress you currently, why do you think things won't be improved in 6 months? What about 5-10 years from now? Need I remind you of the AI winter? Progress isn't linear. You want to believe progress will continue at its current pace. I'd suggest it's every bit as reasonable to assume progress will stall out as current techniques plateau, just as they did in the past.
- Teever 4y ago
  Everything ends, it's true. But there's no reason to believe that this technique will plateau before some noteworthy results are obtained. Other than being connected by the term 'AI' what makes you believe that the past performance of researchers is indicative of future performance? Are any of the limitations of the Apollo program inherent limitations of space exploration? How are they connected?
  - BaseballPhysics 4y ago

fwlr 4y ago

“Someone, I think Bertrand Russell, said we compare the mind to whatever is the most complex machine we know. Clocks, steam engines, telephone relays, digital computers. For AI, it’s the opposite: as capabilities increase, and our understanding of AI systems decreases, the analogies become more and more dismissive. … Machines you can use for free today pass the Turing test, these are called ‘stochastic parrots’, which is dismissive, but at least parrots are living things that engage in goal-directed activity. Every single day machines do something that if you were told of it not one year ago you would have called it witchcraft, but LLMs are ‘blurry JPEGs’. Yesterday I heard ‘Markov chain on steroids’. When the first computer wakes up we’ll call it a pile of sed scripts. …” https://borretti.me/article/and-yet-it-understands https://borretti.me/article/and-yet-it-understands

tyronehed 4y ago

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