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Seems like Investors are cautious and not getting on the hype train blindly (cough.. crypto/blockchain cough..). I think that is a good thing. AI has real use c

Seems like Investors are cautious and not getting on the hype train blindly (cough.. crypto/blockchain cough..). I think that is a good thing. AI has real use cases but currently it is going through the hype cycle especially with every Tom Dick and Harry starting an "AI Startup" which are mostly a wrapper around ChatGPT etc. I think in next 5-7 years, AI will stabilize and most of the "get rich quick" types would have disappeared. Whatever is left then will be the AI and its future.

alex1212 3y ago
Definitely a hype cycle at the moment. I am old enough that this is my second ;)
- hattmall 3y ago
  Second hype cycle or second AI hype cycle? If the latter when was the first?
  - yxre 3y ago
    1955 with the advent of the field with some very hopeful mathematicians, but the research never produced anything. 1980 after the foundations of neural networks, but it was too computationally intensive to be useful 2009 with Watson https://www.hiig.de/en/a-brief-history-of-ai-ai-in-the-hype-cycle/ https://www.hiig.de/en/a-brief-history-of-ai-ai-in-the-hype-...
    - padolsey 3y ago
      Could this time be different? The tools are now in the hands of the "masses", not behind closed doors or in lofty ivory towers. People can run this stuff on their laptops etc
      - timy2shoes 3y ago
        Every time someone says “this time it’s different” (e.g. 1998 internet bubble, 2007 housing bubble, 2020 crypto bubble, etc) time proves that this time was not really that different.
        deleted 3y ago
        [deleted]
        civilitty 3y ago
        > (e.g. 1998 internet bubble, 2007 housing bubble, 2020 crypto bubble, etc) That's some extreme cherry picking. During that time period, the internet and smartphones alone have completely changed society (for better and worse) in the span of only three decades, despite the former going causing a minor economic crash in its infancy. Almost everything is different except human nature. The scammers are innovating just like everyone else.
        goatlover 3y ago
        When someone says a technology completely changed society, I think of the hypothetical singularity that Kurzweil and company predict, where it's basically impossible for us to predict what the future looks like after. But when you look back at the world before the rise of the web and then smartphones, it's just taking preexisting technologies and making them available in more mobile formats. TV, radio, satellite and computers existed before then (1968 mother of all demos had word processing, hypertext, networking, online video). And some people did more or less foresee what we've done online since. We still burn fossil fuels to a large extent, still drive but not fly cars, still live on Earth not in space, still die of the same causes, etc. I watch a long cargo train that looks like it's form the 80s go by and wonder how much the internet changed cargo hauling. I'm sure with the logistics the internet made things a lot more efficient, but the actual hauling is not much different. It's not like we teleport things around now. You can order online instead of out of a catalog, but brick stores remain. You can read digital books, but still plenty of printed materials, bookstores, libraries.
        JohnFen 3y ago
        > the internet and smartphones alone have completely changed society I honestly think this overstates the case pretty severely. They have certainly caused societal change, but from what I can see, society as a whole is not actually all that different from what it was before all of that.
      - sgift 3y ago
        Could yes? Will it be? I can tell you when you don't need the answer anymore, i.e. in a few years. It's the very nature of the hype cycle that it is very hard to distinguish from a real thing.
    - alex1212 3y ago
      Spot on, 2009 with Watson was my first. Oh, the memories...It was nowhere near as nuts as this one, at least in my head.
    - p1esk 3y ago
      I don’t remember much happening with NNs in 1980. There was a lot of hype in 1992-1998 though.
    - rsynnott 3y ago
      There was also a voice recognition thing in the 90s, the whole self-driving car/computer vision thing early to mid last decade, and a _very_ short-lived period when everyone was a chatbot startup in 2016 (I think Microsoft Tay just poured so much cold water over this that it died almost immediately).
  - paulddraper 3y ago
    Machine learning became quite the buzzword in 2016(?)
    - alex1212 3y ago
      I definitely remember it being the "hot thing" in the ad tech space
  - ben_w 3y ago
    I can remember hyped up news after Watson; personally I was hyped up after Creatures (though in my defence I was a teenager and hadn't really encountered non-fictional AI before); before those there was famously the AI winter, following hype that turned out to be unreasonable.
  - dspillett 3y ago
    Not the OP, but I've been through a few AI hype cycles and know of earlier ones, depending on what you count: ML more generally over the last half decade or so¹, the excitement around Watson (and Deep Blue before it), the second big bump in neural network interest in the mid/late 80s², there have been a couple of cycles regarding expert-system-like methods over the decades, etc. -- [1] though that has produced more useful output than some of the previous hype cycles, as I think will the current one as it seemingly already is doing [2] I was barely born for the start of the “AI winter” following the first such hype cycle
  - ska 3y ago
    Wikipedia has a summary of some of the earlier history here https://en.wikipedia.org/wiki/AI_winter https://en.wikipedia.org/wiki/AI_winter
- jvanderbot 3y ago
  Fourth here, if you count dot com, early robotics cum self driving cars, and web 3. Each had their impact, winners and vast array of losers.
EA-3167 3y ago
I think people are starting to realize that "AI" in the present context is just the new vehicle for people who were yelling, "NFT's and Cyrpto" just a year ago.
- xwdv 3y ago
  I can’t wait for these people to run out of “vehicles” and face the reality.
ben_w 3y ago
Even with my rose-tinted glasses on about the future of AI, it's not clear who will be the "winner" here, or even if any business making them will be a winner. If open source models are good enough (within the category of image generators it looks like many Stable Diffusion clone models are), what's the business case for Stability AI or Midjourney Inc.? Same for OpenAI and LLMs — even though for now they have the hardware edge and a useful RLHF training set from all the ChatGPT users giving thumbs up/down responses, that's not necessarily enough to make an investor happy.
- rebeccaskinner 3y ago
  Early signals to me are that regulatory capture will end up being the moat that gets used here. I think it's a horrible outcome for society, but likely one that will make some companies a lot of money. Early grumblings around regulation for a lot of AI models seem at risk of making open source models (and even open-weigh models) effectively illegal. Training from scratch is also going to both remain prohibitively expensive for individuals and most bootstrapped startups, plus with more of the common sources of data locking out companies from using training data it's going to be hard for new entrants to catch up. I personally think the only way AI will end up being a benefit to society is if we end up with unencumbered free and open models that run locally and can be refined locally. Every financial incentive is pushing in the other direction though.
  - benreesman 3y ago
    This should be one of the highest voted comments in all of the AI threads this year. Meta is no doubt doing this because it’s in their best interest, but if both the quality and licensing of LLaMA 2 start a trend that’s a pretty effective counter-weight to eyeball scanner world. And there’s other stuff. George Hotz is pretty unpopular because he does kind of put the crazy in crazy smart (which I personally find a refreshing change to the safe space for relatively neurotypical people in the land of aspy nerds), but tinygrad is a fundamentally more optimizable design than its predecessors with an explicit technical emphasis on accelerator portability and an implicit idealistic agenda around ruining the whole day of The AI Cartel. And it runs the marquee models. Serious megacorp CEOs seem to be glancing nervously in his direction, which is healthy. It’s not locked-in yet.
bushbaba 3y ago
I think it’s more to do with high rate environment, with most AI firms having no clear path to profitability. Where-as many traditional tech venture rounds (now of days) have a solid business model and current profitability per deal, using raised capital to accelerate growth at current loss for long term profit.
dehrmann 3y ago
We might be on a hype train, but ChatGPT is already much more useful than bitcoin ever was.
- codegeek 3y ago
  I agree with you there.
- LordDragonfang 3y ago
  I think that's precisely why the investors aren't as interested - bitcoin had very little value by itself, so investors got dollar signs in their eyes when a startup claimed to be able to add the value it was missing. ChatGPT already has a lot of value by itself, the value added by any startup is going to be marginal at best.
  - tsunamifury 3y ago
    I think this is a good example of the VC mindset, but I think it is also flawed on their part. LLMs are a lot more like a generalized processor than people are admitting right now. Granted you can talk to it, but it becomes significantly more capable when you learn how to program it -- and thats where the value will be added.
    - LordDragonfang 3y ago
      >when you learn how to program it I don't know if you mean, like, LoRAs and similar (actual substantive changes), but the vast majority of "learning how to program" LLMs (accounting for the majority of startup pitches as well) is "prompt engineering" - which, as the meme goes, isn't a moat. There's a skill to it, yes, but if your singular advantage boils down to a few lines of English prose, your product isn't able to control a market - and VCs are (rightly) not interested unless you have the possibility to be a near-monopoly.
      - tsunamifury 3y ago
        This is the error of the thinking. It would be like saying software doesn't have a moat because thats just clever talking to a processor. But no one would say that now, thats ridiculous. There is a sufficient degree of prompt engineering that is already defensible, I'm already doing it myself IMO. You'll see very sophisticated hybrid programming/prompting systems being developed in the next year that will prove out the case. For example 30 parallel prompts that then amalgamate into a decision and an audit, with 10 simulation level prompts running chained afterwards to clean the output. These types of atomic configurations will become sufficiently complex to not be just for 'anybody'.
mach1ne 3y ago
Depends on what you mean by ’wrapper’. For most AI startups it isn’t viable to train their own models. For most customer use-cases, ChatGPT interface isn’t enough. Wrappers are currently the only logical implementation of AI to production.
- ska 3y ago
  This is approximately true at the moment - but it's an open question how much that is worth to customers. The market will sort it out, but it's not clear that all of these "wrapper" startups have a workable business model.
  - mach1ne 3y ago
    True, especially regarding how easily their services can be replicated. Their margins are low, and customer acquisition does not provide them with network effects that would yield a moat.
strangattractor 3y ago
That is new in itself. When have VC's ever not jumped on the hype wagon? The lemmings squad has FOMO for blood.
soulofmischief 3y ago
ha ha, another "cryptocurrency has no real use cases but <new thing I am excited about> does" post on HN, my favorite meme.
- wiseowise 3y ago
  It’s true, though.
  - soulofmischief 3y ago
    The extreme irony is that the automated web will largely be used by AI to begin with, and the automated web is powered by decentralized computational efforts such as smart contracts and digital currency. It's like people completely forget/ignore that cryptocurrency is a mathematical problem still in its infancy. If you think these aren't all fundamental units of the next web, you're not thinking about it from the right perspective. If you can't pick apart the real mathematical utility and origin behind crypto efforts from a generation of scammers who hijacked a very real thing, then you just lack understanding or nuance. We are decades away from the most obvious solution but it very likely involves cryptographically-backed digital currency and smart contract systems used by automated neural networks.
    - jazzyjackson 3y ago
      that's commie thinking, that somehow if we split the work up enough we can compensate labor equitably. AI benefits from the same economies of scale as all the other means of production, and the winners are going to be the ones that can reinvest their profit into growth and outpace competitors. tl;dr I don't see distributed multi party computation doing a better job than a rack of H100s
      - soulofmischief 3y ago
        I'm speaking AI run on the edge. The kind of AI that will become pervasive. Digital personas on autopilot. The days of me having to do things like book my own flight are coming to an end.
alfalfasprout 3y ago
The reality is also that the "holy shit" moment around LLMs seems to have largely passed. Models are incrementally improving, sure, but the fundamental limitations are here to stay (at least for now). That means a long tail of adding guard rails, etc. At the end of the day, the value add is also around integration and implementation and that is very difficult to generalize.
- beebmam 3y ago
  I don't think so. Very few people I've spoken with have used GPT-4, even engineers. GPT-4 is light years ahead of GPT-3.5
  - mcny 3y ago
    The people who have used GPT-4 seem to unanimously agree that the GPT-4 today is not the same as GPT-4 as released. Open ai is clearly holding back...
    - OO000oo 3y ago
      I’ve noticed that answers have more filler and useless politeness now, but I probably don’t use it enough to notice more than that.
  - pclmulqdq 3y ago
    GPT-4 has been entirely unimpressive to me. I first used it 3 months after launch, when they had already degraded the quality significantly, and there was no "magic" moment. LAMDA (internal to Google) was actually the last time I had that sense of AI wonder, and since then, the GPTs are basically only incrementally better. Edit: fixed the number - I thought it launched in January. It turns out late March was the launch, while the first hints/discussion about it were January. I got around to it in early July.
    - Uehreka 3y ago
      > I first used it six months after launch. I’m not sure what you mean by this; GPT-4 launched 4 months ago.
elzbardico 3y ago
There is also the wrong uses of the tech. Some people think you can train a model with any amount of data you may have and that the model will be useful somehow. There’s a SaaS company in Brazil which has a solution for recruitment that is a text book case of bad usage of machine learning. Not going to mention them here, but their “resume matching by AI” is completely bonkers because of that. But, enterprise don’t care if it works, it just needs to have this bullet point so the HR director can say he implemented a selection tool powered by AI on her next presentation.
Grimburger 3y ago
> every Tom Dick and Harry starting an "AI Startup" Producthunt has basically become that these days, none of it is inspirational nor value adding, just constant "X but with AI"
bandrami 3y ago
Right now AI produces code that competent coders can massage into the real thing or copy that competent writers can massage into the real thing. I've not seen any evidence it's ever going to turn that corner, but obviously the future is unpredictable.
- lumost 3y ago
  anecdotally, it was better at generating code ~4 months ago. It makes one wonder if there is a market for "super-premium AIs" for software engineers/other technical users.
lumost 3y ago
Curiously, I observed that many investors (or at least people proposing to pitch investors) focus on the simplest of use cases. Perhaps the investor crowd is betting that they can consolidate a few of the successful stories? Or are simply looking to fund many "app" teams to complement their large VC bets in foundation models?

alex1212 3y ago

Definitely a hype cycle at the moment. I am old enough that this is my second ;)

hattmall 3y ago
Second hype cycle or second AI hype cycle? If the latter when was the first?
- yxre 3y ago
  1955 with the advent of the field with some very hopeful mathematicians, but the research never produced anything. 1980 after the foundations of neural networks, but it was too computationally intensive to be useful 2009 with Watson https://www.hiig.de/en/a-brief-history-of-ai-ai-in-the-hype-cycle/ https://www.hiig.de/en/a-brief-history-of-ai-ai-in-the-hype-...
  - padolsey 3y ago
    Could this time be different? The tools are now in the hands of the "masses", not behind closed doors or in lofty ivory towers. People can run this stuff on their laptops etc
    - timy2shoes 3y ago
      Every time someone says “this time it’s different” (e.g. 1998 internet bubble, 2007 housing bubble, 2020 crypto bubble, etc) time proves that this time was not really that different.
      - deleted 3y ago
        [deleted]
      - civilitty 3y ago
        > (e.g. 1998 internet bubble, 2007 housing bubble, 2020 crypto bubble, etc) That's some extreme cherry picking. During that time period, the internet and smartphones alone have completely changed society (for better and worse) in the span of only three decades, despite the former going causing a minor economic crash in its infancy. Almost everything is different except human nature. The scammers are innovating just like everyone else.
        goatlover 3y ago
        When someone says a technology completely changed society, I think of the hypothetical singularity that Kurzweil and company predict, where it's basically impossible for us to predict what the future looks like after. But when you look back at the world before the rise of the web and then smartphones, it's just taking preexisting technologies and making them available in more mobile formats. TV, radio, satellite and computers existed before then (1968 mother of all demos had word processing, hypertext, networking, online video). And some people did more or less foresee what we've done online since. We still burn fossil fuels to a large extent, still drive but not fly cars, still live on Earth not in space, still die of the same causes, etc. I watch a long cargo train that looks like it's form the 80s go by and wonder how much the internet changed cargo hauling. I'm sure with the logistics the internet made things a lot more efficient, but the actual hauling is not much different. It's not like we teleport things around now. You can order online instead of out of a catalog, but brick stores remain. You can read digital books, but still plenty of printed materials, bookstores, libraries.
        JohnFen 3y ago
        > the internet and smartphones alone have completely changed society I honestly think this overstates the case pretty severely. They have certainly caused societal change, but from what I can see, society as a whole is not actually all that different from what it was before all of that.
    - sgift 3y ago
      Could yes? Will it be? I can tell you when you don't need the answer anymore, i.e. in a few years. It's the very nature of the hype cycle that it is very hard to distinguish from a real thing.
  - alex1212 3y ago
    Spot on, 2009 with Watson was my first. Oh, the memories...It was nowhere near as nuts as this one, at least in my head.
  - p1esk 3y ago
    I don’t remember much happening with NNs in 1980. There was a lot of hype in 1992-1998 though.
  - rsynnott 3y ago
    There was also a voice recognition thing in the 90s, the whole self-driving car/computer vision thing early to mid last decade, and a _very_ short-lived period when everyone was a chatbot startup in 2016 (I think Microsoft Tay just poured so much cold water over this that it died almost immediately).
- paulddraper 3y ago
  Machine learning became quite the buzzword in 2016(?)
  - alex1212 3y ago
    I definitely remember it being the "hot thing" in the ad tech space
- ben_w 3y ago
  I can remember hyped up news after Watson; personally I was hyped up after Creatures (though in my defence I was a teenager and hadn't really encountered non-fictional AI before); before those there was famously the AI winter, following hype that turned out to be unreasonable.
- dspillett 3y ago
  Not the OP, but I've been through a few AI hype cycles and know of earlier ones, depending on what you count: ML more generally over the last half decade or so¹, the excitement around Watson (and Deep Blue before it), the second big bump in neural network interest in the mid/late 80s², there have been a couple of cycles regarding expert-system-like methods over the decades, etc. -- [1] though that has produced more useful output than some of the previous hype cycles, as I think will the current one as it seemingly already is doing [2] I was barely born for the start of the “AI winter” following the first such hype cycle
- ska 3y ago
  Wikipedia has a summary of some of the earlier history here https://en.wikipedia.org/wiki/AI_winter https://en.wikipedia.org/wiki/AI_winter
jvanderbot 3y ago
Fourth here, if you count dot com, early robotics cum self driving cars, and web 3. Each had their impact, winners and vast array of losers.

EA-3167 3y ago

I think people are starting to realize that "AI" in the present context is just the new vehicle for people who were yelling, "NFT's and Cyrpto" just a year ago.

xwdv 3y ago
I can’t wait for these people to run out of “vehicles” and face the reality.

ben_w 3y ago

Even with my rose-tinted glasses on about the future of AI, it's not clear who will be the "winner" here, or even if any business making them will be a winner. If open source models are good enough (within the category of image generators it looks like many Stable Diffusion clone models are), what's the business case for Stability AI or Midjourney Inc.? Same for OpenAI and LLMs — even though for now they have the hardware edge and a useful RLHF training set from all the ChatGPT users giving thumbs up/down responses, that's not necessarily enough to make an investor happy.

rebeccaskinner 3y ago
Early signals to me are that regulatory capture will end up being the moat that gets used here. I think it's a horrible outcome for society, but likely one that will make some companies a lot of money. Early grumblings around regulation for a lot of AI models seem at risk of making open source models (and even open-weigh models) effectively illegal. Training from scratch is also going to both remain prohibitively expensive for individuals and most bootstrapped startups, plus with more of the common sources of data locking out companies from using training data it's going to be hard for new entrants to catch up. I personally think the only way AI will end up being a benefit to society is if we end up with unencumbered free and open models that run locally and can be refined locally. Every financial incentive is pushing in the other direction though.
- benreesman 3y ago
  This should be one of the highest voted comments in all of the AI threads this year. Meta is no doubt doing this because it’s in their best interest, but if both the quality and licensing of LLaMA 2 start a trend that’s a pretty effective counter-weight to eyeball scanner world. And there’s other stuff. George Hotz is pretty unpopular because he does kind of put the crazy in crazy smart (which I personally find a refreshing change to the safe space for relatively neurotypical people in the land of aspy nerds), but tinygrad is a fundamentally more optimizable design than its predecessors with an explicit technical emphasis on accelerator portability and an implicit idealistic agenda around ruining the whole day of The AI Cartel. And it runs the marquee models. Serious megacorp CEOs seem to be glancing nervously in his direction, which is healthy. It’s not locked-in yet.

bushbaba 3y ago

I think it’s more to do with high rate environment, with most AI firms having no clear path to profitability. Where-as many traditional tech venture rounds (now of days) have a solid business model and current profitability per deal, using raised capital to accelerate growth at current loss for long term profit.

dehrmann 3y ago

We might be on a hype train, but ChatGPT is already much more useful than bitcoin ever was.

codegeek 3y ago
I agree with you there.
LordDragonfang 3y ago
I think that's precisely why the investors aren't as interested - bitcoin had very little value by itself, so investors got dollar signs in their eyes when a startup claimed to be able to add the value it was missing. ChatGPT already has a lot of value by itself, the value added by any startup is going to be marginal at best.
- tsunamifury 3y ago
  I think this is a good example of the VC mindset, but I think it is also flawed on their part. LLMs are a lot more like a generalized processor than people are admitting right now. Granted you can talk to it, but it becomes significantly more capable when you learn how to program it -- and thats where the value will be added.
  - LordDragonfang 3y ago
    >when you learn how to program it I don't know if you mean, like, LoRAs and similar (actual substantive changes), but the vast majority of "learning how to program" LLMs (accounting for the majority of startup pitches as well) is "prompt engineering" - which, as the meme goes, isn't a moat. There's a skill to it, yes, but if your singular advantage boils down to a few lines of English prose, your product isn't able to control a market - and VCs are (rightly) not interested unless you have the possibility to be a near-monopoly.
    - tsunamifury 3y ago
      This is the error of the thinking. It would be like saying software doesn't have a moat because thats just clever talking to a processor. But no one would say that now, thats ridiculous. There is a sufficient degree of prompt engineering that is already defensible, I'm already doing it myself IMO. You'll see very sophisticated hybrid programming/prompting systems being developed in the next year that will prove out the case. For example 30 parallel prompts that then amalgamate into a decision and an audit, with 10 simulation level prompts running chained afterwards to clean the output. These types of atomic configurations will become sufficiently complex to not be just for 'anybody'.

mach1ne 3y ago

Depends on what you mean by ’wrapper’. For most AI startups it isn’t viable to train their own models. For most customer use-cases, ChatGPT interface isn’t enough. Wrappers are currently the only logical implementation of AI to production.

ska 3y ago
This is approximately true at the moment - but it's an open question how much that is worth to customers. The market will sort it out, but it's not clear that all of these "wrapper" startups have a workable business model.
- mach1ne 3y ago
  True, especially regarding how easily their services can be replicated. Their margins are low, and customer acquisition does not provide them with network effects that would yield a moat.

strangattractor 3y ago

That is new in itself. When have VC's ever not jumped on the hype wagon? The lemmings squad has FOMO for blood.

soulofmischief 3y ago

ha ha, another "cryptocurrency has no real use cases but <new thing I am excited about> does" post on HN, my favorite meme.

wiseowise 3y ago
It’s true, though.
- soulofmischief 3y ago
  The extreme irony is that the automated web will largely be used by AI to begin with, and the automated web is powered by decentralized computational efforts such as smart contracts and digital currency. It's like people completely forget/ignore that cryptocurrency is a mathematical problem still in its infancy. If you think these aren't all fundamental units of the next web, you're not thinking about it from the right perspective. If you can't pick apart the real mathematical utility and origin behind crypto efforts from a generation of scammers who hijacked a very real thing, then you just lack understanding or nuance. We are decades away from the most obvious solution but it very likely involves cryptographically-backed digital currency and smart contract systems used by automated neural networks.
  - jazzyjackson 3y ago
    that's commie thinking, that somehow if we split the work up enough we can compensate labor equitably. AI benefits from the same economies of scale as all the other means of production, and the winners are going to be the ones that can reinvest their profit into growth and outpace competitors. tl;dr I don't see distributed multi party computation doing a better job than a rack of H100s
    - soulofmischief 3y ago
      I'm speaking AI run on the edge. The kind of AI that will become pervasive. Digital personas on autopilot. The days of me having to do things like book my own flight are coming to an end.

alfalfasprout 3y ago

The reality is also that the "holy shit" moment around LLMs seems to have largely passed. Models are incrementally improving, sure, but the fundamental limitations are here to stay (at least for now). That means a long tail of adding guard rails, etc. At the end of the day, the value add is also around integration and implementation and that is very difficult to generalize.

beebmam 3y ago
I don't think so. Very few people I've spoken with have used GPT-4, even engineers. GPT-4 is light years ahead of GPT-3.5
- mcny 3y ago
  The people who have used GPT-4 seem to unanimously agree that the GPT-4 today is not the same as GPT-4 as released. Open ai is clearly holding back...
  - OO000oo 3y ago
    I’ve noticed that answers have more filler and useless politeness now, but I probably don’t use it enough to notice more than that.
- pclmulqdq 3y ago
  GPT-4 has been entirely unimpressive to me. I first used it 3 months after launch, when they had already degraded the quality significantly, and there was no "magic" moment. LAMDA (internal to Google) was actually the last time I had that sense of AI wonder, and since then, the GPTs are basically only incrementally better. Edit: fixed the number - I thought it launched in January. It turns out late March was the launch, while the first hints/discussion about it were January. I got around to it in early July.
  - Uehreka 3y ago
    > I first used it six months after launch. I’m not sure what you mean by this; GPT-4 launched 4 months ago.

elzbardico 3y ago

There is also the wrong uses of the tech. Some people think you can train a model with any amount of data you may have and that the model will be useful somehow. There’s a SaaS company in Brazil which has a solution for recruitment that is a text book case of bad usage of machine learning. Not going to mention them here, but their “resume matching by AI” is completely bonkers because of that. But, enterprise don’t care if it works, it just needs to have this bullet point so the HR director can say he implemented a selection tool powered by AI on her next presentation.

Grimburger 3y ago

> every Tom Dick and Harry starting an "AI Startup" Producthunt has basically become that these days, none of it is inspirational nor value adding, just constant "X but with AI"

bandrami 3y ago

Right now AI produces code that competent coders can massage into the real thing or copy that competent writers can massage into the real thing. I've not seen any evidence it's ever going to turn that corner, but obviously the future is unpredictable.

lumost 3y ago
anecdotally, it was better at generating code ~4 months ago. It makes one wonder if there is a market for "super-premium AIs" for software engineers/other technical users.

lumost 3y ago

Curiously, I observed that many investors (or at least people proposing to pitch investors) focus on the simplest of use cases. Perhaps the investor crowd is betting that they can consolidate a few of the successful stories? Or are simply looking to fund many "app" teams to complement their large VC bets in foundation models?