Something can be both technically incredibly impressive, genuinely useful and yet at the same dramatically over-hyped. That may be the case for AI today although the range of possible outcomes makes the latter point genuinely unclear.
The difference for me is that Web3 was never shown to be at all useful.
This made me chuckle abit, not that you are wrong i dont know. But it reminds me of how my parents generation understood the internet, full of scams and grifters :)
François Chollet already have a response[1] for you in his thread:
> One last thought -- don't overindex on the web3 <> LLMs comparison. Of course web3 was pure hot air while LLMs is real tech with actual applications -- that's not the parallel I'm making. The parallel is in the bubble formation social dynamics, especially in the VC crowd.
The comparison is between the level of hype not the technology itself. If you take the time to read the thread he is more than well aware of the practical aspects of AI.
I know that - I read the thread - and I respect Chollet and the fact that he knows an awful lot more about AI than I do. I personally don't think though that the comparison to Web3 is helpful even with the clarification deep in the thread.
> The difference for me is that Web3 was never shown to be at all useful.
Because nobody agrees what web3 even means, it's a totally useless term, not that dissimilar to AGI or consciousness, which nobody can properly define. People who hate crypto define web3 in terms of all the negative stuff, while people who have a vested interested in pumping token prices (like VCs) will define web3 in terms of all the potentially positive stuff.
I believe that the that fundamentals of crypto are incredibly useful and will eventually be adopted, and have been in meany places, but all the web3/NFT/etc stuff (whatever that means) is just useless hype and ponzi schemes.
Crypto has a much more negative image because it's full of scams, but that doesn't mean anything. It's just significantly easier to create scams with crypto because money is at the very base layer, than it is to create scams with AI. But that doesn't imply anything about the usefulness of these technologies.
>I believe that the that fundamentals of crypto are incredibly useful and will eventually be adopted, and have been in meany places, but all the web3/NFT/etc stuff (whatever that means) is just useless hype and ponzi schemes.
Could you elaborate? It's been 15 years since the bitcoin paper and I still don't see where the game changing commercial applications of crypto are beyond the black/grey market uses for which it has already been adopted.
ChatGPT is trivially useful in a lot of cases...The other day I asked it to write marketing copy for a project and it wrote _better_ marketing copy than I could have written in an hour. On another project, I spent 10 minutes integrating the OpenAI library and was programmatically receiving incredible results with almost no effort.
The nature of predicting the future means that there will be periods of overconfidence. In the case of Web3 (taken to mean blockchain/crypto/digital coins), the overconfidence was fueled by a core ponzi scheme combined with truly extraordinary returns for early speculators. But AI has no ponzi scheme attached to it so the comparison breaks down. My uncle cannot gamble his retirement on a mysterious promise of überwealth from a man with wild hair and no financial experience.
AI companies will have lots of false starts but 2022 was a transformational year and we are only getting started.
Read the whole thread. Francis is the creator of Keras and an AI engineer at Google. He knows his stuff.
He calls out ads/marketing/copywriting as one area where ChatGPT is effective. His point is that the scope of things beyond that use case is probably a lot more limited than people are assuming.
I would say code generation and documenting is another one. The UX for this is a bit sucky but I've been pretty blown away with chat gpt's ability to generate, translate, and explain existing code.
I actually started trying to learn rust using chat gpt. I can just ask it to explain bits I don't understand ... and it does.
There's a lot of content generation in the legal and medical sphere that is probably also pretty much something where chat gpt could be helpful. Dangerous of course when it gets it wrong. But still, I could see this being a useful tool for researchers in all sorts of fields to quickly dig through a lot of information. Basically, chat gpt is trained on more stuff than a single human will be able to read.
I think this whole space is maybe bottlenecked on imagination. We have a lot of AI experts with not a whole lot of other expertise not seeing the forest for the trees. OpenAI employs a few geniuses but their product is basically a chat box and an API.
As I was remarking to a friend the other day: so they have chat gpt, pretty decent speech to text, and amazing text to speech .... so why can't I talk to chat gpt and listen to the answer? Such an obvious thing to do. Surely somebody thought of that. I mean inside OpenAI. I know there's a multitude of openai powered proofs of concept by third parties. But they don't seem to have the ambition to support a finished product so far.
> Read the whole thread. Francis is the creator of Keras and an AI engineer at Google. He knows his stuff.
I read the thread, it actually starts with him saying:
"If this had been a blog post and not a random spur-of-the-moment train of thoughts, I wouldn't have made the AI/web3 comparison. It was counterproductive, as it is what most folks are now focusing on. The two are, in fact, very much not the same."
So you can have the "appeal to authority" but the authority now says that was bad and should not have done it. :-)
He continues:
"I meant to compare the surrounding hype generation dynamics (as discussed towards the end of the thread). Expectations unmoored from reality becoming a universally accepted, self-evident canon once the same narratives have been repeated enough times in the echo chamber."
I'm guessing your salary depends on you thinking that AI-generated marketing copy is a Good Thing™.
To me, it just sounds like more dystopian attention spam. If absolutely all marketing copy vanished overnight never to return, in my opinion the world would be a better place.
I'm hoping we haven't hit the "uncanny valley" of ML generated text yet, and we will get to a point where something very deep in our brain is able to pick up that ML generated text isn't something coming from a genuine person (much like how lots of people intuitively understand that marketing copy is valueless) and viscerally react to it in a negative way.
It would be the only possible defense against this dystopian crap.
So far, when asked what's the use case for ChatGPT/LLMs, the sole answer with clear PMF is marketing copy. Agree it is very good for that. Just as crypto had very clear PMF for cross-border payments and stablecoins in middle income countries without dollarized banking. The problem is neither of these use cases is sufficient to justify peak valuations. (OpenAI is currently raising at $30bn.)
Like crypto, there are other potential use cases on the horizon for LLMs. The problem is the tech is still far too clunky, unreliable and impractical for the foreseeable future. LLMs are subject to a devastating hallucination problem, where they confidently report clearly erroneous data. And there is no solution in sight. Marketing copy is one of the sole major use cases, where random inaccuracies is mostly not catastrophic. But you're never going to trust LLMs to write code or legal contracts or technical documentation or even your own emails until the hallucination issue is drastically improved.
That leaves us with a few other niches that are, frankly not very monetizable. ChatGPT is very good at writing student essays, but students don't have very much money to spend. Makes a fun chatbot, but people are unlikely to pay much of anything to have a chat companion.
Like crypto, AI is a case of really intellectually interesting technology that nerdsniped a lot of smart people. Like crypto, AI has a few small (in terms of market size) use cases where there's clear PMF. Like crypto, there are potentially a lot of other much larger use cases that the nerdsniped smart people are imagining. Like crypto, these large use cases are going to require a lot of fundamental improvements to the tech itself before they become feasible. Like crypto in 2021, AI valuations in 2023 are treating those large scale use cases as imminent rather than long-term speculative.
(Note this isn't a statement about which tech has a brighter long-term future. It's still more than possible to believe (as many on HN do) that AI will be transformative over the next couple decades and crypto is vapor. But the point is AI valuations are implying that it's going to be transformative over years not decades, and it's pretty clear that's not the case. There are parallels with crypto in 2021, where regardless of the long-term promise, the short-term returns simply cannot support the valuations.)
From the thread, the author states that spam/"marketing content creation" is the only viable area of application.
> This is consistent with the primary learning from the 2020-2021 class of GPT-3 startups (a category of startups willed into existence by VCs and powered by hype), which is that commercial use cases have been falling almost entirely into the marketing and copywriting niches.
Having lived through hype wave after hype wave after hype wave in tech over the last forty-fifty years, the commentary about the behaviour of VCs resonated. I wonder if part of why VCs back so many copycat companies in hype cycles is a structural incentive to just invest money in things that are getting press, raising the VCs profile and attracting more deal flow and limited partners.
This led to idle speculation: If it was possible to short early-stage startups that VCs were backing, there would be as much incentive for the media to discuss a startup’s shortcomings and vapourware promises as there is to repeat their breathless braggadocio.
I think there is some truth to the statement, although many VCs that I've met are really sharp and thoughtful. Not at all the caricature of greasy tech illiterates that sometimes gets thrown around. You kind of can't generate good returns if you aren't able to think about the long-term trajectories of industries.
But I think that with the bubble times of 2018-2021 a lot of people entered the industry or changed their behavior because it was trendy and cool, and they have been way more down to ride the hype cycle rodeo.
I have also met many intelligent and thoughtful investors. I am speaking only to the systemic effects of a kind of marketplace for information that overvalues hype, and undervalues criticism.
My speculative musing is that if people could take short positions in startups and not just coattail on as one of a group of investors, I wonder if we’d get a lot fewer breathless PR puff-pieces and a lot more cases for pessimism around certain types of hype cycle investments, backed by investors betting their own moeny against the hype.
Web3/NFT/Crypto promises: Very clever and advanced tech, People will stop using the old stuff because they hate the government and want to save pennies.
Web3/NFT/Crypto realities: using it is expensive and hard, scams left and right and the government actually arrives but doesn't remedy the damages. People are not in to save pennies on transactions but to get rich quick.
DALL-E/ChatGPT promises: A statistical model that can generate text and images that are impressive but not always accurate. Also, the tech is not that magical, we just used so much data to train it.
DALL-E/ChatGPT reality: Wows everyone, people actually use it tirelessly for writing code, creating artwork, recreationally etc.
We will probably hit the limits soon and won't have GAI next year but the stuff already delivered is already useful. The crypto stuff might become useful but its nowhere near the hype.
> DALL-E/ChatGPT promises: A statistical model that can generate text and images that are impressive but not always accurate. Also, the tech is not that magical, we just used so much data to train it.
> DALL-E/ChatGPT reality: Wows everyone, people actually use it tirelessly for writing code, creating artwork, recreationally etc.
That's a pretty generous if not biased take, is it not? For me personally, ChatGPT is underwhelming and hasn't done anything remotely impressive when I have used it. And there's a lot of fervor around people using it, but are there interesting use cases outside of advertising? And are there not a ton of harmful use cases? The internet is going to be absolutely filled to the brim with GPT generated junk.
OpenAI's actual promises are "to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity."
A chatbot that's relatively accurate at interpreting and summarising stuff compared with previous generation chatbots and an image generation algorithm that's actually pretty good are a damned sight more useful than NFTs which is why I agree with others that the comparison isn't helpful, but I don't think it's realistic to characterise OpenAI and AI enthusiasts in general as under-promising
I agree, but it can be "wow that's good" without "wow that's going to replace very single creative job in the world by 2024" which a lot of people seem to expect
It's a bit like thinking autonomous parallel parking will automatically bring you fully autonomous cars soon
I don’t think it’s that people expect it. It’s that some people absolutely despise the idea of artists and have some irrational desire to erase their jobs and automate it all.
These people usually aren’t people signing checks—just angry people online, and oftentimes tied in with political motivations. I don’t think many companies are licking their lips at the idea of firing artists (yet). They’re probably thinking about how they can use this to assist artists to get more done faster and at higher quality.
The main driver is technological advancement and the generated value is _obviously_ net positive.
Not saying that there aren't issues that need to be discussed, nor am I saying that there isn't any (unnecessary) hype. But the comparison to Web3 is a stretch.
The author addresses this:
> One last thought -- don't overindex on the web3 <> LLMs comparison. Of course web3 was pure hot air while LLMs is real tech with actual applications -- that's not the parallel I'm making. The parallel is in the bubble formation social dynamics, especially in the VC crowd.
Every day I see one or two new thought pieces on how AI is not actually good/capable/impressive or how AI is overhyped. I have seen zero thought pieces on how AI is amazing and hyped. Meanwhile a lot of people are having fun with, or doing useful things with, StableDiffusion and ChatGPT.
The negative takes are mostly correct in all the limitations they talk about, but what they miss is how amazing these things are despite these limitations. These things are remarkably simple and limited yet they can generate realistic photos of myself in places I've never been, wearing clothes I've never worn, doing things I've never done, with a quick text sentence. Or nearly pass the bar exam.
On top of that a lot of the limitations have straightforward ways to address, many of which are already in progress. It is going to get really interesting. StableDiffusion knows nothing about the images it is produces, its just repeated denoising with image targets. It doesn't really understand anything about your text either, its just matching up tags. But both of those things can easily change. Put a big language model in front of it to better understand text. Already variants of these image models have depth information. Next up 3d object information, maybe next models of physics so it can understand how things would actually work in the scene, and so on.
> but what they miss is how amazing these things are despite these limitations
The author of this Twitter thread is François Chollet, Senior Staff Software Engineer at Google, creator of Keras and major contributor to TensorFlow, and author of Deep Learning in Python, considered by many a seminal book in introductory DL...
I'd say he understands how amazing these things are despite the limitations, and he specifically says in the thread that it's an amazing time to be building DL apps.
>The author of this Twitter thread is François Chollet, Senior Staff Software Engineer at Google, creator of Keras and major contributor to TensorFlow, and author of Deep Learning by Python, considered by many a seminal book in introductory DL...
That sounds like someone who's great at API design, not a deep learning researcher.
Don’t think anybody doubts that the current achievements are intellectually impressive. The issue for VCs is how valuable are they from a business perspective. Creating photos of people in places they’ve never been is really cool, but realistically how much money will people actually pay for that?
For AI to be as valuable as current rounds are implying it has to actually be capable of replacing your lawyer, your accountant, your software engineer. ChatGPT is nowhere near accurate enough to do that. It’s the same issue we ran into with super cruise control versus fully autonomous driving. Or speech recognition. Early progress was fast. Last mile in AI is always brutal.
Maybe there’s some argument to say ChatGPT won’t replace your lawyer or software engineer but will make them 20% more efficient. Possible. Though I’m still skeptical. ChatGPT’s unparalleled ability to create really convincing sounding errors is a big hidden negative productivity drag.
Generative AI is good for SEO copy because it’s an AI talking to an AI. Google looks at text generated by ChatGPT and is like “wow, that’s exactly how I think about things.” They were trained on much of the same content: the web.
The biggest challenge for generative AI is its willingness to make things up. It’s fine when you’re playing around. Not so fine when you’re expecting it to actually help you in a real way.
I suspect this is why Google has not debuted such an interface despite literally decades of work on AI. You have to be able to bolt a “truth filter” onto the AI, which seems difficult.
As far as consumer interest goes, the problem with Web3 is it sells the means rather than the end. Nobody cares if your Twitter/Substack/Spotify Web3 alternative is decentralised or you own your own data on the platform. To win it has to be immediately useful and/or better than alternatives.
Content generation AI is so obviously useful to the majority of people and it does not require an understanding of how it works in order to be impressed by it.
Impressive for sure. Usefulness is still being explored (outside of a few early things like Copilot).
The majority of people are still interacting with this stuff primarily as a toy, and while it's a much, much smaller leap to imagine how you'd use it in everyday life vs. something like web3, most people aren't yet, and I don't think it's an absolute certainty that they will (or at the very least, how universally they will).
"We tend to overestimate the effect of technology in the short term and underestimate it in the long term."
The comparison with web3 is very excessive though. This AI stuff is at least somewhat actually useful. Web3 was a gigantic billion dollar bubble that produced very little in the way of things that are useful for any purpose, even playing around. It's one of the most vapid bubbles in history outside pure financial instrument bubbles.
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The difference for me is that Web3 was never shown to be at all useful.
> One last thought -- don't overindex on the web3 <> LLMs comparison. Of course web3 was pure hot air while LLMs is real tech with actual applications -- that's not the parallel I'm making. The parallel is in the bubble formation social dynamics, especially in the VC crowd.
[1]: https://nitter.lacontrevoie.fr/fchollet/status/1612178630494...
But actually it’s just social bubbles especially in VCs.
It’s not a response or a clarification it’s a change to the meaning of his headline.
Because nobody agrees what web3 even means, it's a totally useless term, not that dissimilar to AGI or consciousness, which nobody can properly define. People who hate crypto define web3 in terms of all the negative stuff, while people who have a vested interested in pumping token prices (like VCs) will define web3 in terms of all the potentially positive stuff.
I believe that the that fundamentals of crypto are incredibly useful and will eventually be adopted, and have been in meany places, but all the web3/NFT/etc stuff (whatever that means) is just useless hype and ponzi schemes.
Crypto has a much more negative image because it's full of scams, but that doesn't mean anything. It's just significantly easier to create scams with crypto because money is at the very base layer, than it is to create scams with AI. But that doesn't imply anything about the usefulness of these technologies.
Could you elaborate? It's been 15 years since the bitcoin paper and I still don't see where the game changing commercial applications of crypto are beyond the black/grey market uses for which it has already been adopted.
What is a web3 website/product that can be called a hit?
ChatGPT is trivially useful in a lot of cases...The other day I asked it to write marketing copy for a project and it wrote _better_ marketing copy than I could have written in an hour. On another project, I spent 10 minutes integrating the OpenAI library and was programmatically receiving incredible results with almost no effort.
The nature of predicting the future means that there will be periods of overconfidence. In the case of Web3 (taken to mean blockchain/crypto/digital coins), the overconfidence was fueled by a core ponzi scheme combined with truly extraordinary returns for early speculators. But AI has no ponzi scheme attached to it so the comparison breaks down. My uncle cannot gamble his retirement on a mysterious promise of überwealth from a man with wild hair and no financial experience.
AI companies will have lots of false starts but 2022 was a transformational year and we are only getting started.
He calls out ads/marketing/copywriting as one area where ChatGPT is effective. His point is that the scope of things beyond that use case is probably a lot more limited than people are assuming.
Web3 was a circle jerk within the crypto community. It only convinced fools.
Recent GPT/stable diffusion products universally blow people away with their output.
Engineers and everyone else regularly dismiss new tech for its shortcomings and completely miss the forest for the trees.
I actually started trying to learn rust using chat gpt. I can just ask it to explain bits I don't understand ... and it does.
There's a lot of content generation in the legal and medical sphere that is probably also pretty much something where chat gpt could be helpful. Dangerous of course when it gets it wrong. But still, I could see this being a useful tool for researchers in all sorts of fields to quickly dig through a lot of information. Basically, chat gpt is trained on more stuff than a single human will be able to read.
I think this whole space is maybe bottlenecked on imagination. We have a lot of AI experts with not a whole lot of other expertise not seeing the forest for the trees. OpenAI employs a few geniuses but their product is basically a chat box and an API.
As I was remarking to a friend the other day: so they have chat gpt, pretty decent speech to text, and amazing text to speech .... so why can't I talk to chat gpt and listen to the answer? Such an obvious thing to do. Surely somebody thought of that. I mean inside OpenAI. I know there's a multitude of openai powered proofs of concept by third parties. But they don't seem to have the ambition to support a finished product so far.
I read the thread, it actually starts with him saying:
"If this had been a blog post and not a random spur-of-the-moment train of thoughts, I wouldn't have made the AI/web3 comparison. It was counterproductive, as it is what most folks are now focusing on. The two are, in fact, very much not the same."
So you can have the "appeal to authority" but the authority now says that was bad and should not have done it. :-)
He continues:
"I meant to compare the surrounding hype generation dynamics (as discussed towards the end of the thread). Expectations unmoored from reality becoming a universally accepted, self-evident canon once the same narratives have been repeated enough times in the echo chamber."
Deleted Comment
He also said pytorch was just a hype. It looks like he just doesn't like things he didn't do himself.
To me, it just sounds like more dystopian attention spam. If absolutely all marketing copy vanished overnight never to return, in my opinion the world would be a better place.
It would be the only possible defense against this dystopian crap.
Like crypto, there are other potential use cases on the horizon for LLMs. The problem is the tech is still far too clunky, unreliable and impractical for the foreseeable future. LLMs are subject to a devastating hallucination problem, where they confidently report clearly erroneous data. And there is no solution in sight. Marketing copy is one of the sole major use cases, where random inaccuracies is mostly not catastrophic. But you're never going to trust LLMs to write code or legal contracts or technical documentation or even your own emails until the hallucination issue is drastically improved.
That leaves us with a few other niches that are, frankly not very monetizable. ChatGPT is very good at writing student essays, but students don't have very much money to spend. Makes a fun chatbot, but people are unlikely to pay much of anything to have a chat companion.
Like crypto, AI is a case of really intellectually interesting technology that nerdsniped a lot of smart people. Like crypto, AI has a few small (in terms of market size) use cases where there's clear PMF. Like crypto, there are potentially a lot of other much larger use cases that the nerdsniped smart people are imagining. Like crypto, these large use cases are going to require a lot of fundamental improvements to the tech itself before they become feasible. Like crypto in 2021, AI valuations in 2023 are treating those large scale use cases as imminent rather than long-term speculative.
(Note this isn't a statement about which tech has a brighter long-term future. It's still more than possible to believe (as many on HN do) that AI will be transformative over the next couple decades and crypto is vapor. But the point is AI valuations are implying that it's going to be transformative over years not decades, and it's pretty clear that's not the case. There are parallels with crypto in 2021, where regardless of the long-term promise, the short-term returns simply cannot support the valuations.)
> This is consistent with the primary learning from the 2020-2021 class of GPT-3 startups (a category of startups willed into existence by VCs and powered by hype), which is that commercial use cases have been falling almost entirely into the marketing and copywriting niches.
Spam?
This led to idle speculation: If it was possible to short early-stage startups that VCs were backing, there would be as much incentive for the media to discuss a startup’s shortcomings and vapourware promises as there is to repeat their breathless braggadocio.
But I think that with the bubble times of 2018-2021 a lot of people entered the industry or changed their behavior because it was trendy and cool, and they have been way more down to ride the hype cycle rodeo.
My speculative musing is that if people could take short positions in startups and not just coattail on as one of a group of investors, I wonder if we’d get a lot fewer breathless PR puff-pieces and a lot more cases for pessimism around certain types of hype cycle investments, backed by investors betting their own moeny against the hype.
Web3/NFT/Crypto realities: using it is expensive and hard, scams left and right and the government actually arrives but doesn't remedy the damages. People are not in to save pennies on transactions but to get rich quick.
DALL-E/ChatGPT promises: A statistical model that can generate text and images that are impressive but not always accurate. Also, the tech is not that magical, we just used so much data to train it.
DALL-E/ChatGPT reality: Wows everyone, people actually use it tirelessly for writing code, creating artwork, recreationally etc.
We will probably hit the limits soon and won't have GAI next year but the stuff already delivered is already useful. The crypto stuff might become useful but its nowhere near the hype.
> DALL-E/ChatGPT reality: Wows everyone, people actually use it tirelessly for writing code, creating artwork, recreationally etc.
That's a pretty generous if not biased take, is it not? For me personally, ChatGPT is underwhelming and hasn't done anything remotely impressive when I have used it. And there's a lot of fervor around people using it, but are there interesting use cases outside of advertising? And are there not a ton of harmful use cases? The internet is going to be absolutely filled to the brim with GPT generated junk.
A chatbot that's relatively accurate at interpreting and summarising stuff compared with previous generation chatbots and an image generation algorithm that's actually pretty good are a damned sight more useful than NFTs which is why I agree with others that the comparison isn't helpful, but I don't think it's realistic to characterise OpenAI and AI enthusiasts in general as under-promising
It's a bit like thinking autonomous parallel parking will automatically bring you fully autonomous cars soon
These people usually aren’t people signing checks—just angry people online, and oftentimes tied in with political motivations. I don’t think many companies are licking their lips at the idea of firing artists (yet). They’re probably thinking about how they can use this to assist artists to get more done faster and at higher quality.
Not saying that there aren't issues that need to be discussed, nor am I saying that there isn't any (unnecessary) hype. But the comparison to Web3 is a stretch.
The author addresses this:
> One last thought -- don't overindex on the web3 <> LLMs comparison. Of course web3 was pure hot air while LLMs is real tech with actual applications -- that's not the parallel I'm making. The parallel is in the bubble formation social dynamics, especially in the VC crowd.
So aren't they just saying "hype is hype"?
(edited an incomplete sentence)
The negative takes are mostly correct in all the limitations they talk about, but what they miss is how amazing these things are despite these limitations. These things are remarkably simple and limited yet they can generate realistic photos of myself in places I've never been, wearing clothes I've never worn, doing things I've never done, with a quick text sentence. Or nearly pass the bar exam.
On top of that a lot of the limitations have straightforward ways to address, many of which are already in progress. It is going to get really interesting. StableDiffusion knows nothing about the images it is produces, its just repeated denoising with image targets. It doesn't really understand anything about your text either, its just matching up tags. But both of those things can easily change. Put a big language model in front of it to better understand text. Already variants of these image models have depth information. Next up 3d object information, maybe next models of physics so it can understand how things would actually work in the scene, and so on.
going to get wild.
The author of this Twitter thread is François Chollet, Senior Staff Software Engineer at Google, creator of Keras and major contributor to TensorFlow, and author of Deep Learning in Python, considered by many a seminal book in introductory DL...
I'd say he understands how amazing these things are despite the limitations, and he specifically says in the thread that it's an amazing time to be building DL apps.
That sounds like someone who's great at API design, not a deep learning researcher.
You didn't see this one? There are many more, but I remembered this one.
https://news.ycombinator.com/item?id=34086462
For AI to be as valuable as current rounds are implying it has to actually be capable of replacing your lawyer, your accountant, your software engineer. ChatGPT is nowhere near accurate enough to do that. It’s the same issue we ran into with super cruise control versus fully autonomous driving. Or speech recognition. Early progress was fast. Last mile in AI is always brutal.
Maybe there’s some argument to say ChatGPT won’t replace your lawyer or software engineer but will make them 20% more efficient. Possible. Though I’m still skeptical. ChatGPT’s unparalleled ability to create really convincing sounding errors is a big hidden negative productivity drag.
The biggest challenge for generative AI is its willingness to make things up. It’s fine when you’re playing around. Not so fine when you’re expecting it to actually help you in a real way.
I suspect this is why Google has not debuted such an interface despite literally decades of work on AI. You have to be able to bolt a “truth filter” onto the AI, which seems difficult.
Content generation AI is so obviously useful to the majority of people and it does not require an understanding of how it works in order to be impressed by it.
The majority of people are still interacting with this stuff primarily as a toy, and while it's a much, much smaller leap to imagine how you'd use it in everyday life vs. something like web3, most people aren't yet, and I don't think it's an absolute certainty that they will (or at the very least, how universally they will).
The comparison with web3 is very excessive though. This AI stuff is at least somewhat actually useful. Web3 was a gigantic billion dollar bubble that produced very little in the way of things that are useful for any purpose, even playing around. It's one of the most vapid bubbles in history outside pure financial instrument bubbles.