7 ms·

Is AI Winter coming again?

40 points by gpt4o 2y ago

I heard someone saying that most of the AI startups aren't getting funding. I know that the first AI winter started by not getting enough funding. So what's your opinion?

minimaxir 2y ago
Not a winter, but a correction akin to crypto a couple years ago.
- talldayo 2y ago
  Yep. A lot of eggs are currently in one, barely-solvent basket. What happens next is anyone's guess.
kingkongjaffa 2y ago
> AI startups aren't getting funding Corollary: 99% of AI startups are not providing real customer value and do not deserve to get funding on merit.
- meiraleal 2y ago
  There is a lot of funding for capital-intensive projects and not much funding for consumer-level projects which will bring AI to the masses. If just 10% of what's going to Nvidia went to the end user ecosystem we would see much AI bringing much more ROI.
- jryle70 2y ago
  Correction: 99% of all startups are not providing real customer value. They would all die. The other 1% however, bring real customer value and go on to become a success. AI startups included. > do not deserve to get funding on merit What is the criteria to decide here? If you know please. I want to drop everything and invest in them.
  - Lionga 2y ago
    Criteria is providing real customer value. Now go drop everything and figure out who is doing that.
    - herbst 2y ago
      Many do. The question is can I recreate their exact business with a few lines of code?
      - meiraleal 2y ago
        No, you can't create a business with a few lines of code. Developing and marketing an app is so difficult that it is called "fullstack" and most people that call themselves fullstack developers aren't capable of doing the full stack.
  - herbst 2y ago
    I've seen a obvious ChatGPT wrapper being funded on a local variant of Shark Tank just because it was actually a nice idea. We've gone way to far already.
ggm 2y ago
> I know that the first AI winter started by not getting enough funding. Well.. not quite. The funding was government funding. The opponents got behind things like the lighthill report [1] and had the government funding cut. IMNSHO this was the right thing to do. The claims were overblown and it was wasting national funds in research. But it was pretty political. People stopped talking to each other for decades. I was a 12 year old in this time, My dad was in the trenches in the opposition to AI funding camp so that's my bias. Nothing which has come since makes me re-consider this, I might say that modern-day private capital JV/VC funding has been a bit silly, but in the end it's private funds so it's their call. [1] Lighthill, James (1973). "Artificial Intelligence: A General Survey" http://www.chilton-computing.org.uk/inf/literature/reports/lighthill_report/p001.htm http://www.chilton-computing.org.uk/inf/literature/reports/l...
mikewarot 2y ago
The first AI winter was because of a book about Perceptrons, was perceived as being extremely critical of them, which killed interest. It took decades for neural nets to finally prove their effectiveness. The second was because the benefits of "Expert Systems" were oversold, and didn't prove to be as beneficial as expected. There will be a heavy correction in the market caps of companies that bet heavy on AI, as the promises don't live up to the hype. However, in this case, there clearly is benefit to using LLMs, the cost of training has proven to be prohibitive. Slower and more prudent approaches, with better hardware will allow progress to continue. If nothing else, it'll be a mild AI winter.
- pdimitar 2y ago
  > However, in this case, there clearly is benefit to using LLMs Legitimate curious question: what are the clear benefits exactly? I mean stuff that objectively improves society, not the plaything that ChatGPT has mostly become (there are exceptions to this as well, of course, I had a CFO telling me lately he used ChatGPT to find mistakes or bad contract clauses).
  - mikewarot 2y ago
    Uses for LLMs and Neural Nets in general include: Searching documents in discovery, sentiment analysis, summarization, flushing out ideas, 1st level support, writing code, doing speech->text, text->speech, translation. There are many things we can do now that were previously expensive or cost prohibitive. This is about the same as the computerization of records. No longer to we have to pay people to keep rooms full of files in order to aid retrieval and long term record storage. --- but I see you're asking about non-cost things We can now read documents that are translated from other languages, lowering those barriers to learning about other cultures. It's now easier to interact with the information available to all via the internet. It also makes some evil things easier, but that comes with every technology.
    - pdimitar 2y ago
      OK, I can partially agree with some of the points but... writing code? Any tangible proof on that one? I have spoken with many colleagues who were adamant that the LLMs can at best provide some boilerplate generation and nothing much beyond that. One or two mentioned it could find a bug in their Python code. > This is about the same as the computerization of records. No longer to we have to pay people to keep rooms full of files in order to aid retrieval and long term record storage. Eh, have you read the "Bullshit Jobs" book? It's a social and economic problem, rarely has been a technological one... TL;DR people want headcount, not efficiency. :/
muzani 2y ago
AI tools and LLMs have been overfunded. A few are able to stand out, but many aren't able to catch up with the likes of OpenAI. Image, video, music, speech aren't fully solved yet, and new models are still competing with giants like Imagen and Midjourney. The startups that build on AI can still be heavily funded. Most likely you aren't going to see many AI startups like character.ai. They'll be things made possible with AI. Uber wasn't an app company nor a cloud company, it's a company made possible by the two. Reddit and FB/Meta didn't need mobile apps, but it certainly increased engagement.
fnord77 2y ago
I heard someone say that we're at the AI version of 1996 during the dotcom boom.
- aurareturn 2y ago
  I said that. I still think so.
  - steve_adams_86 2y ago
    I think so, yet for my career I’d hate to be wrong. I’m not sure how to weight my biases in the matter. I use AI daily and like it for a few use cases, but I’m not sure how it could bridge the gap from “useful boilerplate generator and rubber duck” to something as basic as “can actually find useful ways to clarify or optimize code in ways I can’t”. It’s not a big ask but it feels very far away despite recent progress.
    - aurareturn 2y ago
      We're really early. It's been only 1.5 years since GPT4 - which caught everyone's pants down. Hardware has to catch up. We need to produce a lot more compute. People need more time to build on top of the foundational models.
      - high_na_euv 2y ago
        GPT3, right?
- sumeno 2y ago
  People said the same thing about crypto right before it crashed. People say lots of things, it doesn't make them any more likely to be true.
  - eimrine 2y ago
    Crypto never crashes, it just allows you to buy it sometimes.
oainoai 2y ago
OpenAI is in hibernation now. If you look at OpenAI LLC articles of incorporation and address you will see them signaling this themselves. This is the hype cycle maneuvering.
- meiraleal 2y ago
  Yeah I have the impression they are deliverying the bare minimum (or even less than that) for a big shocking release as soon as they can (but there goes 1 year and a half already)
  - alexander2002 2y ago
    I wonder if they want to go for-profit before major updates
deleted 2y ago
[deleted]
gpt4o 2y ago
AI Winter reasons: Funding is lost due to unmet promises ● Lighthill Report 1973 shuts down funding in UK ● Dreyfus at MIT argues lots of human reasoning is not based on logic rules, involving instinct and unconscious reasoning ○ (No AI researcher will eat lunch with Dreyfus for the next decade) ● Sussman: “using precise language to describe essentially imprecise concepts doesn't make them any more precise.”
sitkack 2y ago
Remove startups from your thinking, it has nothing to do with what AI winter was. The only winter will be for those that do not use AI.
mdmunna 2y ago
[flagged]
WheelsAtLarge 2y ago
Yes, LLMs are hitting a plateau and there's no new clear path to AGI or something close.
MeetingsBrowser 2y ago
Big Tech is still pouring billions into AI. We're seeing real-world applications and breakthroughs. It's just harder for the "we'll sprinkle some AI on it" startups to get funded. Investors are looking for solid business models and actual problems solved, not just hype. The wheat's being separated from the chaff. Probably healthy for the ecosystem long-term.
seanmcdirmid 2y ago
We were talking about the new AI winter coming 10 and 5 years ago. Advances keep coming that put it off. As far as I can tell, we keep getting further away from the next AI winter, but that could change in a decade or so.
atleastoptimal 2y ago
The only thing that could cause an AI winter at this point is a thermonuclear war. Just the release of o1 hasn't been fully appreciated yet. And in the next few months and year ahead we are getting a deluge of new SOTA models that will completely change the assumptions of what AI can do. A lot of the AI startups are just cash-grab wrappers with little understanding of fundamentals under the hood. Their failure isn't reflective of the massive gains in AI and track to AGI in the next few years.
- chaosist 2y ago
  Common programming problems will be solved because they can be approached in a probabilistic fashion by the very nature that they are common problems. I would expect harder problems to be much harder. I am a non-software engineer, I work for a small company that we could do whatever we want with language models in terms of the business. The issue though is all of our business problems are stacks of one off problems that the current models offer us basically no help on. Even if the models could help us we would basically have to rebuild the business from the ground up around the models to really benefit much. Like the dotcom bubble, there is a large amount of time it will take for culture , business and society to leverage the technology. Between then and now I suspect sits an absolutely brutal AI winter that is brought on by nothing more than a good old recession.
TigerofTao 2y ago
[flagged]
goralph 2y ago
To be honest I wish the Attention paper never came out. All of this AI/LLM stuff is exasperating. I don't think I can stomach to hear another MBA talk about "leveraging AI" in their next startup/product initiative. Cool, better autocomplete in my IDE is handy. But that's about it. I'd trade that back in a heart beat if I didn't have to have awful chatbots shoved in my face every time I open a webpage. Retirement has never felt so far away.
- listenallyall 2y ago
  MBAs? All I hear are programmers (including on this page) praising ChatGPT for writing some subroutine so that they didn't have to themselves.
  - rsynnott 2y ago
    > for writing some subroutine Hadn't realised there were that many FORTRAN programmers still around (in fairness, various languages have used 'subroutine' to describe various special cases of functions, or sometimes just all functions, but generally those languages have largely died out.)
wruza 2y ago
Most of the AI startups also are shameless api proxies. I don’t see why funding or payments should go to yet another system prompt wrapper.
csomar 2y ago
Unless there is another jump in quality in the next GPT-5, we have plateaued. There is still time as there has been a significant jump between GTP-3.5 and GPT-4. I'd say we have at max one year to find out. The fact that OpenAI keeps releasing new products means they are quite pressured by market forces to demonstrate interpolation as investors are anxious about the billions being burned on compute. So in a nutshell, it'll boil down to the next year or so. Regarding people who say that GPT-4 increase productivity and whatnot. That's not the point, GPT-4/Claude3.5 do increase productivity and I use them daily and frequently. The question is whether that productivity increase will match the investments made. And investors have poured too much into AI.
- Lionga 2y ago
  The questions is if completely new ways of using GPT/LLMs will come up. If they are just what they are now (Copilot/Summarize Text etc.) better GPT will just have very marginal gains and 99% of investments in AI is wasted. If they are somehow useful in very novel ways maybe things look better.
  - csomar 2y ago
    We kind of had an explosion of wrapper companies around chatGPT. It seems, by far, text -> images -> code are the only things they are capable of and in diminishing returns order. I can't really imagine them being useful to something else because the ability to reason shouldn't be scoped to one particular field. If they can reason in math, they should be able to reason in programming or medicine too.
mergisi 2y ago
[dead]
segmondy 2y ago
Winter is seasonal and localized. There will be a winter but it will not be everywhere. There's a lot of folks building AI companies with no path to useful product or profit. It's just the next hot things, there's likewise been quite a number of investors that didn't want to miss the train so they hopped into whatever train they could irrespective of the destination. There will be a moment of reckoning. With that said, generative AI has proved to be very useful and we have absolutely no idea what the limits are, there' a lot to be built and in that manner, things will be good for quite a while. It might be that as the very first useful ideas introduce useful ideas, the companies that are currently lost will gain ideas and pivot their way to usefulness and profit. Or perhaps there will be enough useful companies to drown out the lost ones. With that said, plenty startups will die and plenty will succeed. It doesn't matter, just figure out a way to contribute positively and be part of those that will survive.

40 points by gpt4o 2y ago

I heard someone saying that most of the AI startups aren't getting funding. I know that the first AI winter started by not getting enough funding. So what's your opinion?

minimaxir 2y ago

Not a winter, but a correction akin to crypto a couple years ago.

talldayo 2y ago
Yep. A lot of eggs are currently in one, barely-solvent basket. What happens next is anyone's guess.

kingkongjaffa 2y ago

> AI startups aren't getting funding Corollary: 99% of AI startups are not providing real customer value and do not deserve to get funding on merit.

meiraleal 2y ago
There is a lot of funding for capital-intensive projects and not much funding for consumer-level projects which will bring AI to the masses. If just 10% of what's going to Nvidia went to the end user ecosystem we would see much AI bringing much more ROI.
jryle70 2y ago
Correction: 99% of all startups are not providing real customer value. They would all die. The other 1% however, bring real customer value and go on to become a success. AI startups included. > do not deserve to get funding on merit What is the criteria to decide here? If you know please. I want to drop everything and invest in them.
- Lionga 2y ago
  Criteria is providing real customer value. Now go drop everything and figure out who is doing that.
  - herbst 2y ago
    Many do. The question is can I recreate their exact business with a few lines of code?
    - meiraleal 2y ago
      No, you can't create a business with a few lines of code. Developing and marketing an app is so difficult that it is called "fullstack" and most people that call themselves fullstack developers aren't capable of doing the full stack.
- herbst 2y ago
  I've seen a obvious ChatGPT wrapper being funded on a local variant of Shark Tank just because it was actually a nice idea. We've gone way to far already.

ggm 2y ago

> I know that the first AI winter started by not getting enough funding. Well.. not quite. The funding was government funding. The opponents got behind things like the lighthill report [1] and had the government funding cut. IMNSHO this was the right thing to do. The claims were overblown and it was wasting national funds in research. But it was pretty political. People stopped talking to each other for decades. I was a 12 year old in this time, My dad was in the trenches in the opposition to AI funding camp so that's my bias. Nothing which has come since makes me re-consider this, I might say that modern-day private capital JV/VC funding has been a bit silly, but in the end it's private funds so it's their call. [1] Lighthill, James (1973). "Artificial Intelligence: A General Survey" http://www.chilton-computing.org.uk/inf/literature/reports/lighthill_report/p001.htm http://www.chilton-computing.org.uk/inf/literature/reports/l...

mikewarot 2y ago

The first AI winter was because of a book about Perceptrons, was perceived as being extremely critical of them, which killed interest. It took decades for neural nets to finally prove their effectiveness. The second was because the benefits of "Expert Systems" were oversold, and didn't prove to be as beneficial as expected. There will be a heavy correction in the market caps of companies that bet heavy on AI, as the promises don't live up to the hype. However, in this case, there clearly is benefit to using LLMs, the cost of training has proven to be prohibitive. Slower and more prudent approaches, with better hardware will allow progress to continue. If nothing else, it'll be a mild AI winter.

pdimitar 2y ago
> However, in this case, there clearly is benefit to using LLMs Legitimate curious question: what are the clear benefits exactly? I mean stuff that objectively improves society, not the plaything that ChatGPT has mostly become (there are exceptions to this as well, of course, I had a CFO telling me lately he used ChatGPT to find mistakes or bad contract clauses).
- mikewarot 2y ago
  Uses for LLMs and Neural Nets in general include: Searching documents in discovery, sentiment analysis, summarization, flushing out ideas, 1st level support, writing code, doing speech->text, text->speech, translation. There are many things we can do now that were previously expensive or cost prohibitive. This is about the same as the computerization of records. No longer to we have to pay people to keep rooms full of files in order to aid retrieval and long term record storage. --- but I see you're asking about non-cost things We can now read documents that are translated from other languages, lowering those barriers to learning about other cultures. It's now easier to interact with the information available to all via the internet. It also makes some evil things easier, but that comes with every technology.
  - pdimitar 2y ago
    OK, I can partially agree with some of the points but... writing code? Any tangible proof on that one? I have spoken with many colleagues who were adamant that the LLMs can at best provide some boilerplate generation and nothing much beyond that. One or two mentioned it could find a bug in their Python code. > This is about the same as the computerization of records. No longer to we have to pay people to keep rooms full of files in order to aid retrieval and long term record storage. Eh, have you read the "Bullshit Jobs" book? It's a social and economic problem, rarely has been a technological one... TL;DR people want headcount, not efficiency. :/

muzani 2y ago

AI tools and LLMs have been overfunded. A few are able to stand out, but many aren't able to catch up with the likes of OpenAI. Image, video, music, speech aren't fully solved yet, and new models are still competing with giants like Imagen and Midjourney. The startups that build on AI can still be heavily funded. Most likely you aren't going to see many AI startups like character.ai. They'll be things made possible with AI. Uber wasn't an app company nor a cloud company, it's a company made possible by the two. Reddit and FB/Meta didn't need mobile apps, but it certainly increased engagement.

fnord77 2y ago

I heard someone say that we're at the AI version of 1996 during the dotcom boom.

aurareturn 2y ago
I said that. I still think so.
- steve_adams_86 2y ago
  I think so, yet for my career I’d hate to be wrong. I’m not sure how to weight my biases in the matter. I use AI daily and like it for a few use cases, but I’m not sure how it could bridge the gap from “useful boilerplate generator and rubber duck” to something as basic as “can actually find useful ways to clarify or optimize code in ways I can’t”. It’s not a big ask but it feels very far away despite recent progress.
  - aurareturn 2y ago
    We're really early. It's been only 1.5 years since GPT4 - which caught everyone's pants down. Hardware has to catch up. We need to produce a lot more compute. People need more time to build on top of the foundational models.
    - high_na_euv 2y ago
      GPT3, right?
sumeno 2y ago
People said the same thing about crypto right before it crashed. People say lots of things, it doesn't make them any more likely to be true.
- eimrine 2y ago
  Crypto never crashes, it just allows you to buy it sometimes.

oainoai 2y ago

OpenAI is in hibernation now. If you look at OpenAI LLC articles of incorporation and address you will see them signaling this themselves. This is the hype cycle maneuvering.

meiraleal 2y ago
Yeah I have the impression they are deliverying the bare minimum (or even less than that) for a big shocking release as soon as they can (but there goes 1 year and a half already)
- alexander2002 2y ago
  I wonder if they want to go for-profit before major updates

deleted 2y ago

[deleted]

gpt4o 2y ago

AI Winter reasons: Funding is lost due to unmet promises ● Lighthill Report 1973 shuts down funding in UK ● Dreyfus at MIT argues lots of human reasoning is not based on logic rules, involving instinct and unconscious reasoning ○ (No AI researcher will eat lunch with Dreyfus for the next decade) ● Sussman: “using precise language to describe essentially imprecise concepts doesn't make them any more precise.”

sitkack 2y ago

Remove startups from your thinking, it has nothing to do with what AI winter was. The only winter will be for those that do not use AI.

mdmunna 2y ago

[flagged]

WheelsAtLarge 2y ago

Yes, LLMs are hitting a plateau and there's no new clear path to AGI or something close.

MeetingsBrowser 2y ago

Big Tech is still pouring billions into AI. We're seeing real-world applications and breakthroughs. It's just harder for the "we'll sprinkle some AI on it" startups to get funded. Investors are looking for solid business models and actual problems solved, not just hype. The wheat's being separated from the chaff. Probably healthy for the ecosystem long-term.

seanmcdirmid 2y ago

We were talking about the new AI winter coming 10 and 5 years ago. Advances keep coming that put it off. As far as I can tell, we keep getting further away from the next AI winter, but that could change in a decade or so.

atleastoptimal 2y ago

The only thing that could cause an AI winter at this point is a thermonuclear war. Just the release of o1 hasn't been fully appreciated yet. And in the next few months and year ahead we are getting a deluge of new SOTA models that will completely change the assumptions of what AI can do. A lot of the AI startups are just cash-grab wrappers with little understanding of fundamentals under the hood. Their failure isn't reflective of the massive gains in AI and track to AGI in the next few years.

chaosist 2y ago
Common programming problems will be solved because they can be approached in a probabilistic fashion by the very nature that they are common problems. I would expect harder problems to be much harder. I am a non-software engineer, I work for a small company that we could do whatever we want with language models in terms of the business. The issue though is all of our business problems are stacks of one off problems that the current models offer us basically no help on. Even if the models could help us we would basically have to rebuild the business from the ground up around the models to really benefit much. Like the dotcom bubble, there is a large amount of time it will take for culture , business and society to leverage the technology. Between then and now I suspect sits an absolutely brutal AI winter that is brought on by nothing more than a good old recession.

TigerofTao 2y ago

[flagged]

goralph 2y ago

To be honest I wish the Attention paper never came out. All of this AI/LLM stuff is exasperating. I don't think I can stomach to hear another MBA talk about "leveraging AI" in their next startup/product initiative. Cool, better autocomplete in my IDE is handy. But that's about it. I'd trade that back in a heart beat if I didn't have to have awful chatbots shoved in my face every time I open a webpage. Retirement has never felt so far away.

listenallyall 2y ago
MBAs? All I hear are programmers (including on this page) praising ChatGPT for writing some subroutine so that they didn't have to themselves.
- rsynnott 2y ago
  > for writing some subroutine Hadn't realised there were that many FORTRAN programmers still around (in fairness, various languages have used 'subroutine' to describe various special cases of functions, or sometimes just all functions, but generally those languages have largely died out.)

wruza 2y ago

Most of the AI startups also are shameless api proxies. I don’t see why funding or payments should go to yet another system prompt wrapper.

csomar 2y ago

Unless there is another jump in quality in the next GPT-5, we have plateaued. There is still time as there has been a significant jump between GTP-3.5 and GPT-4. I'd say we have at max one year to find out. The fact that OpenAI keeps releasing new products means they are quite pressured by market forces to demonstrate interpolation as investors are anxious about the billions being burned on compute. So in a nutshell, it'll boil down to the next year or so. Regarding people who say that GPT-4 increase productivity and whatnot. That's not the point, GPT-4/Claude3.5 do increase productivity and I use them daily and frequently. The question is whether that productivity increase will match the investments made. And investors have poured too much into AI.

Lionga 2y ago
The questions is if completely new ways of using GPT/LLMs will come up. If they are just what they are now (Copilot/Summarize Text etc.) better GPT will just have very marginal gains and 99% of investments in AI is wasted. If they are somehow useful in very novel ways maybe things look better.
- csomar 2y ago
  We kind of had an explosion of wrapper companies around chatGPT. It seems, by far, text -> images -> code are the only things they are capable of and in diminishing returns order. I can't really imagine them being useful to something else because the ability to reason shouldn't be scoped to one particular field. If they can reason in math, they should be able to reason in programming or medicine too.

mergisi 2y ago

[dead]

segmondy 2y ago

Winter is seasonal and localized. There will be a winter but it will not be everywhere. There's a lot of folks building AI companies with no path to useful product or profit. It's just the next hot things, there's likewise been quite a number of investors that didn't want to miss the train so they hopped into whatever train they could irrespective of the destination. There will be a moment of reckoning. With that said, generative AI has proved to be very useful and we have absolutely no idea what the limits are, there' a lot to be built and in that manner, things will be good for quite a while. It might be that as the very first useful ideas introduce useful ideas, the companies that are currently lost will gain ideas and pivot their way to usefulness and profit. Or perhaps there will be enough useful companies to drown out the lost ones. With that said, plenty startups will die and plenty will succeed. It doesn't matter, just figure out a way to contribute positively and be part of those that will survive.