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After the massive hype around generative AI, seems likely there will be an AI winter when the promised transformation in many business areas just doesn't happen

After the massive hype around generative AI, seems likely there will be an AI winter when the promised transformation in many business areas just doesn't happen as advertised.

pixl97 4y ago
I remember the hype cycle around this thing called the "internet" back in the day. People said it was going to take over the world, even though back then it was slow and kinda sucked. And then it did.
- diceduckmonk 4y ago
  I remember a hype cycle called “BigData”. Companies now realize data science that big of a step to business analytics of the 90s.
- lm28469 4y ago
  What about cryptos, VR, nosql, nfts, &c. ?
  - zachnwhite 4y ago
    thank you
- RandomLensman 4y ago
  Do you remember all the failed predictions, too?
- palata 4y ago
  > And then it did. After the dotcom bubble exploded. Can't we call that a winter?
  - pixl97 4y ago
    What metrics do you want to go by? At least by internet use and user growth the dotcom bubble still saw massive amounts of new user growth and online time by users. Was there a massive reduction in completely untenable .com's? But I'm not exactly sure if that's the definition of a winter, plenty of other internet based businesses did fine and kept growing in that time.
    - palata 4y ago
      Sounds fair indeed
- JohnFen 4y ago
  The internet was well-established and its worth proven many times over before it was ever open to the public, so well before the hype cycle happened.
Symmetry 4y ago
In many cases we see that making effective use of a new technology requires a lot of other changes. Electrification brought large productivity gains to factories, but only after they were re-designed to be more spread out as to compacted around a central motive shaft. IT has brought a lot of productivity gains but business processes have to be changed to make use of it. Likewise, making use of LLMs will probably require some bottom up rethinking of how businesses work which won't be fast or automatic.
ffhhj 4y ago
> doesn't happen as advertised. But there will be a small transformation: * More busy work will be automated taking away some of the fun and leaving the harder tasks thus making jobs shittier, pushing workers to find other kinds of work. * More solutions on AI looking for problems will be implemented increasing the speed of success/failure, and from the lottery winner effect we can expect "the granny that created an AI solution and earned millions" that other devs will follow and fail leaving debts.
- brazzy 4y ago
  > More busy work will be automated taking away some of the fun and leaving the harder tasks thus making jobs shittier Since when is busy work fun and hard tasks shitty?
Daishiman 4y ago
A disappointment in the hype cycle isn't equivalent to AI winter. The hype cycle always, eventually, hits a trough, even with wildly successful products. It's very likely we'll be disappointed with AI in many oversold contexts (I share the sentiment about self-driving cars), but it can't be denied that ChatGPT is a product that's being used _right now_ to massive success and still has quite a ways to go.
- RandomLensman 4y ago
  It doesn't go into large value decisions and projects in a meaningful way (pretty much like all AI) - that is the critical thing AI needs to get to. Where was AI when guaranteeing SVB's deposits was decided, for example?
  - Hermitian909 4y ago
    > It doesn't go into large value decisions and projects in a meaningful way (pretty much like all AI) - that is the critical thing AI needs to get to Large decisions such as SVB deposits are literally the last thing that will be given to AI, it's the most important part of the business. That doesn't mean AI is useless or is not being incorporated into valuable parts of businesses. I'm at a large tech company, LLMs are already entering some of our key product workflows. It massively lowers the floor for a number of product features e.g. recommendation systems. In a more general sense, many features that were previously too difficult to expose (e.g. simple coding commands) to business users are now on the table as long as we give them limited access to an LLM. The current hype train means that we don't even need to do much user education.
    - RandomLensman 4y ago
      I am not claiming AI is useless. Rather that pushing AI too hard will create disappointment as it isn't just going into every part of businesses with the same speed (or at all for still some time on some things).
- kenjackson 4y ago
  Also can I add that I hate the comparison to self-driving cars. The issue with self-driving cars is the penalty for a mis-step can be huge, even if doing something mundane, e.g., driving home from the neighborhood grocery store. If crashing a self-driving car required me to spend 5 minutes rejiggering it, I'd probably use the feature a lot. With generative models there's usually very little cost to it making a mistake -- and even better, I can determine when the cost is likely to be high and modify my behavior. Self-driving cars do seem much better than they used to be. But I have no interest in using them until they get better still. I don't have this same bar with LLMs or DALL-Es. And I think this will contribute to more continuous improvement in the technology.

After the massive hype around generative AI, seems likely there will be an AI winter when the promised transformation in many business areas just doesn't happen as advertised.

pixl97 4y ago

I remember the hype cycle around this thing called the "internet" back in the day. People said it was going to take over the world, even though back then it was slow and kinda sucked. And then it did.

diceduckmonk 4y ago
I remember a hype cycle called “BigData”. Companies now realize data science that big of a step to business analytics of the 90s.
lm28469 4y ago
What about cryptos, VR, nosql, nfts, &c. ?
- zachnwhite 4y ago
  thank you
RandomLensman 4y ago
Do you remember all the failed predictions, too?
palata 4y ago
> And then it did. After the dotcom bubble exploded. Can't we call that a winter?
- pixl97 4y ago
  What metrics do you want to go by? At least by internet use and user growth the dotcom bubble still saw massive amounts of new user growth and online time by users. Was there a massive reduction in completely untenable .com's? But I'm not exactly sure if that's the definition of a winter, plenty of other internet based businesses did fine and kept growing in that time.
  - palata 4y ago
    Sounds fair indeed
JohnFen 4y ago
The internet was well-established and its worth proven many times over before it was ever open to the public, so well before the hype cycle happened.

Symmetry 4y ago

In many cases we see that making effective use of a new technology requires a lot of other changes. Electrification brought large productivity gains to factories, but only after they were re-designed to be more spread out as to compacted around a central motive shaft. IT has brought a lot of productivity gains but business processes have to be changed to make use of it. Likewise, making use of LLMs will probably require some bottom up rethinking of how businesses work which won't be fast or automatic.

ffhhj 4y ago

> doesn't happen as advertised. But there will be a small transformation: * More busy work will be automated taking away some of the fun and leaving the harder tasks thus making jobs shittier, pushing workers to find other kinds of work. * More solutions on AI looking for problems will be implemented increasing the speed of success/failure, and from the lottery winner effect we can expect "the granny that created an AI solution and earned millions" that other devs will follow and fail leaving debts.

brazzy 4y ago
> More busy work will be automated taking away some of the fun and leaving the harder tasks thus making jobs shittier Since when is busy work fun and hard tasks shitty?

Daishiman 4y ago

A disappointment in the hype cycle isn't equivalent to AI winter. The hype cycle always, eventually, hits a trough, even with wildly successful products. It's very likely we'll be disappointed with AI in many oversold contexts (I share the sentiment about self-driving cars), but it can't be denied that ChatGPT is a product that's being used _right now_ to massive success and still has quite a ways to go.

RandomLensman 4y ago
It doesn't go into large value decisions and projects in a meaningful way (pretty much like all AI) - that is the critical thing AI needs to get to. Where was AI when guaranteeing SVB's deposits was decided, for example?
- Hermitian909 4y ago
  > It doesn't go into large value decisions and projects in a meaningful way (pretty much like all AI) - that is the critical thing AI needs to get to Large decisions such as SVB deposits are literally the last thing that will be given to AI, it's the most important part of the business. That doesn't mean AI is useless or is not being incorporated into valuable parts of businesses. I'm at a large tech company, LLMs are already entering some of our key product workflows. It massively lowers the floor for a number of product features e.g. recommendation systems. In a more general sense, many features that were previously too difficult to expose (e.g. simple coding commands) to business users are now on the table as long as we give them limited access to an LLM. The current hype train means that we don't even need to do much user education.
  - RandomLensman 4y ago
    I am not claiming AI is useless. Rather that pushing AI too hard will create disappointment as it isn't just going into every part of businesses with the same speed (or at all for still some time on some things).
kenjackson 4y ago
Also can I add that I hate the comparison to self-driving cars. The issue with self-driving cars is the penalty for a mis-step can be huge, even if doing something mundane, e.g., driving home from the neighborhood grocery store. If crashing a self-driving car required me to spend 5 minutes rejiggering it, I'd probably use the feature a lot. With generative models there's usually very little cost to it making a mistake -- and even better, I can determine when the cost is likely to be high and modify my behavior. Self-driving cars do seem much better than they used to be. But I have no interest in using them until they get better still. I don't have this same bar with LLMs or DALL-Es. And I think this will contribute to more continuous improvement in the technology.