Not simply operating at a loss, absolutely dumping their prices giving away their products for almost nothing to gain market share. They are burning money at an impressive rate, just for some imaginary payoff in the future.
All MBAs and CEOs are like puppies chasing their own tails.
They want the growth because number go up good. They’ll do anything for number go up. And when number go up, they get the good and then they need to focus on next number go up.
They have no long term plan other than number go up. For the next few quarters, they can slap AI on anything and number go up. What happens if AI takes all the non manual labor jobs? Or if it turns out AI is useless and they wasted billions on snake oil? They don’t know, cause they were thinking about number go up right now, not number go up later.
It’s fine, because even though the CEO eventually drives the company into the ground in pursuit of indefinite growth over long-term stability, that accomplishment is no deterrent to getting hired at another company to do it again. The idea of companies with a long-term vision and plan that provides employees with stability and a career is dead.
It’s hard to imagine that gaining market share is even meaningful right now. There’s such a profusion of stuff out there. How much does it actually mean if someone is using your product today, I wonder?
I know people replacing basic tools with AI versions that are basically just running the simply tool and pretty printing the output
They’re only foing it because it’s basically free to run it through AI. That whoisbut with AI is going to be so expensive when these companies enshittif-AI
Sure that’s the point of venture capital, throwing some money at the wall and see what sticks. You’d expect to have most of them fail, but the one good one makes up for it.
However in this case it isn’t people throwing some money at startups. It’s large companies like Microsoft throwing trillions into this new tech. And not just the one company looking for a little niche to fill, all of them are all in, flooding the market with random shit.
Uber and Spotify are maybe not the best examples to use, although they are examples of people throwing away money in hopes of some sort of payoff (even though they both made a small profit recently, but nowhere near digging themselves out of the hole). They are however problematic in the way they operate. Uber’s whole deal is exploiting workers, turning employees into contractors just to exploit them. And also skirting regulations around taxis for the most part. They have been found to be illegal in a lot of civilised countries and had to change the way they do business there, limit their services or not operate in those countries at all. Spotify is music and the music industry is a whole thing I won’t get into.
The current AI bubble isn’t comparable to venture capital investing in some startups. It’s more comparable to the dotcom bubble, where the industry is perceived to move in a certain direction. Either companies invest heavily and get with the times, or they die. And smart investors put their money in anything with the new tech, since that’s where the money is going to be made. Back then the new tech was the internet, now the new tech is AI. We found out the hard way, it was total BS. The internet wasn’t the infinite money glitch people thought it was and we all paid the price.
However the scale of that bubble was small as compared to this new AI bubble. And the internet was absolutely a trans-formative technology, changing the way we work and live forever. It’s too early to say if this LLM based “AI” technology will do the same, but I doubt it. The amount of BS thrown around these days is too high. As someone with a somewhat good grasp of how LLMs actually work on a fundamental level, the promised made aren’t backed up by facts. And the amount of money being put into this aren’t near any even optimistic payoff in the future.
If you want to throw in a simple, over simplified example: This AI boom is more like people throwing money at Theranos than anything else.
Well maybe one person is a little bit more impressed by some pretty pictures than another person. I really don’t see what that has to do with a company like Microsoft putting their money into this? They don’t make songs or movie trailers.
To me I’m stunned but that’s just me, on top of this we’re only in year like 5 of AI going mainstream, where will it be in 10 years? 20 years?
This is a common trap a lot of people fall into. See what improvements have been made the last couple of years, who knows where it will end up right? Unfortunately, reality doesn’t work like that. Improvements made in the past don’t guarantee improvements will continue in the future. There are ceilings that can be run into and are hard to break. There can even be hard limits that are impossible to break. There might be good reasons to not further develop promising technologies from the past into the future. There is no such thing as infinite growth.
Edit:
Just checked out that song, man that song is shit…
“My job vanished without lift.” What does that even mean? That’s not even English.
And that’s just one of the dozens of issues I’ve seen in 30 secs. You are kidding yourself if you think this is the future, that’s one shit future bro.
All right, we are done here. I’ve tried to engage with you in a fair and honest way. Giving you the benefit of the doubt and trying to respond to the points you are trying to make.
But it appears you are just a troll or an idiot, either way I’m done.
The gains in AI have been almost entirely in compute power and training, and those gains have run into powerful diminishing returns. At the core it’s all still running the same Markov chains as the machine learning experiments from the dawn of computing; the math is over a hundred years old and basically unchanged.
For us to see another leap in progress we’ll need to pioneer new calculations and formulate different types of thought, then find a way to integrate that with large transformer networks.
Mixture of experts has been in use since 1991, and it’s essentially just a way to split up the same process as a dense model.
Tanks are an odd comparison, because not only have they changed radically since WW2, to the point that many crew positions have been entirely automated, but also because the role of tanks in modern combat has been radically altered since then (e.g. by the proliferation of drone warfare). They just look sort of similar because of basic geometry.
Consider the current crop of LLMs as the armor that was deployed in WW1, we can see the promise and potential, but it has not yet been fully realized. If you tried to match a WW1 tank against a WW2 tank it would be no contest, and modern armor could destroy both of them with pinpoint accuracy while moving full speed over rough terrain outside of radar range (e.g. what happened in the invasion of Iraq).
It will take many generational leaps across many diverse technologies to get from where we are now to realizing the full potential of large language models, and we can’t get there through simple linear progression any more than tanks could just keep adding thicker armor and bigger guns, it requires new technologies.
nd modern armor could destroy both of them with pinpoint accuracy while moving full speed over rough terrain outside of radar range (e.g. what happened in the invasion of Iraq).
lol, that is NOT what happened in Iraq. The tanks were sitting on low boy trucks for the vast majority of the invasion. How do I know this? Because they were in my convoys.
Even for major offensives after the initial invasion, that’s not at all what happened. They were basically employed as large mortars, sitting about a half mile outside of a town, and leveling it.
Uber’s value-add wasn’t in putting black car services on the internet. It was in operating as a universal middleman for transactions between riders and cabbies.
Similarly, Spotify found a way of scamming both media content creators and advertisers at an industrial scale, while propagating a bunch of far-right influencers for the benefit of anti-tax / anti-environment / anti-LGBTQ conservative groups.
It’s worth interrogating what the real business model is for any of these services. If you get under the hood of AI, what you’re going to find is a lot of CYA applications - the military can cheaply exploit AI to produce fountains of “This guy is a terrorist” data points that help justify the next airstrike, call centers can churn out convincing scam calls more quickly and cheaply than ever before, visual arts studios can rapidly and covertly plagiarize professionally produced media.
These are legalistic tools for evading bureaucratic oversight. They aren’t value-add to the retail customer in any way that matters.
We also don’t know the true cost of these tools since most AI service providers are still operating at a loss.
Not simply operating at a loss, absolutely dumping their prices giving away their products for almost nothing to gain market share. They are burning money at an impressive rate, just for some imaginary payoff in the future.
A future where we don’t have jobs so the rich can make more money by selling us stuff? But I won’t have money to pay for stuff! Hmmm!
All MBAs and CEOs are like puppies chasing their own tails.
They want the growth because number go up good. They’ll do anything for number go up. And when number go up, they get the good and then they need to focus on next number go up.
They have no long term plan other than number go up. For the next few quarters, they can slap AI on anything and number go up. What happens if AI takes all the non manual labor jobs? Or if it turns out AI is useless and they wasted billions on snake oil? They don’t know, cause they were thinking about number go up right now, not number go up later.
Our economy is a farce.
and so goes the ouroboros of late stage capitalism until we are back to feudalism
It’s fine, because even though the CEO eventually drives the company into the ground in pursuit of indefinite growth over long-term stability, that accomplishment is no deterrent to getting hired at another company to do it again. The idea of companies with a long-term vision and plan that provides employees with stability and a career is dead.
The real reason is they want enough money pumped into AI so someone can automate fascism.
That’s seriously the plan
Fucking clown world
It’s hard to imagine that gaining market share is even meaningful right now. There’s such a profusion of stuff out there. How much does it actually mean if someone is using your product today, I wonder?
And, in doing so, they’ve set the market price at that value for the service they advertise, which is more than they deliver already.
When Ai enters the Valley of Discontent, the price it can set for what it actually offers will be even less than it is now.
So many companies are going to get burnt by it
I know people replacing basic tools with AI versions that are basically just running the simply tool and pretty printing the output
They’re only foing it because it’s basically free to run it through AI. That
whoisbut with AI is going to be so expensive when these companies enshittif-AIThis is true with most VC backed tech companies, not just AI
The dream is to destroy things like entry level professional jobs so they can add to the class divide.
The same was true for YouTube, in the beginning they operated at a loss, and when people were hooked on the service, they monetized it.
YouTube wasn’t created to make money, it was created to watch the wardrobe malfunction.
nah, it was invented to be able to watch a kid’s little brother bite his finger
deleted by creator
Tangible value, not just a black box that might give you what you want
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lol, I have llama.cpp and ollama setup on a separate pc just so I can understand and discuss from experience.
What’s your point?
Sure that’s the point of venture capital, throwing some money at the wall and see what sticks. You’d expect to have most of them fail, but the one good one makes up for it.
However in this case it isn’t people throwing some money at startups. It’s large companies like Microsoft throwing trillions into this new tech. And not just the one company looking for a little niche to fill, all of them are all in, flooding the market with random shit.
Uber and Spotify are maybe not the best examples to use, although they are examples of people throwing away money in hopes of some sort of payoff (even though they both made a small profit recently, but nowhere near digging themselves out of the hole). They are however problematic in the way they operate. Uber’s whole deal is exploiting workers, turning employees into contractors just to exploit them. And also skirting regulations around taxis for the most part. They have been found to be illegal in a lot of civilised countries and had to change the way they do business there, limit their services or not operate in those countries at all. Spotify is music and the music industry is a whole thing I won’t get into.
The current AI bubble isn’t comparable to venture capital investing in some startups. It’s more comparable to the dotcom bubble, where the industry is perceived to move in a certain direction. Either companies invest heavily and get with the times, or they die. And smart investors put their money in anything with the new tech, since that’s where the money is going to be made. Back then the new tech was the internet, now the new tech is AI. We found out the hard way, it was total BS. The internet wasn’t the infinite money glitch people thought it was and we all paid the price.
However the scale of that bubble was small as compared to this new AI bubble. And the internet was absolutely a trans-formative technology, changing the way we work and live forever. It’s too early to say if this LLM based “AI” technology will do the same, but I doubt it. The amount of BS thrown around these days is too high. As someone with a somewhat good grasp of how LLMs actually work on a fundamental level, the promised made aren’t backed up by facts. And the amount of money being put into this aren’t near any even optimistic payoff in the future.
If you want to throw in a simple, over simplified example: This AI boom is more like people throwing money at Theranos than anything else.
deleted by creator
Well maybe one person is a little bit more impressed by some pretty pictures than another person. I really don’t see what that has to do with a company like Microsoft putting their money into this? They don’t make songs or movie trailers.
This is a common trap a lot of people fall into. See what improvements have been made the last couple of years, who knows where it will end up right? Unfortunately, reality doesn’t work like that. Improvements made in the past don’t guarantee improvements will continue in the future. There are ceilings that can be run into and are hard to break. There can even be hard limits that are impossible to break. There might be good reasons to not further develop promising technologies from the past into the future. There is no such thing as infinite growth.
Edit:
Just checked out that song, man that song is shit…
“My job vanished without lift.” What does that even mean? That’s not even English.
And that’s just one of the dozens of issues I’ve seen in 30 secs. You are kidding yourself if you think this is the future, that’s one shit future bro.
deleted by creator
All right, we are done here. I’ve tried to engage with you in a fair and honest way. Giving you the benefit of the doubt and trying to respond to the points you are trying to make.
But it appears you are just a troll or an idiot, either way I’m done.
deleted by creator
Quickly making garbage doesn’t make the garbage good.
Yes that was the argument
u/Thorry84@feddit.nl: AI produces garbage
me: this looks amazing to me, sure it’s not perfect but it’s super impressive considering it was made in like 30 minutes
u/Thorry84@feddit.nl: no it’s garbage, look I noticed minor things that are not correct!
me: fair enough, can you make something better using any other tools besides AI?
u/Thorry84@feddit.nl: fuck you🤬🤬🤬🤬🤬🤬
The gains in AI have been almost entirely in compute power and training, and those gains have run into powerful diminishing returns. At the core it’s all still running the same Markov chains as the machine learning experiments from the dawn of computing; the math is over a hundred years old and basically unchanged.
For us to see another leap in progress we’ll need to pioneer new calculations and formulate different types of thought, then find a way to integrate that with large transformer networks.
deleted by creator
Mixture of experts has been in use since 1991, and it’s essentially just a way to split up the same process as a dense model.
Tanks are an odd comparison, because not only have they changed radically since WW2, to the point that many crew positions have been entirely automated, but also because the role of tanks in modern combat has been radically altered since then (e.g. by the proliferation of drone warfare). They just look sort of similar because of basic geometry.
Consider the current crop of LLMs as the armor that was deployed in WW1, we can see the promise and potential, but it has not yet been fully realized. If you tried to match a WW1 tank against a WW2 tank it would be no contest, and modern armor could destroy both of them with pinpoint accuracy while moving full speed over rough terrain outside of radar range (e.g. what happened in the invasion of Iraq).
It will take many generational leaps across many diverse technologies to get from where we are now to realizing the full potential of large language models, and we can’t get there through simple linear progression any more than tanks could just keep adding thicker armor and bigger guns, it requires new technologies.
lol, that is NOT what happened in Iraq. The tanks were sitting on low boy trucks for the vast majority of the invasion. How do I know this? Because they were in my convoys.
Even for major offensives after the initial invasion, that’s not at all what happened. They were basically employed as large mortars, sitting about a half mile outside of a town, and leveling it.
Uber’s value-add wasn’t in putting black car services on the internet. It was in operating as a universal middleman for transactions between riders and cabbies.
Similarly, Spotify found a way of scamming both media content creators and advertisers at an industrial scale, while propagating a bunch of far-right influencers for the benefit of anti-tax / anti-environment / anti-LGBTQ conservative groups.
It’s worth interrogating what the real business model is for any of these services. If you get under the hood of AI, what you’re going to find is a lot of CYA applications - the military can cheaply exploit AI to produce fountains of “This guy is a terrorist” data points that help justify the next airstrike, call centers can churn out convincing scam calls more quickly and cheaply than ever before, visual arts studios can rapidly and covertly plagiarize professionally produced media.
These are legalistic tools for evading bureaucratic oversight. They aren’t value-add to the retail customer in any way that matters.
They are sucking up our power supply at a furious pace though.