What if I’m a billionaire trying to crush the working class and accelerate climate change and political division so the class war doesn’t pop off before i can get to my climate bunker?
Or a billionaire fascist who wants to sloppify everyone’s brains and increase alienation while annihilating interiority so people will become docile and the class war won’t pop off and we get the 1984 timeline?
Or a billionaire asshole who wanted to murder a concept and settled on ‘truth’?
Or a really big ‘infinite jest’ fan?
So “ai” has a lot of use cases. Maybe dont be such a reflexive reactionary fucking Luddite piece of shit about it.
Blockchain solves a specific problem: safe transactions without a trusted authority.
It has a lot of downsides to solve this problem without a trusted authority, so in any case where you can use a trusted authority (for example a central server) it’s much better to use that instead of a blockchain.
So everyone who added blockchains to their projects gained all the downsides while never having the problem it was meant to solve in the first place.
AIs, and I assume you meant LLMs with that, are a different breed. LLMs are new: never before could a computer handle natural language to such a degree.
Problem is, that it’s still new. So no one knows what the “killer applications” are or what monetization should look like, or what the laws about it will be.
People just throw every against the wall and see what sticks… And hope for AGI/ASI and to be on the side that rides that nearly infinite potential to the moon.
Or, you know, crash and burn in case AI reaches a wall/diminishing returns/systemic problems that can’t be fixed.
I think semantic search could be a use for it, except our corporate overlords won’t give that for us, as that wouldn’t be as futuristic as a “talking computer”.
Blockchain is an adequate solution to a problem that already has other, cheaper solutions.
AI is an adequate solution to a problem that has no other similarly adequate solutions (classification of complex information). Unfortunately, all the money is in that solution being applied to problems where it’s not adequate (content generation, user interaction).
AI is an adequate solution to a problem that has no other similarly adequate solutions (classification of complex information).
Sentiment analysis machines and such have been around before LLMs and eat much less electricity.
LLMs taken over the “AI” label so much that any success from a machine learning context is attributed to it, while it actually defunds and kills research out of ML all into LLMs.
It’s true that LLMs (and GANs) are taking over a term that contains a lot of other stuff, from fuzzy logic to a fair chunk of computer linguistics.
If you look at what AI does, however, it’s mostly classification. Whether it’s fitting imprecise measurements into categories or analyzing waveform to figure out which word it represents regardless of diction and dialect; a lot of AI is just the attempt at classifying hard to classify stuff.
And then someone figure out how to hook that up to a Markov chain generator (LLMs) or run it repeatedly to “recognize” an image in pure noise (GANs). And those are cool little tricks but not really ones that solve a problem that needed solving. Okay, I’ll grant that GANs make a few things in image retouching more convenient but they’re also subject to a distressingly large number of failure modes and consume a monstrous amount of resources.
Plus the whole thing where they’re destroying the concept of photographic and videographic evidence. I dislike that as well.
I really like AI when used for what it’s good at: Taking messy input data and classifying it. We’re getting some really cool things done that way and some even justify the resources we’re spending. But I do agree with you that the vast majority of funding and resources gets spent on the next glorified chatbot in the vague hope that this one will actually generate some kind of profit. (I don’t think that any of the companies who are invested in AI still actually believe their products will generate a real benefit for the end user.)
If you look at what AI does, however, it’s mostly classification.
Not necessarily, a huge use case is regulation and control in the engineering, not the political sense. Like driverless cars, independently flying drones and such. And yeah, they need classification subsystems under the hood to work, but their ultimate outputs are complex control signals, not simple classes.
And don’t get me wrong, I also like ML and AI as a field, I just don’t like how OpenAI fucked the field with text generators that they got Silicon Valley to worship like gods. I even like LLMs, just not the grotesquely outsized cult around them.
Every decade has at least one of these buzzwords (multimedia, internet/ online, social media, mobile app, blockchain, cryptocoins, micropayment, delivery, ai,…)… They can be used to attract dumb investor’s money but they have their useful sides too.
Ok. They are just buzzwords which outline a set of tools. They are worthless without a realizable concept with a benefit for the end-user. And the use of the right tool for the job. So, I’m not sure about useful cryptocoins and blockchain use cases (I wouldn’t count financial speculation as particularly useful).
This isnt productive, and the hype is the largest I have ever seen. Ireland–a wealthy developed tech savvy nation–isnt building new homes to address their housing crisis because this shit is taking all the energy and water.
Okay, but, devils advocate:
What if I’m a billionaire trying to crush the working class and accelerate climate change and political division so the class war doesn’t pop off before i can get to my climate bunker?
Or a billionaire fascist who wants to sloppify everyone’s brains and increase alienation while annihilating interiority so people will become docile and the class war won’t pop off and we get the 1984 timeline?
Or a billionaire asshole who wanted to murder a concept and settled on ‘truth’?
Or a really big ‘infinite jest’ fan?
So “ai” has a lot of use cases. Maybe dont be such a reflexive reactionary fucking Luddite piece of shit about it.
deleted by creator
Blockchain solves a specific problem: safe transactions without a trusted authority.
It has a lot of downsides to solve this problem without a trusted authority, so in any case where you can use a trusted authority (for example a central server) it’s much better to use that instead of a blockchain.
So everyone who added blockchains to their projects gained all the downsides while never having the problem it was meant to solve in the first place.
AIs, and I assume you meant LLMs with that, are a different breed. LLMs are new: never before could a computer handle natural language to such a degree.
Problem is, that it’s still new. So no one knows what the “killer applications” are or what monetization should look like, or what the laws about it will be.
People just throw every against the wall and see what sticks… And hope for AGI/ASI and to be on the side that rides that nearly infinite potential to the moon.
Or, you know, crash and burn in case AI reaches a wall/diminishing returns/systemic problems that can’t be fixed.
We will see.
I think semantic search could be a use for it, except our corporate overlords won’t give that for us, as that wouldn’t be as futuristic as a “talking computer”.
Blockchain is an adequate solution to a problem that already has other, cheaper solutions.
AI is an adequate solution to a problem that has no other similarly adequate solutions (classification of complex information). Unfortunately, all the money is in that solution being applied to problems where it’s not adequate (content generation, user interaction).
Sentiment analysis machines and such have been around before LLMs and eat much less electricity.
LLMs taken over the “AI” label so much that any success from a machine learning context is attributed to it, while it actually defunds and kills research out of ML all into LLMs.
It’s true that LLMs (and GANs) are taking over a term that contains a lot of other stuff, from fuzzy logic to a fair chunk of computer linguistics.
If you look at what AI does, however, it’s mostly classification. Whether it’s fitting imprecise measurements into categories or analyzing waveform to figure out which word it represents regardless of diction and dialect; a lot of AI is just the attempt at classifying hard to classify stuff.
And then someone figure out how to hook that up to a Markov chain generator (LLMs) or run it repeatedly to “recognize” an image in pure noise (GANs). And those are cool little tricks but not really ones that solve a problem that needed solving. Okay, I’ll grant that GANs make a few things in image retouching more convenient but they’re also subject to a distressingly large number of failure modes and consume a monstrous amount of resources.
Plus the whole thing where they’re destroying the concept of photographic and videographic evidence. I dislike that as well.
I really like AI when used for what it’s good at: Taking messy input data and classifying it. We’re getting some really cool things done that way and some even justify the resources we’re spending. But I do agree with you that the vast majority of funding and resources gets spent on the next glorified chatbot in the vague hope that this one will actually generate some kind of profit. (I don’t think that any of the companies who are invested in AI still actually believe their products will generate a real benefit for the end user.)
Not necessarily, a huge use case is regulation and control in the engineering, not the political sense. Like driverless cars, independently flying drones and such. And yeah, they need classification subsystems under the hood to work, but their ultimate outputs are complex control signals, not simple classes.
And don’t get me wrong, I also like ML and AI as a field, I just don’t like how OpenAI fucked the field with text generators that they got Silicon Valley to worship like gods. I even like LLMs, just not the grotesquely outsized cult around them.
Just to point but…
Nothing is stopping that first billionaire to run to their climate bunker right now. It’s currently way better than it will be during the disaster.
And making people dumber is an almost certain way to make them more violent too.
The odds are good some of them are thinking exactly like you pointed. But that would be because they are dumb.
Every decade has at least one of these buzzwords (multimedia, internet/ online, social media, mobile app, blockchain, cryptocoins, micropayment, delivery, ai,…)… They can be used to attract dumb investor’s money but they have their useful sides too.
Ok. They are just buzzwords which outline a set of tools. They are worthless without a realizable concept with a benefit for the end-user. And the use of the right tool for the job. So, I’m not sure about useful cryptocoins and blockchain use cases (I wouldn’t count financial speculation as particularly useful).
Every time somebody starts raving about some tech, it’ll turn out to be a classic hype cycle.
This isnt productive, and the hype is the largest I have ever seen. Ireland–a wealthy developed tech savvy nation–isnt building new homes to address their housing crisis because this shit is taking all the energy and water.
That’s true. The tech bros are playing the market by blowing bubble after bubble and raising the stakes each time.
Gotta ask what the supervillain-ass end game is.
Excuse me the Segway never came back up
The tech itself though is still used in hoverboards, robots and some other self balancing micro mobility devices.
That graph is peak bullshit.
Just because you believe the hype, it doesn’t mean there’s a milder use case for your application.
Unfortunately LLM do have one profitable application: generating spam and astroturfing