Modern AI data centers consume enormous amounts of power, and it looks like they will get even more power-hungry in the coming years as companies like Google, Microsoft, Meta, and OpenAI strive towards artificial general intelligence (AGI). Oracle has already outlined plans to use nuclear power plants for its 1-gigawatt datacenters. It looks like Microsoft plans to do the same as it just inked a deal to restart a nuclear power plant to feed its data centers, reports Bloomberg.

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6 points
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Nfts were a scam from the start something that has no actual purpose utility or value being given value through hype.

Generative AI is very different. In my honest opinion you have to have your head in the sand if you don’t believe that AI is only going to incrementally improve and expand in capabilities. Just like it has year over year for the last 5 to 10 years. And just like for the last decade it continues to solve more and more real-world problems in increasingly effective manners.

It isn’t just constrained to llms either.

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7 points

The creators who made the LLM boom said they cannot improve it any more with the current technique due to diminishing returns.

It’s worthless in its current state.

Should be dying out faster imo.

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2 points

That’s one groups opinion, we still see improving LLMs I’m sure they will continue to improve and be adapted for whatever future use we need them. I mean I personally find them great in their current state for what I use them for

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3 points

What skin do you have in this game? Leading industry experts, who btw want to SELL IT TO YOU, told you it has hit a ceiling. Why do you refute it so much? Let it die, we will all be better off.

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-1 points

There are always new techniques and improvements. If you look at the current state, we haven’t even had a slowdown

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1 point
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Nah

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4 points
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One of the major problems with LLMs is it’s a “boom”. People are rightfully soured on them as a concept because jackasses trying to make money lie about their capabilities and utility – never mind the ethics of obtaining the datasets used to train them.

They’re absolutely limited, flawed, and there are better solutions for most problems … but beyond the bullshit LLMs are a useful tool for some problems and they’re not going away.

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2 points
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I cannot think of one single application where an LLM is better or even equivalent than having a person do the job. Its real only use is to trade human workers for cheaper but inferior output, at the detriment to mankind as a whole because we have in excess labor and in shortage power.

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1 point

I suspect you’re right. But there really is never a good way to tell with these kinds of experimental techs. It could be a runaway chain of improvement. Or it is probably even odds that there is a visible and clear decline before it peters out, or just suddenly slams into a beick wall with no warning.

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