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PaperclipPerfector  26d ago (text post)   36915 thread views

Culture War Roundup for the week of January 27, 2025

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uranium only has around 100 years of proven reserves

It's more complicated than that. Current reactors are not breeders and as such throw away most of their actinides unburnt (and cannot use thorium); after accounting for fixing those inefficiencies (which are avoidable, just not currently economic because uranium is cheap) and for mining thorium as well, you can do about x300 on that. And that's assuming we can't harvest the uranium in seawater, which is like x20 again.

Why isn't this community more concerned about these kinds of issues, as opposed to worrying about AI (which is not profitable, or efficient).

This article is low-quality. Everyone keeps forecasting that LLMs will hit a wall, and then they don't.

Aside from maybe pandemics, I expect trendlines to get scrambled by some combination of WWIII and AI before these come into play.

Okay where are they going to get more training data from? They've already used the entire internet. You also aren't accounting for the fact that OpenAI lost $5 billion last year.

It's not helpful for you to say the article is low quality without providing examples.

Okay where are they going to get more training data from?

Probably somewhere. Or they'll make do without it. I doubt if we got all of the performance possible from LLMs within seven years of discovering them (that would likely be some kind of record).

Alternatively, you can cast your mind back to 1980, and imagine asking "how can microprocessors continue shrinking without solving [whatever problem deep UV excimer laser photolithography solves]?"

(Surprisingly on topic, check out the next article there: Gwern’s AI-Generated Poetry was from 2019, and the performance improvements over that short of a time are stark.)

You also aren't accounting for the fact that OpenAI lost $5 billion last year.

They've got $500 billion more (sort of) lined up already, and you're worried about that? Those losses are trivially small.

I think that when they say they are out of training data, they mean they are out of legal training data. There's a lot of low-hanging illegal fruit they could pick. Goodle hasn't used everybody's gmail inboxes. I have about hundreds of thousands of pieces of input data they could harvest that way.

Also really dystopian. Would also explain the success of the new Chinese model. They don't give a shit about privacy.

Maybe they use the automatic conversation transcription technology that logs every conversation held in hearing range of a cell phone and transmits it to the government. Text transcripts of everything said in the United States for the past few years would certainly feed their data need.

It's been possible for a long time now, there's no way they aren't doing this.

I can guarantee you that transcribed illegal government wiretaps of everything heard by every cell phone are not in the training data.

This could be. Dystopian AF

With models like o1 and R1, they recursively improve themselves. Synthetic data works fine.

You also aren't accounting for the fact that OpenAI lost $5 billion last year.

And this is a problem? Are their investors with hundreds of billions to offer running scared? They're aware, they don't care. Running out of money is not a problem for them.

It doesn't though. In the linked article, there's clearly evidence that synthetic data leads to hallucinations over time.

What they do is hire people to make new training data. There's a few online platforms where you can get paid to do this. I've been paid to do this.

hire people to make new training data

That doesn't seem viable for the amount of data required by ML training in the current paradigm. I feel like the clear future is improvements in automated induction of data or just observation from reality.

Then how to explain O-3 and Deep Seek R1? I believed the same as you until very recently and now I am questioning that.

And if we can't figure out efficient fusion after 3 centuries, we really don't deserve nuclear energy in the first place.

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