No, publishers don’t go to the stores. The stores send the books back to the publisher.

What are my arguments? Can you even tell me?

Because what I’ve said. Is that we already do destroys millions of unsold books. And the various filings, rapports, inquiries, and fucking weather data, isn’t sold at bookstores to begin with. So the risk of those being bought and destroyed are zero.

So… you have not cared one bit, that publishers destroy unsold books for well over 50 years. But when these companies do it, it’s somehow terrible.

To scan every page manually is going to take hours. Where as if you remove the spine and separate the pages, you can feed it automatically in minutes.

And since they want to process hundreds of thousands of books… well, you’re literate so in sure you can do the math.

They’re just books… And again. For the fifth time probably, publishers destroy more unsold books than these companies. And have been doing so for the past 50 years.

No one seems to care publishers destroy old unsold books. But as soon as it’s AI companies then all of a sudden it’s a crime against humanity.

Buddy, how many books do you think are written every year?

If you started today. And did nothing but read until you died. You would not even have finished all the new books that were published last year.

Point being. There’s an enourmous amount of books printed every year. Most of them doesnt sell very well. So they are sent back to the publisher. And the publisher does not have room to keep every copy. So they’re destroyed. Maybe recycled into other paper products, maybe burned for energy. Regardless. What AI companies are buying is but a drop in the ocean.

And it has nothing to do with people “not reading”

Seriously, what the fuck are you talking about?

I’m sorry you didnt know the vast majority of unsold books are destroyed and recycled into something else. What did you think we did with them? No one wants to store 10’000 unsold copies of Robert Holms, “The straight circle”

What they’re buying are the cheapest literature they can find. Old unsold books no one wanted for decades.

There’s not a single scientific finding we have not digitalised, which you can buy the originals of. We’ve digitalised every single patent filed. Ever.

And weather data? Seriously? You think they’re buying weather data published on paper only? Where do you even buy that?

You’re doing an awful lot of speculating. The texts circulating through clubs, are circulating. These books were not.

Do you have any idea how many books we casually destroy? Books that never got sold, that are just wasting space for the next new book. The only difference is that unsold books being burned for energy isn’t manking the news. It’s just another thursday

These companies need quantity over quality. They’re gonna buy the cheapest books in bulk they can.

Contrary to what some might think. I’m not taking a stance for AI. I’m just pointing out, no one cared about these books 1 month ago. No one wanted to buy them. No one wanted to read them. That’s why they’ve been sitting on a shelf in a warehouse collecting dust.

They’re not valuable in any sense of the word. They’re only “rare” in the sense that they sold so poorly, there was no point in printing more.

This is such a silly thing to glue on the hate-train. “They’re destroying books no one wanted to read!” Oh no… anyway

General Public License lincensed code

What is it you think we’re talking about? This isn’t some LLM. It’s a very specific purposebuilt piece of software to analyse data from earthquakes and recordable shifts in the tectonic plates.

I disagree with your assessment. Modern machine learning methods will result in a far more complex algorithm than any human could device on their own. It will be “cheap” to execute, but only because of the vast amount of data it’s been trained on. That’s the strength. The raw number of calculations it can do per second means it can sift through more data in a day than a human could in its lifetime.

The biggest danger is hidden local minimums that can potentially distort new results and findings. But that’s not unique to machine learning. And you can let the AI grade its result with how certain it is. Automatically flag any result that falls below a certain threshold. And again, this is where the danger of local minimum come in. Because it can raise the certainty of results when maybe it shouldn’t be so certain. Though you will find out quickly when results are false with high certainty. Then you go back and you keep working at it.

As of this particular topic of earthquakes. There are no traditional tools of accurately predicting them. We’ve never been able to do it before. Now they think this might be able to. So we will just have to wait and see if its predictions are accurate or not.

How about you read the article before you start being outraged over your own false assumptions