No, LCOE is an aggregated sum of all the cash flows, with the proper discount rates applied based on when that cash flow happens, complete with the cost of borrowing (that is, interest) and the changes in prices (that is, inflation). The rates charged to the ratepayers (approved by state PUCs) are going to go up over time, with inflation, but the effect of that on the overall economics will also be blunted by the time value of money and the interest paid on the up-front costs in the meantime.

When you have to pay up front for the construction of a power plant, you have to pay interest on those borrowed funds for the entire life cycle, so that steadily increasing prices over time is part of the overall cost modeling.

Even if you take money out of the equation, people need the productive output of other people to survive.

A man alone on a desert island cannot retire. As soon as he is unable to provide for himself, he dies. Yes, he can accumulate certain “savings,” but much of what is needed to survive cannot be banked and used later. Food storage is limited, and any method of long term food storage tends to require additional processing to be edible, so there will always need to be some kind of just-in-time cooking process to keep people fed. Same with shelter, where maintenance needs will always be there, or health care, where real time treatment will always need to be done.

In a society with a shrinking population, there will be an unrelenting pressure to simply stop supporting those who are not productive. And those who are productive will selfishly shape that society to cover their own needs first.

That’s not just capitalism, it’s every economic system. Taking care of our elderly and our disabled is a luxury of a prosperous society. If the ratio goes out of wack, the willingness to continue supporting that luxury may not always be there.

we’ve been fed this narrative that overpopulation is eventually going to destroy the world

It’s always been wrong, and some of us have been arguing against that kind of neo-Mathusian worldview this entire time.

Note that the same view also leads to the incorrect conclusion that population shrinkage will be good for resource management, pollution, etc. If one believes that a large and growing population will deplete the world’s resources and destroy the environment, one might conclude that a shrinking population will help conserve the world’s resources and preserve the environment.

But look at how things actually play out. The countries with the shrinking populations are still increasing their resource consumption, and the slowdown in population growth hasn’t slowed down resource depletion in large part because humans don’t all use the same amount of resources. If the population of India shrinks to the size of the population of the United States, but then increases its greenhouse emissions to match that of the United States, that would be bad for the environment despite the population reduction.

A shrinking population isn’t really a problem in itself, but an aging population is. That’s the concern about birth rates, is the worry that unproductive old people will have their lives cut short rather than enjoying a reasonable retirement.

apparently then it was around 20% to 25% as well

No, the unemployment rate was around 20-25% under the traditional definition. It’s currently 4.2% under that definition.

If you want to use this LISEP definition, fine, but recognize that it’s been above 30% for most of its existence, and has only been under 25% since COVID. Basically, if you go by the LISEP definition then you’re saying that the job market after COVID has been better than it has ever been before.

When the definition of unemployed is changed to exclude the majority of working age people without jobs then it is no longer a helpful statistic.

U-3 has used the same definition of unemployed since 1940.

Whatever metric you want to use, you should look at that number and how it changes over time, to get a sense of trend lines. LISEP says the “true” unemployment rate is currently 24.3% in May 2025, which is basically the lowest it’s ever been.

Since the metric was created in 1994, the first time that it dipped below 25% was briefly in the late 2010’s, right before COVID, and then has been under 25% since September 2021.

Under this alternative metric of unemployment, the unemployment rate is currently one of the lowest in history.

My problem with nuclear is both the high cost and, somewhat counterintuitively, the very long life cycles to spread that high cost. The economics only make sense if the plant runs for 75 years, which represents an opportunity cost of displacing whatever might be available in 25 or 50 years.

A solar plant planned in 2025 might be online in 2027, and decommissioned in 2047, replaced with whatever technology/economics are available then. But a new nuclear reactor bakes in the costs for 80+ years, to be paid by ratepayers who haven’t been born yet.

So if in 2050 a 2030-constructed nuclear plant is still imposing costs of $66/MWh on ratepayers, to finance the interest and construction costs from 25 years earlier, will that be competitive with the state of solar/wind/batteries/hydrothermal at that time? Given the past trend lines, it seems economically foolish to lock in today’s prices for the next 80 years.

This paper lays out the cost projections that one could expect with the lessons learned from Vogtle Units 3 & 4, with the tax credits and government guarantees available as of 2024:

https://web.mit.edu/kshirvan/www/research/ANP201 TR CANES.pdf

Ok, current projections are still for the next two AP1000s at Vogtle to be something like $10 billion. That’s just not cost competitive with solar/wind. And it’s also not very realistic to assume that there won’t be cost overruns on the next one, either. Complex engineering projects tend to run over.

Also where did you see they did amortization of solar?

I’m just familiar with Lazard’s LCOE methodology. The linked paper talks about LCOE, so that’s just how that particular cost analysis works.

Vogtle added 2 AP1000 reactors for $35 billion. Future deployments might be cheaper, but there’s a long way to go before it can compete with pretty much any other type of power generation.

But the other misleading part is they looked at 20 years which is close to the life cycle for solar/batteries and not even half the life of nuclear

I think Lazard’s LCOE methodology looks at the entire life cycle of the power plant, specific to that power plant. So they amortize solar startup/decommissioning costs across the 20 year life cycle of solar, but when calculating LCOE for nuclear, they spread the costs across the 80 year life cycle of a nuclear plant.

Nuclear is just really, really expensive. Even if plants required no operating costs, the up front costs are so high that it represents a significant portion of the overall operating costs for any given year.

The Vogtle debacle in Georgia cost $35 billion to add 2 MW 2GW (edit to fix error) of capacity. They’re now projecting that over the entire 75 year lifespan the cost of the electricity will come out to be about $0.17 to $0.18 per kilowatt hour.

Archive.org was distributing the books themselves to users. Anthropic argued (and the authors suing them weren’t able to show otherwise) that their software prevents users from actually retrieving books out of the LLM, and that it only will produce snippets of text from copyrighted works. And producing snippets in the context of something else is fair use, like commentary or criticism.

just spitting the information back out, without paying the copyright source

The court made its ruling under the factual assumption that it isn’t possible for a user to retrieve copyrighted text from that LLM, and explained that if a copyright holder does develop evidence that it is possible to get entire significant chunks of their copyrighted text out of that LLM, then they’d be able to sue then under those facts and that evidence.

It relies heavily on the analogy to Google Books, which scans in entire copyrighted books to build the database, but where users of the service simply cannot retrieve more than a few snippets from any given book. That way, Google cannot be said to be redistributing entire books to its users without the publisher’s permission.

What does an LLM application (or training processes associated with an LLM application) have to do with the concept of learning?

No, you’re framing the issue incorrectly.

The law concerns itself with copying. When humans learn, they inevitably copy things. They may memorize portions of copyrighted material, and then retrieve those memories in doing something new with them, or just by recreating it.

If the argument is that the mere act of copying for training an LLM is illegal copying, then what would we say about the use of copyrighted text for teaching children? They will memorize portions of what they read. They will later write some of them down. And if there is a person who memorizes an entire poem (or song) and then writes it down for someone else, that’s actually a copyright violation. But if they memorize that poem or song and reuse it in creating something new and different, but with links and connections to that previous copyrighted work, then that kind of copying and processing is generally allowed.

The judge here is analyzing what exact types of copying are permitted under the law, and for that, the copyright holders’ argument would sweep too broadly and prohibit all sorts of methods that humans use to learn.

specifically about the training itself.

It’s two issues being ruled on.

Yes, as you mention, the act of training an LLM was ruled to be fair use, assuming that the digital training data was legally obtained.

The other part of the ruling, which I think is really, really important for everyone, not just AI/LLM companies or developers, is that it is legal to buy printed books and digitize them into a central library with indexed metadata. Anthropic has to go to trial on the pirated books they just downloaded from the internet, but has fully won the portion of the case about the physical books they bought and digitized.

No. The court made its ruling with the explicit understanding that the software was configured not to recite more than a few snippets from any copyrighted work, and would never produce an entire copyrighted work (or even a significant portion of a copyrighted work) in its output.

And the judge specifically reserved that question, saying if the authors could develop evidence that it was possible for a user to retrieve significant copyrighted material out of the LLM, they’d have a different case and would be able to sue under those facts.

The law says this is ok now, right?

No.

The judge accepted the fact that Anthropic prevents users from obtaining the underlying copyrighted text through interaction with its LLM, and that there are safeguards in the software that prevent a user from being able to get an entire copyrighted work out of that LLM. It discusses the Google Books arrangement, where the books are scanned in the entirety, but where a user searching in Google Books can’t actually retrieve more than a few snippets from any given book.

Anthropic get to keep the copy of the entire book. It doesn’t get to transmit the contents of that book to someone else, even through the LLM service.

The judge also explicitly stated that if the authors can put together evidence that it is possible for a user to retrieve their entire copyrighted work out of the LLM, they’d have a different case and could sue over it at that time.

Does buying the book give you license to digitise it?

Does owning a digital copy of the book give you license to convert it into another format and copy it into a database?

Yes. That’s what the court ruled here. If you legally obtain a printed copy of a book you are free to digitize it or archive it for yourself. And you’re allowed to keep that digital copy, analyze and index it and search it, in your personal library.

Anthropic’s practice of buying physical books, removing the bindings, scanning the pages, and digitizing the content while destroying the physical book was found to be legal, so long as Anthropic didn’t distribute that library outside of its own company.

The court’s ruling explicitly depended on the fact that Anthropic does not allow users to retrieve significant chunks of copyrighted text. It used the entire copyrighted work to train the weights of the LLMs, but is configured not to actually copy those works out to the public user. The ruling says that if the copyright holders later develop evidence that it is possible to retrieve entire copyrighted works, or significant portions of a work, then they will have the right sue over those facts.

But the facts before the court were that Anthropic’s LLMs have safeguards against distributing copies of identifiable copyrighted works to its users.

It took me a few days to get the time to read the actual court ruling but here’s the basics of what it ruled (and what it didn’t rule on):

• It’s legal to scan physical books you already own and keep a digital library of those scanned books, even if the copyright holder didn’t give permission. And even if you bought the books used, for very cheap, in bulk.
• It’s legal to keep all the book data in an internal database for use within the company, as a central library of works accessible only within the company.
• It’s legal to prepare those digital copies for potential use as training material for LLMs, including recognizing the text, performing cleanup on scanning/recognition errors, categorizing and cataloguing them to make editorial decisions on which works to include in which training sets, tokenizing them for the actual LLM technology, etc. This remains legal even for the copies that are excluded from training for whatever reason, as the entire bulk process may involve text that ends up not being used, but the process itself is fair use.
• It’s legal to use that book text to create large language models that power services that are commercially sold to the public, as long as there are safeguards that prevent the LLMs from publishing large portions of a single copyrighted work without the copyright holder’s permission.
• It’s illegal to download unauthorized copies of copyrighted books from the internet, without the copyright holder’s permission.

Here’s what it didn’t rule on:

• Is it legal to distribute large chunks of copyrighted text through one of these LLMs, such as when a user asks a chatbot to recite an entire copyrighted work that is in its training set? (The opinion suggests that it probably isn’t legal, and relies heavily on the dividing line of how Google Books does it, by scanning and analyzing an entire copyrighted work but blocking users from retrieving more than a few snippets from those works).
• Is it legal to give anyone outside the company access to the digitized central library assembled by the company from printed copies?
• Is it legal to crawl publicly available digital data to build a library from text already digitized by someone else? (The answer may matter depending on whether there is an authorized method for obtaining that data, or whether the copyright holder refuses to license that copying).

So it’s a pretty important ruling, in my opinion. It’s a clear green light to the idea of digitizing and archiving copyrighted works without the copyright holder’s permission, as long as you first own a legal copy in the first place. And it’s a green light to using copyrighted works for training AI models, as long as you compiled that database of copyrighted works in a legal way.