At present, no. I've done a number of experiments with LLMs' capabilities with generating fiction, and while they are impressive for a beginner writer -- because fo the lack of spelling and grammar mistakes, they are nowhere near being able to write competent fiction.

This is because they don't model reader or character minds, they're based on word probabilities, like a predictive text keyboard. The engineers can compensate for for this to a surprising degree by feeding it data to recognize specific situations (e.g. the car wash is 100 feet from my driveway; should I drive or walk?). But this is turd-polishing.

AI technology practice isn't foundational. Critical thinking is. The closer AIs come to being able to do something that looks like them doing our thinking for us, the more capable we have to be at thinking without them. A human who can't outthink an AI adds nothing to an AI-human partnership.

This proposed school is a typical scheme by people who think because they have been educated, they understand how the education works. This is like thinking because you eat, you know how to cook. Project work in education is nothing new; it goes back well over a century. And in real life, you may get a STEM degree, but your real education in engineering comes from real life work. But that doesn't mean classes in calculus and physics don't do anything for you.

Or English classes, for that matter. Nobody doubts the value of project work in education, particularly *androgogy* -- the education of adults. But for *pedagogy* you have to establish foundational skills as the student matures intellectually and socially. Entering the high school years, a typical student has had *no* training in critical thinking skills. To develop critical thinking skills in an area, you need both general skills (epistemologicla literacy: research, location of orignial sources, dealing with conflicting evidence) and domain specific training in that area. In other words, *liberal arts* training is foundational in an AI-saturated world. "Liberal Arts" -- from *artes liberales*: literally the skills necessary to be a free person.

But I think these people have at least got the problem right: as AI drives the cost of elaborate projects down, we all have more projects in our future. Big, elaborate, faultlessly plausible-looking projects which may or may not have actual value.

Where they are completely wrong is the solution, which is to organize education around practicing using AI to make impressive projects. In a word of AI-enamored dunces this will put you at the head of a very sorry class of ignoramuses. The answer is to build fundamental cognitive and intellectual skils at every stage of a student's development. Project work is surely part of that, but it's just a technique, not a solution.

In a nutshell, the academy is training students to be the next step down the evolutionary scale from code monkeys. More like the pigeons B.F. Skinner trained in WW2 to peck at a screen, in an attempt to create a primitive guided missile without computers. They want to create "main characters"; and they'll probably create a few. There are always a few natural autodidacts in any moderately large group. But what they are set up is to produce a bunch of fragile, economically privileged narcissists trained to cover their lack of education with impressive-looking AI slop.

...Modern ejector seats cause spinal injuries from which full recovery is "unusual". Smashing the spines of pilots might not be the most effective way to boost morale.

$22,000 per hour. The F35 will be nearer $42,000 per hour. These are under-estimates, as they do not include price hikes, crashes that close businesses, crashing into businesses, crashing into heavily-populated sports centres, etc.

Yeah, it’s easy to think that making a biological weapon is as easy as just following a series of steps, but it’s not. It’s going to require labs and source materials that are going to be hard to get without somebody noticing. State-sponsored groups already have access to these, and you better believe they already have at least looked at weapon-building scenarios or small-scale prototypes. Isolated actors are going to have a much harder time, even if they have PhDs.

It's a way of reframing sloppy practices as a signal to your investors that your software has become powerful. Most of the horror stories about AI showing signs of becoming hyperintelligent are coming from the companies themselves, which should tell us something.

While the energy source of wind and solar are free, building and maintaining the plants is not free.

If all they were building were a single 100MW data center, sure: renewables would be cheaper to build. But they evidently are planning a major campus that will consume most of the plant's 615 MW output over the next 25 years.

A solar installation, in a favorable location, capable of supplying 600MW around the clock (with battery backup) would have to be roughly 1800MW in capacity. It would be among the largest inthe world, on the order of ten thousand acres in size at a build cost of maybe 2 billion. The battery backup system to ensure 99.9% uptime would be 9x the size of the largest li-ion grid storage system ever built, and set you back on the order of 4-5 billion dollars.

While it's probably cheaper to go renewable than build a *new* nuclear plant, if you can reactivate and one for just two billion that looks like a bargain, if you have a use for all that power. Inability to save money by load following is the financial Achilles' heel of this generation of reactors, but if you have a guaranteed customer for most of your output, years in advance, that's as close to an ideal economic case for them as anything could be.

Sort of. It’s clear that Tristan and Levant were working on NS and had generated a preliminary proof that was still being verified. They were taking their time to cleanup the proofs so that they could be presented elegantly, but then OpenAI gained access to their unpublished work, evidenced by the wording of the prompt they claimed to have used, and rushed to scoop them. This kind of shit happens all the time in academia. It’s rather unsurprising that it would also happen between OpenAI and Anthropic.

Which in itself is appropriate (most employees of companies have a responsibility to protect trade secrets from competitors), but the problem here is they wanted to take credit for getting to a solution faster than their competitor, which they did using publicly non-disclosed information.

And because OpenAI is desperate to show that their models can generate proofs to hard problems, this scenario is highly likely. They were augmenting their training data with examples of partial proofs and “Oh look, there is a nice draft of a paper that someone was editing with Codex”

They also heard that someone at Anthropic was working on this, so they decided that it was imperative they publish first.

If you read Tristan’s actual statement, which someone posted a link to below, the reason he is suspicious is because the details are of the approach, including the specific wording used in the prompt, were non-obvious. That and the timing of when the work supposedly started circumstantially points to theft of Tristan and Levant’s work. Tristan does not actually accuse of OpenAI of theft because he doesn’t have any proof, but the sequence of events is definitely suspicious.

There is also the issue of the pressure tactics: respond to a meeting invite the same day, respond to a meeting invite on Sunday of Labor Day weekend, release your proof so that we can follow up with ours the next day. They clearly were rushing their result because they wanted to scoop anything that Anthropic may have been working on. Meanwhile, Tristan is more interested in the academic discourse, but he can no longer release the result he wanted to release, because writing good proofs takes time and OpenAI didn’t want to give him that time.

Sorry, uh what? Bohr’s model is not useful for anything beyond hydrogen. That’s why high school chemistry classes only teach it as the first step in the historical development of atomic orbital theory.

ToS is the strongest argument, but the distillers are not parties to the ToS. They get their data from data brokers. It is possible that data brokers are violating the ToS, but it would be hard to write ToS that precluded running queries for third parties without creating problems for consultancies and other businesses. Even presuming the ToS could be written to preclude the data brokers doing that, it doesn't affect the resulting model.

But the general shape of the argument brings us right back to unclean hands: we worked hard on this model and it's not fair for you to profit off our work in a way that doesn't have our permission.

I think the fair-minded position is to see what people think when the documentary comes out. You're essentially arguing a negative here -- that there *can't* be anything of value that hasn't been said yet.

Also, I don't think saying something *new* is necessarily critical. Sometimes saying something obvious but in an interesting way is worthwhile.

In this case, Holmes gave access to the filmmaker. Obviously she has an agenda. If the filmmaker is smart, he has an agenda that's different from hers. If he knows his business he'll find something interesting to show you from that conflict.

Now looking at the trailer -- holy shit that woman gives off batshit crazy vibes. That's new to me. I expected her to be slick, persuasive, like Saruman in Lord of the Rings: someone. you'd need real strength of mind to resist being persuaded by. If I'd just handed someone like that my business card, I'd get it back on some pretext then head as fast as I could for the door.

It doesn't make it *right*, but it does make claiming it is *wrong* inconsistent with their own behavior. This could prevent the US companies from suing the Chinese companies seeking an injunction (due to the "unclean hands" doctrine), and probably blocks them from seeking monetary damages in most US jurisdictions.

And suing may undermine the US companies own intellectual property claims by exposing their shaky foundations. An AI model isn't *expression*, so it can't be copyrighted. Insofar as the service allows the underlying model to be deduced through regular usage, trade secret protections don't apply because that's *reverse engineering*, which trade secrets don't prevent.

This leaves violations of terms of service. But setting aside the dubious enforceability of anti-reverse engineering provisions, the Chinese companies may not even be parties to the ToS agreement if they are obtaining the model data through a network of contractors and shell companies.With only moderate paranoia, they can effectively shield themselves from some kind of US tort claim.

Which leaves them with the model they've created from the US company's model, but which the US company has no IP claim upon. If I download a DeepSeek model that's been (hypothetically speaking) trained on Claude, Anthropic might not like that, but what can they do about it?

It's a strange situation. US investors are spending cumulatively on over half a trillion dollars a year in the hope of owning a breakthrough frontier model that is the end of the economic world as we know it. But the essence of the model might not be intellectual property at all.