I hope you've all read the Aschenbrenner paper from 2024.

https://situational-awareness....

Never mind Trump's rambling speaking style. He's aware of it and he likes it.

We know that people in the Trump admin have, at minimum, been briefed on the Aschenbrenner paper. I assume some of them have read the whole thing.

The point he's making - that we're on the cusp of ASI, and the USA MUST not get there wildly behind, for example, China, is correct. And that the USA should not be shackled by an international framework that rival nations are going to ignore anyway.

He's directionally correct, even if you think he's too stupid to know what he's agreeing with.

No. I think hollywood has always been subversive and run by foreign pedophiles. For example, look for the interview with Shirley Temple about what they tried doing to her as a _child_,

I think it has produced enough pro-American-MIC films every now and then to stay out of more government trouble.

You usually don't realize (at the time) that the media you watched as a child was subverting you (and your parents desires). And unless you revisit those films a generation later with a critical eye, you may not realize it ever.

But that's how the ratchet effect works. The newer media that is now visibly odious to me is only visibly odious to me because it is targeting the edge of an overton window that has continued moving since my own youth. The leading edge of socially allowable media subversion continues to advance until a historical reset event sets it back somewhat. Or, sometimes, when there is sufficient market rejection.

In the case of hollyweird, the concentration of power has significant drawbacks; destroying that concentration of power will probably be a net benefit. (to be clear, I think It will amplify other problems instead).

In general, I think evil seems to be more effective when it is centralized and powerful, with captured institutions, while maintaining the ability to operate openly, and has de-facto monopoly control over the domain in which it operates, and when most people do not understand what is being done to them.

If Trump had promised to destroy hollywood, I would have voted for him 10x harder.

(And i expect I would be disappointed because he wouldn't actually follow through with it)

Anyway, hopefully, AI gets the job done and finally kills that wretched industry. I look forward to further democratization of movie making.

(fwiw, my knee jerk reaction is to oppose the merger.)

The current generation of these smartglasses devices will fail and disappear.

Let me show my work:

1. women cannot use these smart glasses to take selfies.
2. therefore, women will not wear them.
3. therefore, the only people who wear them will be men
4. anything that men do but which women do not do is probably criminal, but certainly creepy, a red flag, or a cause of the ick
5. therefore, men will be shamed (or arrested) into not wearing them either

QED.

My late wife did undergraduate research in photosystem II where there was quantum effects back in 2002. She did her PhD thesis on proton coupled electron transfer (PCET) in soybean lipoxogenase, then had a long career developing models for Fortran code that did quantum simulation of proteins (she was behind Tagdock in Amber MD). This is nothing new; several biological systems have quantum effects that are central to their mechanism.

I don't think training a model with copyrighted data is any kind of gray zone at all.

Running inference against such a model _might_ be infringing.

But I don't see the legal argument that model training would be.

Think of model training as lossy data compression. You provide an input, it produces a compressed artifact, and it can no longer reproduce the original when you uncompress it. It can produce _something_. It cannot reproduce the original.

On slashdot, we all agree that format shifting copyrighted works should be allowed and unrestricted, right?

If there is applicable case law here about how lossy a "reproduction" can be before copyright has something to say about it, that would be relevant. Do you know of any?

I think you're repeating something that feels emotionally valid but in my experience, isn't factually (or legally) accurate.

I have found AI models to be frustratingly _obedient_ of copyright.

I'll be in a situation where I ask a specific question about what a document says, and the AI repeatedly says the work is copyrighted and it can't just tell me what it says _verbatim_, but it can answer specific questions for me in its own words (while telling me to check the original).

Two examples from my life are procedural questions about what Roberts Rules of Order would require in a given situation, and, what ASD STE-100 says about how to name/word things.

The applicable US law would appear to be USC 17 Sec 106 and 107, which on one hand limits derivative works, but on the other, allows fair use for purposes of teaching, scholarship, or research.

(USC references provided by AI, btw. Which I haven't read)

I used to agree with you, and then oddly enough, about 25-30 years ago, I came across this signature on another regular slashdot posters postings:

"The law, in its majestic equality, forbids the rich as well as the poor to sleep under bridges, to beg in the streets, and to steal bread."

(AI tells me the attribution is "The Red Lily", Anatole France, 1894)

Well, yes, the farther north, the more important DST is, but also, where you line up in your time zone.

This map is pretty insightful but not for the sun rise time: https://ancillary-proxy.atarimworker.io?url=https%3A%2F%2Fwww.washingtonpost.com...

What it does show is that the more north-east and south-west in a time zone you are, the more DST makes daylight more "normal". So all the east coast cities (NY, Philadelphia, Boston) and Chicago, Milwaukee, and St. Louis in central TZ end up with earlier sunrises in the winter with DST/Normal time. If you make DST permanent, two of the big population centers (and voting blocks) in the US are now not seeing daylight until late in the mornings in winter.

Most of the states below Kentucky don't get affected too much, so Houston and LA won't care. But when you annoy easily 1/2 of the US population, this won't last too long...

One of the defining papers in this field is 2013 "Intriguing properties of neural networks" by Szegedy et al. In their own words from the abstract, "we find that deep neural networks learn input-output mappings that are fairly discontinuous to a significant extent"

I'm using the word "continuous" in the same sense as them. (Perhaps it does indeed mean what I think it means...)

In image processing like this article is talking about, the classic example of a harmful response is that your car's camera sees "speed limit 30" sign, but a small sticker it makes the image processor believe it saw a "speed limit 70" sign.

(this is an actual demonstrated attack. It means that pranksters could cripple self driving.)

The thing about these image classifiers is that they're not "continuous". You can make it see a stop sign as a right-of-way sign, or a green light.

My main AGENTS.md has ten lines about the most important coding principles:

The instruction on "meaning" ended up carrying a lot of weight to the AI. It adopted the habit of putting a comment on every single field and function that starts with the word "// Meaning: " and they're honestly, genuinely good ones! Single-line sentences on fields that carry a lot of good weight.

Separately, I have a LEARNINGS.md file which I have the AI auto-update every time it gets course corrected by me. Over the first two weeks there were a lot of course corrections, but now there are only a few a day. The file ended up carrying my senior engineer wisdom, more or less, the kind of things I normally mentor to junior developers on the team over several years. Here's an extract: https://ancillary-proxy.atarimworker.io?url=https%3A%2F%2Fgist.github.com%2Fljw100...

My CS degree had a lot of theorem proofs in it, invariants, that kind of thing. I've always had the habit of aiming to prove my code correct under all possible circumstances. Usually not a formal proof, but using the same skeleton as a formal proof would.

It got me a job on the C# language design team (when I tried to prove an algorithm correct, couldn't, discovered a counter-proof that the runtime had a flaw).

As I mentor junior devs and review their code, I'm always telling them to reason about their invariants better and document them.

Now in the age of AI, I find that invariant-heavy and proof-heavy guidance to the AI ends up getting its work done quicker and higher quality. OpenAI mentioned the same thing in a blog post in February.

Sure, there are many paths to professional success and engineering excellence that don't involve this kind of CS heavy approach. But, there are many that do...

I think a tool that lets one person do the work of 20 will result in 17 people being laid off, as the company triples its rate of work. (I can see triple being feasible and achievable in the software industry, but maybe not more)

Oh, and a "train" is a bit like 100 cars back to back.