he more I learn about neural networks, the more they seem like very convoluted statistics

How so?

That’s where the almost comes in. Unfortunately, there are many traps for the unwary stochastic parrot.

Training a neural net can be seen as a generalized regression analysis. But that’s not where it comes from. Inspiration comes mainly from biology, and also from physics. It’s not a result of developing better statistics. Training algorithms, like Backprop, were developed for the purpose. It’s not something that the pioneers could look up in a stats textbook. This is why the terminology is different. Where the same terms are used, they don’t mean quite the same thing, unfortunately.

Many developments crucial for LLMs have no counterpart in statistics, like fine-tuning, RLHF, or self-attention. Conversely, what you typically want from a regression - such as neatly interpretable parameters with error bars - is conspicuously absent in ANNs.

Any ideas you have formed about LLMs, based on the understanding that they are just statistics, are very likely wrong.

People confabulate all the time.

False memories can also be deliberately created. Here’s a classic: https://www.washington.edu/news/2001/06/11/i-tawt-i-taw-a-bunny-wabbit-at-disneyland-new-evidence-shows-false-memories-can-be-created/

Neural nets, including LLMs, have almost nothing to do with statistics. There are many different methods in Machine Learning. Many of them are applied statistics, but neural nets are not. If you have any ideas about how statistics are at the bottom of LLMs, you are probably thinking about some other ML technique. One that has nothing to do with LLMs.

The noun doesn’t matter after an adjective like ‘multiple.’ Nothing good ever follows ‘multiple.’

-Terry Pratchett, Guards! Guards!

The Russian reliance on terror tactics makes me wonder what lessons they took away from WW2. This is clearly part of a pattern; a military doctrine, that had already been applied during the fighting in Syria, if not earlier.

Not like this is the first time. It’s not even the second time.

The article lies about what’s in the bill. No idea why.

https://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=202320240SB1047

What are they gonna do, send in a fucking swat team to take anything that doesn’t have hardware level DRM?

In a future where this is established, wouldn’t you expect non-compliant hardware to be treated just as drugs or machine guns are treated now?

I think that’s hardly an immediate worry, though. Various services already scan for illegal content or suspicious activity. It wouldn’t take much to get ISPs to snitch on their customers.

It’s steady pressure and it’s only in one direction. Some countries resist more than others. I’m guessing you are not in the EU, because if so, you’d be aware of the “chat control” push.

Even so, it’s not the days of Napster anymore. Think about hardware DRM. It stops no one but you, too, paid to have it developed and built into your devices. Think about Content ID. That’s not going away. It’s only going to be expanded. That frog will be boiled.

Recently, intellectual property has been reframed as being about “consensual use of data”. I think this is proving to be very effective. It’s no longer “piracy” or “theft”, it’s a violation of “consent”. The deepfake issue creates a direct link to sexual aggression. One bill in the US, that ostensibly targets deepfakes, would apply to any movie with a sex scene; making sharing it a federal felony.

Hey, I’m just saying how it’s going. Look at, say, threads here about deepfakes. See all the calls for laws and government action. How can that be enforced?

it would be if internet regulation was practically enforceable for anyone other than commercial businesses operating out in the open.

Well, then I guess we just have to call for more government enforcement.

In the EU, there is certainly more government pressure, instead of just lawsuits between big (or small) players.

I just described what’s going on. The world outside of China or Russia is going slower but the direction is the same.

Borders in cyberspace is the future. There are increased efforts to regulate the internet everywhere. Think copyright, age verification, the GDPR, or even anti-CSAM laws. It’s all about making sure that information is only available to people who are permitted to access it. China is really leading the way here.

We do not agree with China’s regulations, but that only means that we need border controls. Data must be checked for regulatory compliance with local laws.

Private ownership ≠ capitalism.

Right. It’s private ownership of capital; aka the means of production. You’re saying that data should be owned because it can be used productively. That’s exactly capitalism for capitalism’s sake.

This is a typical economically right-wing approach. There is a problem, so you just create a new kind of property and call it done. The magic of the market takes care of it, or something. I don’t understand why one would expect a different result from trying the same thing.

The solution for capitalism is more capitalism? Have you never played monopoly?

I feel this deserves more attention. Not only is the Milky Way named for literal milk; it is named for specifically for human milk.

Because there is no easy way to ban in a democracy. Originally, the term means someone who hangs around in the lobby of congress (or such like) and talks to representatives when they come through. Imagine this is just some ordinary voter who has an important issue on their minds; perhaps someone like Raphael Lemkin. He did that. Non-profit organizations - like Greenpeace - lobby, as well. It’s hard forbidding lobbying without unintended side effects.

Even if you did, it might not get you where you want. Representatives would still have an open ear for major employers in their districts. After all, voters want those jobs. Representatives meet those bosses on many occasions, like charity events. Money and power can be used to get more money and power.

Personal access is only a part of it, anyway. People influence the media and fund political ads. There’s also funding for think tanks and universities. People with money and power (or fame) can do more of that.

Don’t assume this something that just happens behind closed doors out of the public eye. For example, you may have noticed the recent kerfuffle between actress Scarlet Johansson and OpenAI. OAI allegedly hired a voice actress that sounded too similar to ScarJo. This community here seems to have largely sided with ScarJo. Which means that they want famous people to receive a rent for lending out their voices; a rent which will be ultimately paid by consumers. And if you have a similar voice? Tough.

This is exactly something that many of these AI lobbyists are paid to achieve. They are supposed to get money for the rich people who pay them; preferably without the rich people having to do work.

That wouldn’t make any sense.

Lagerfeld was right.