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

-Terry Pratchett, Guards! Guards!

Ahh. TV shows before everything became political. Just two guys hating each other for very silly reasons completely unconnected to anything on earth.

But it’s not “from each according to his ability”. FOSS is what people feel like contributing. And it’s not “to each according to their need”. It’s take it or leave it, unless someone feels like fulfilling requests.

Traditionally, the slogan meant a duty to work. Contributing what you feel like is just charity.

Capitalism, at its core, is private control of the capital. Copyright law turns code into intellectual property/capital. I’ve read the argument that copyleft requires strong copyrights. That argument implicitly makes copyleft a feature of capitalism. You know how rich people or corporations sometimes donate large sums to get their name on something, EG a hospital wing? That’s not so different from a FOSS license that requires attribution.

artificial intelligence noun

1 : the capability of computer systems or algorithms to imitate intelligent human behavior

also, plural artificial intelligences : a computer, computer system, or set of algorithms having this capability

2 : a branch of computer science dealing with the simulation of intelligent behavior in computers

https://www.merriam-webster.com/dictionary/artificial intelligence

Text explaining why the neural network representation of common features (typically with weighted proportionality to their occurrence) does not meet the definition of a mathematical average. Does it not favor common response patterns?

Hmm. I’m not really sure why anyone would write such a text. There is no “weighted proportionality” (or pathways). Is this a common conception?

You don’t need it to be an average of the real world to be an average. I can calculate as many average values as I want from entirely fictional worlds. It’s still a type of model which favors what it sees often over what it sees rarely. That’s a form of probability embedded, corresponding to a form of average.

I guess you picked up on the fact that transformers output a probability distribution. I don’t think anyone calls those an average, though you could have an average distribution. Come to think of it, before you use that to pick the next token, you usually mess with it a little to make it more or less “creative”. That’s certainly no longer an average.

You can see a neural net as a kind of regression analysis. I don’t think I have ever heard someone calling that a kind of average, though. I’m also skeptical if you can see a transformer as a regression but I don’t know this stuff well enough. When you train on some data more often than on other data, that is not how you would do a regression. Certainly, once you start RLHF training, you have left regression territory for good.

The GPTisms might be because they are overrepresented in the finetuning data. It might also be from the RLHF and/or brought out by the system prompt.

I accidentally clicked reply, sorry.

B) you do know there’s a lot of different definitions of average, right?

I don’t think that any definition applies to this. But I’m no expert on averages. In any case, the training data is not representative of the internet or anything. It’s also not training equally on all data and not only on such text. What you get out is not representative of anything.

A) I’ve not yet seen evidence to the contrary

You should worry more about whether you have seen evidence that supports what you are saying. So, what kind of evidence do you want? A tutorial on coding neural nets? The math? Video or text?

That’s a) not how it works and b) not averaging.

Who exactly creates the image is not the only issue and maybe I gave it too much prominence. Another factor is that the use of copyrighted training data is still being negotiated/litigated in the US. It will help if they tread lightly.

My opinion is that it has to be legal on first amendment grounds, or more generally freedom of expression. Fair use (a US thing) derives from the 1st amendment, though not exclusively. If AI services can’t be used for creating protected speech, like parody, then this severely limits what the average person can express.

What worries me is that the major lawsuits involve Big Tech companies. They have an interest in far-reaching IP laws; just not quite far-reaching enough to cut off their R&D.

Why would averaging lead to repetition of stereotypes?

Anyway, it’s hard to say LLMs output what they do. GPTisms may have to do with the system prompt or they may result from the fine-tuning. Either way, they don’t seem very internet average to me.

You’re allowed to use copyrighted works for lots of reasons. EG satire parody, in which case you can legally publish it and make money.

The problem is that this precise situation is not legally clear. Are you using the service to make the image or is the service making the image on your request?

If the service is making the image and then sending it to you, then that may be a copyright violation.

If the user is making the image while using the service as a tool, it may still be a problem. Whether this turns into a copyright violation depends a lot on what the user/creator does with the image. If they misuse it, the service might be sued for contributory infringement.

Basically, they are playing it safe.

It’s all just weights and matrix multiplication and tokenization

See, none of these is statistics, as such.

Weights is maybe closest but they are supposed to represent the strength of a neural connection. This is originally inspired by neurobiology.

Matrix multiplication is linear algebra and encountered in lots of contexts.

Tokenization is a thing from NLP. It’s not what one would call a statistical method.

So you can see where my advice comes from.

Certainly there is nothing here that implies any kind of averaging going on.

mathematical average of internet dialog

It’s not. Whenever someone talks about how LLMs are just statistics, ignore them unless you know they are experts. One thing that convinces me that ANNs really capture something fundamental about how human minds work is that we share the same tendency to spout confident nonsense.

Gravity, not friction!

Well, maybe they can’t. This clause would probably not hold up in a lot of countries/courts. OTOH it would in others. It might take years of litigation to figure out.

So, if you want to work on this kind of thing, better consult a lawyer first. It will have a chilling effect and that’s something.

US situation: https://www.eff.org/issues/coders/reverse-engineering-faq

The EULA of the CUDA SDK bans reverse engineering output of the SDK to make translation layers (and such compatibility aids in general).

That makes it more legally dangerous and/or harder for devs. It has no effect on anyone not using the SDK.

https://en.wikipedia.org/wiki/Federal_Reserve_Act

https://en.wikipedia.org/wiki/Bank_regulation_in_the_United_States

What I don’t want in charge, is a shadowy cabal of a few rich people only bound to the maximization of their own profit.

I’m not paying extra to remove what little democratic control there is in the existing system.

It cannot be cheaper, other than by avoiding taxes and regulation.

Consider sending money from US Dollar to Euro:

Sane way: An intermediary (IE a bank) handles this. You give them USD and they give the receiver Euros. This involves some service costs and 2 bank transfers.

Because people exchange money in both ways, the banks need not run out of either Euro or USD. In the background there is the currency market, on which the proper exchange rate is haggled out, which takes care of imbalances in cash flow.

Crypto way: You give a crypto exchange (an intermediary) USD and they give you crypto. This already involves 2 transfers and service costs. One of those 2 transfers is a crypto transfer, which is much more expensive (IE uses more resources) than a bank transfer.

This is already more expensive and then you have to do the same thing again to cash out.

And then we are still not done. Say there is an imbalance in that more people transfer money from USD to Euro than vice versa. That means that crypto becomes more expensive in USD and cheaper in Euro. There’s more demand in terms of USD and more supply for Euro, right?.

That creates an arbitrage opportunity. You can exchange USD for Euro, and then buy crypto for Euro to sell for USD. This closes the circle and puts everything back to the initial state. But to do that, we still have to exchange the real currencies. So now the markets bake the cost of exchanging currency into the crypto prices. At a guess, for some currencies (probably not so much Euro/USD), that would have a significant effect. I’m thinking smaller, poorer countries that send many migrant workers, who send money back home. These workers would not only end up paying the insane overhead of the crypto system, but also, still, most of the normal, direct exchange costs (if they relied on crypto).

The point in OP is that “blockchain” was not a new thing. The Merkle Tree was patented in 1979, meaning that it has been free for decades. Most programmers might never have a use for it but they still encounter it every time they use git (which is older than bitcoin).

So, if you’re not aware of this, that’s because it is very technical and nothing to do with cryptocurrencies.