They do especially good in the cold down to -30C.

Well,
I never really got the naming schemes of Apple OSes as well.
Tiger, Panter, Cogar - ok.
The Mogave as desert, okay.

In general I do not know what my machine is running, I have to look into the system, and I prefer the version number.

Regarding LLMs, I would use philosophers or science persons and would pick a figure which personalizes the strength of the LLM. And then add the quarter of the year when it is released. Like Pascal 1/2026 for a math LLM or Einstein 2/2026 for a physics one and a Renaissance 3/2026 for and al purpose one.

Perhaps in the US.

Most certainly not in Europe.

I reiterate over the prompt. I do not hve to edit the result.

And actually: I doubt there ever was a court case about the copyright of the AI output.

The court cases I am aware about, are if the AI / LLM itself has enough personal rights (or corporate rights) to hold any copyright in his name.

So as simple example: ChatGPT itself - the AI - can not have the copyright about the result/output of one of my prompts. Neither can have the owning company. But I have.

And as I do use it from outside of the US, I certainly have the "copyright", regardless what a future or current US court thinks about that.

ChatGPT was just an example, I do not use it and do not know if there is some "fine print" that would be able to steal my copyright from me.

It does not matter if it is correct.
What matters is if it clear.

"BigDecimals" is not clear. So?

The datatype is BigDecimal - without an "s".

You can not simply add an "s" like you did, to make it a plural. In principal it has no plural, so more correct would have been, if I had not used a plural but simply the singular.

They do nor dodge the blades, they fly around the wind turbines several 100 meters.

An estimate by cat haters.

You do not have enough cats to do that.

I used to have 5 cats, and over 5 years, they killed a single bird, which probably was sick or simply had bad luck.

The actual trick question is: how many birds do live in the US? Does it even reach a billion or 4 billion?

You have like 450 million people. How many cats do you have? How many birds would statistically each of them need to kill to get to 4bn killed birds in total per year.

The number simply makes no sense.

Of course. I was just speculating if they left a plug behind, erm socket.
After all the ability to shut down random stuff, and have everything in the command interface to do so: is already pretty brilliant.

Why do you consider them expensive?
You can train one on your laptop for a few 100 dollars cost of electricity.

Expensive might have been the recent 30 years of research: and that is already paid for.

They could have such a thing in theory, but in practice they don't have it.

The point is: for selection you need some genes, that get mendeled or darwined away ...
And/or others that randomly pop up and get enforced in the surviving population.

And that is not the case.

What is much more likely to go on, is that young birds simply learn from the older ones.

Says the Guy who knows nothing about AI.

The trend is going to multi model models. As in you have a few hundred small models interacting with each other (models, not agents).

At the moment we are at the level of Large Language Models. So the thing they do is in the name: they work on Language.

The next step is to work on Thinking. It is only a matter of a few years - perhaps three - and we have thinking machines. And that has absolutely nothing to do with RAM, or the lack thereof, but SOFTWARE.

Software as in mimicking thought processes - as far as we understand them. We build thinking machines already, in a certain sense they use a bunch of LLMs as "hallucination machines", to give them random ideas to form a path from a prompt mentioning a goal, to a solution.

https://www.youtube.com/watch?...

I have no idea what is going on here on /.
It seems everyone is anti AI ...
And no one has any clue about it the slightest.

Perhaps the video above is to difficult, and you should start here with the basics:
https://www.youtube.com/watch?...

It is basically a very good video that summarizes the evolution of artificial neural networks into LLMs, in under one hour. With lots of code examples, if you are not scared about code.

I think you AI haters have some stupid ideas about what is going on.

The RAM is for data centers that host AI software. Selling the capacity to ordinary companies that use AI in their business processes.

For example: I host 25 agents on rented hardware in a data center.

As long as there are ordinary companies that reform their IT from "CRMs" to agent driven solutions: those new data centers will have customers.

And AI in "ordinary companies" like a vacuum machine seller, or a solar company: is not going away.

There is no objectively imaginable reason that data centers will go bankrupt, unless they are mismanaged (like IONOS)

We don't need bigger models, at this point. What we need is multi-dimensional decomposition, problem space transforms, and the ability for AI to use external tools (such as SQLite, memcached, etc) so that it can externalise static data that it needs to not corrupt accidentally but still keep in easy access.

If we had that, most of the things "bigger models" will do will actually end up being done better, quicker, with fewer compute resources.

SK Hynix is spending $38 billion to build two factories: one for RAM, one for NAND. They expect to start clean room operations near the middle of 2029 at the earliest.

Building the factories isn't the issue. It's all the equipment needed to make/print the wafers, the equipment needed to keep things running, and perhaps most importantly, the people needed to run the factory. None of these can be found on Craisglist.

...to make new factories.

Like imagine if it were possible to create new semiconductor factories, making chips en masse, -- you could perhaps do it in a BIIIG state with a lot of land. You could have a factory with like 100 million square feet. Wouldn't that be something?

Maybe we should have more factories.

If only there were a price incentive to do so.

I guess you want to argue about what the term "AI" means.

A) you should have studied it in university, then your term "Cognitive Systems" would be correct
B) you should adapt what it means now

Now, it means (amoung other things) I can write a query in natural language to a data storage of unstructured date.
And "the engine" figures out what I meant and how to use said data, to produce an answer.

It is not rocket science.