It's trained on moving around dust2, so as long as the previous frame was a view of dust2, the next frame is very likely to be a plausible subsequent view of dust2. In some sense, this encodes a map; but it's not what most people think of when they think about maps.
I'd be interested to see what happens if you look down at your feet for a while, then back up. If the ground looks the same everywhere, do you come up in a random place?
It probably depends on what you see. As long as you have a broad view over a part of the map, you should stay in that region, but I guess that if you look at a mono-color wall, you probably find yourself in a very different part of the map when you look around yourself again.
But I am just guessing, and I haven't tried it yet.
The difference between JVM, CLR and C in regards to parallel and concurrent code is that they are built for those kind of workloads, and have a memory model proper, hence not needing a GIL.
I think they would have to here, to support native modules. Jython (and I believe IronPython, but don't quote me) does not support native CPython modules. CPython modules explicitly control the GIL, so if they are supported (as they are here), you can't really leave the GIL out without exposing potential thread safety issues.
CPython does not have a GIL Global Interpreter Lock GC Garbage Collection phase with --gil-disabled. GraalVM does have a GIL, like CPython without --gil-disabled.
How CPython accomplished nogil in their - the original and reference - fork is described in the topical linked PEP 703.
It's possible to have a language that doesn't have a GIL, which you implement Python in, but that Python implementation then has a GIL.
The point being that you can't say things like: Jython is written in Java so it doesn't have a GIL. CPython is written in C so doesn't have a GIL. And so on.
I wouldn't call that an evaluation. They are expressing subjective opinions and feelings, text summarization is an active area of research, there are many benchmark datasets and evaluation measures that make progress quantifiable. Which makes rants like this seem rather pointless and uninformed.
Also I don't think you can use NIM packages in production without a subscription, and I wasn't able to find the cost without signing up. Also NIM package for Mistral Nemo is not yet available anyways.
It wasn't that OpenAI was open as in "open source" but rather that its stated mission was to research AI such that all could benefit from it (open), as well as to ensure that it could not be controlled by any one player, rather than to develop commercial products to sell and make a return on (closed).
There's been a no-GIL Python for about a decade, and it's still OSS on BitBucket somewhere with a PSF license (I used it for quite a while), but at the time, the community didn't want to wrestle with some of the issues, like, do you want to forego atomicity for list appends, or do you want to slow them down (Skython took the former route)?
I think the idea is that if they have the same chemical composition this is good evidence that they formed from the same primordial gas cloud. If they just happened to be passing by each other, there would be no reason for the composition to be so similar.
