Correct, which is why before I had said
I think OP is making a joke about python’s GIL, which makes it so even if you are explicitly multi threading, only one thread is ever running at a time, which can defeat the point in some circumstances.
If what you said were true, wouldn’t it make a lot more sense for OP to be making a joke about how even if the source includes multi threading, all his extra cores are wasted? And make your original comment suggesting a coding issue instead of a language issue pretty misleading?
But what you said is not correct. I just did a dumb little test
import threading
import time
def task(name):
time.sleep(600)
t1 = threading.Thread(target=task, args=("1",))
t2 = threading.Thread(target=task, args=("2",))
t3 = threading.Thread(target=task, args=("3",))
t1.start()
t2.start()
t3.start()
And then ps -efT | grep python and sure enough that python process has 4 threads. If you want to be even more certain of it you can strace -e clone,clone3 python ./threadtest.py and see that it is making clone3 syscalls.
I think OP is making a joke about python’s GIL, which makes it so even if you are explicitly multi threading, only one thread is ever running at a time, which can defeat the point in some circumstances.
One note on “sick” being slang for “good”: that particular slang started in the 80s, and some of the younger generation consider it to be old person slang.
I’d say it’s not just misleading but incorrect if it says “integer” but it’s actually floats.
I think to some extent it’s a matter of scale, though. If I advertise something as a calculator capable of doing all math, and it can only do one problem, it is so drastically far away from its intended purpose that the meaning kinda breaks down. I don’t think it would be wrong to say “it malfunctions in 99.999999% of use cases” but it would be easier to say that it just doesn’t work.
Continuing (and torturing) that analogy, if we did the disgusting work of precomputing all 2 number math problems for integers from -1,000,000 to 1,000,000 and I think you could say you had a (really shitty and slow) calculator, which “malfunctions” for numbers outside that range if you don’t specify the limitation ahead of time. Not crazy different from software which has issues with max_int or small buffers.
If it were the case that there had only been one case of a hallucination with LLMs, I think we could pretty safely call that a malfunction (and we wouldn’t be having this conversation). If it happens 0.000001% of the time, I think we could still call it a malfunction and that it performs better than a lot of software. 99.999% of the time, it’d be better to say that it just doesn’t work. I don’t think there is, or even needs to be, some unified understanding of where the line is between them.
Really my point is there are enough things to criticize about LLMs and people’s use of them, this seems like a really silly one to try and push.
We’re talking about the meaning of “malfunction” here, we don’t need to overthink it and construct a rigorous proof or anything. The creator of the thing can decide what the thing they’re creating is supposed to do. You can say
hey, it did X, was that supposed to happen?
no, it was not supposed to do that, that’s a malfunction.
We don’t need to go to
Actually you never sufficiently defined its function to cover all cases in an objective manner, so ACTUALLY it’s not a malfunction!
Whatever, it still wasn’t supposed to do that
The purpose of an LLM, at a fundamental level, is to approximate text it was trained on.
I’d argue that’s what an LLM is, not its purpose. Continuing the car analogy, that’s like saying a car’s purpose is to burn gasoline to spin its wheels. That’s what a car does, the purpose of my car is to get me from place to place. The purpose of my friend’s car is to look cool and go fast. The purpose of my uncle’s car is to carry lumber.
I think we more or less agree on the fundamentals and it’s just differences between whether they are referring to a malfunction in the system they are trying to create, in which an LLM is a key tool/component, or a malfunction in the LLM itself. At the end of the day, I think we can all agree that it did a thing they didn’t want it to do, and that an LLM by itself may not be the correct tool for the job.
Where I don’t think your argument fits is that it could be applied to things LLMs can currently do. If I have an insufficiently trained model which produces a word salad to every prompt, one could say “that’s not a malfunction, it’s still applying weights.”
The malfunction is in having a system that produces useful results. An LLM is just the means for achieving that result, and you could argue it’s the wrong tool for the job and that’s fine. If I put gasoline in my diesel car and the engine dies, I can still say the car is malfunctioning. It’s my fault, and the engine wasn’t ever supposed to have gas in it, but the car is now “failing to function in a normal or satisfactory manner,” the definition of malfunction.
It implies that, under the hood, the LLM is “malfunctioning”. It is not - it’s doing what it is supposed to do, to chain tokens through weighted probabilities.
I don’t really agree with that argument. By that logic, there’s really no such thing as a software bug, since the software is always doing what it’s supposed to be doing: giving predefined instructions to a processor that performs some action. It’s “supposed to” provide a useful response to prompts, anything other than is it not what it should be and could be fairly called a malfunction.
Haven’t digital price tags been used for decades? I’m sure these will be more high tech, but I remember ones like this at least 20 years ago
Yeah, I just did a quick test in Python to do a tcp connection to “0.0.0.0” and it made a loopback connection, instead of returning an error as I would have expected.
Looking completely realistic and being able to discern between real and fake are competing goals. If you can discern the difference, then it does not look completely realistic.
I think what they’re alluding to is generative adversarial networks https://en.m.wikipedia.org/wiki/Generative_adversarial_network where creating a better discriminator that can detect a good image from bad is how you get a better image.
That doesn’t mean it’s a timezone
The title partially answers this.
https://www.timeanddate.com/time/gmt-utc-time.html
GMT is a time zone officially used in some European and African countries. The time can be displayed using both the 24-hour format (0 - 24) or the 12-hour format (1 - 12 am/pm).
UTC is not a time zone, but a time standard that is the basis for civil time and time zones worldwide. This means that no country or territory officially uses UTC as a local time.
I think it’s more equivalent to someone making a meme of a standup routine and changing text in order to make fun of something else. The original was a joke about general data sanitization circa 2007, this one is about the dangers of using unfiltered, unreviewed content for AI training.
They give credit bottom right.
Stealing is a strong word considering it gives credit in the bottom right
I haven’t heard of that being what threading is, but that threading is about shared resourcing and memory space and not any special relationship with the scheduler.
Per the wiki:
https://en.m.wikipedia.org/wiki/Thread_(computing)
I also think you might be misunderstanding the relationship between concurrency and parallelism; they are not mutually exclusive. Something can be concurrent through parallelism, as the wiki page has (emphasis mine):
https://en.m.wikipedia.org/wiki/Concurrency_(computer_science)