cauch

I'm not the one downvoting. Several persons downvoted because your argument is non-sensical, because you failed to answer basic question and because you keep making mistakes showing that you have no idea what you are talking about or not being intellectually honest.

I also don't care about convincing you. Simply, it is nice that when someone says something totally stupid, other people stops the non-sense to be spread.

And indeed, conveniently for you as you were unable to provide basic evidence of your claim, end of communication.

> it can easily move to felony with actual punishment also highly dependent on specifics of a given case

When it involves weapons, evidence tampering or higher crime, which is clearly not the case here.

> Had she not been in US illegally none of this would have transpired including this ridiculous conversation.

What are you talking about? Who was illegally in US? I thought we were talking about Renee Good, who was a US citizen, was never a migrant (even legal), and dropped her son 7 minutes ago and was on her way home.

> Blame may be shared

Which is quite a move from "the onus is on you".

> but it really is on me to assess a risk of any given moment

Yes. And the situation we are talking about should clearly not be a situation that should be assessed as "life threatening". By your own admission, she put herself in a minor offense, not something that should be life-threatening. And the fact that the ICE agents carried guns does not justify that one should consider that any interaction with them means that they are putting themselves in life threatening situation.

> I admit that it must be nice thinking everyone else is responsible for me

Well, you are litterally the one here saying that the ICE agent should think everyone else is responsible for them.

No one else does that. I fully agree that people share some responsibilities in the situation they put themselves into. Where we disagree is when you are saying "the onus is on her". No, the onus is not on her: she put herself in a situation that should NOT be something that should be assessed as overly dangerous.

> You make me sound smarter than I am, but, really, you are just misunderstanding the argument ( not sure if on purpose or not ).

Your argument makes no sense at all. Your argument was also quite downvoted. Surely not because of a woke conspiracy, probably more because indeed your argument makes no sense. Maybe you should consider that maybe it is the case?

> You know what. I am all ears. I may simply be wrong. Present your evidence of the case as you see it.

I asked you first. My FIRST COMMENT: "What do you mean? For what I know, she was at the wrong place at the wrong time, did not do anything voluntarily illegal, and was in a situation where everyone should agree would never have had to degenerate into a life-threatening situation."

You never answered.

If you want the discussion to progress, first provide your answer first. I asked you three time to answer on this point.

edit: in another comment, YOU say: """ << can you give information about the case? (Which "videos"?)

No. Most of the stuff out there. I am already wasting time on HN. I won't also google this stuff for you ( or w/e equivalent you use ). """

You are so full of it. Someone says "present your evidence" when you explicitly said there are videos and you refuse, and here, you are asking exactly "present your evidence".

Before I present my evidence, apply to yourself what you put to others, just strong-man the discussion and try yourself to find element that support my way of seeing the situation.

obstruction of duty is a minor offence, so she was doing an action that put her at risk of a level 3 fine.

You were saying that the onus is on her for putting herself in a situation where she should expect to be shoot. But by your own admission, even if we accept that what she has done properly constitute obstruction of duty (which I doubt is the case, and at best is highly arguable) she was putting herself in a situation where she should never be in any real danger.

But again, you did not answer: she was at the wrong time at the wrong place, she did not go out of her way to be in this situation. Pretending that she "looked for it" is just twisting the facts.

> Your whole world is mildly warped, because you think you can simply apply victim/perpetrator filter to make the whole concept somehow flip. But reality does not work that way.

No, your "whole concept" is just highly subjective. You decided that "the onus is on her" because you decided that when she has responsibility over the fact that the ICE agent was unhinged, while the ICE agent had zero responsibility on the fact that she might be unhinged.

You fail to understand the point. Whatever the specific case is, your argument is that "it's her fault because she did not exercised prudence", and the counter-argument is "in Justice, what you say is simply not true".

And again, your argument is illogical: you can say exactly the same about the ICE agent (they did not acted carefully enough). Why is the victim guilty of not have considered the aggressor as unhinged, and the aggressor not guilty of avoiding the situation that they use to justify their behavior.

First, you did not answer the main point. The main point is that she did not put herself voluntary in a dangerous situation. The fact that some ICE agents were unhinged and dangerous is not something that a normal citizen should expect. And as far as I know, she was just at the wrong place at the wrong time.

But second, your example is moving the goal post. You started by saying "the onus on her". Then you say "when I'm next to my family member that has a gun, I'm almost automatically more careful". But the onus is on your family member. Are you seriously saying that if your family member would shoot you, you will agree that the main responsibility is on you?

And where do you put the bar? Does it mean that if I carry a gun, people should be extra careful next to me and please all of my requests, because it is "on them" if somehow I get angry and shoot them?

This line of reasoning is just so bad. It is "unfalsifiable": you can use this argument anyway you want to blame any people in the situation. Why did you not say "well, the ICE agent should have known that this woman may be dangerous, so he should not have acted in a way that led to increased tension, the onus is on him". And if the ICE agent would have been the victim, would you have said "the onus is on him" for not having been more careful?

What do you mean? For what I know, she was at the wrong place at the wrong time, did not do anything voluntarily illegal, and was in a situation where everyone should agree would never have had to degenerate into a life-threatening situation.

I'm pretty sure that 5 minutes before the incident, everyone involved would agree this was not a life-threatening situation. The only reason there was a death was due to huge failure of ICE.

It's so easy to take any incident where a cop shoot a citizen and says "well, cops have guns, so the onus is on the citizen to be extra careful around cops".

The way you frame the event is very misleading after reading the article.

I know that idiots will argue that "attacking a government building with explosives and committing attempted murder" is "technically correct", but it is stupidity to not understand that it leaves out important nuances.

I don't think the comment you react to is talking about physical limitations (budget, computing power, ...), but scientific methodology policy.

It was perfectly fine to work on any crazy ideas you wanted to. But if you wanted to publish as part of the CERN collaboration (and if you use CERN non-public data and CERN infrastructure, I'm not sure it was possible to publish as an "independent" anyway), there is a lot of protection to ensure that your article is at a good scientific standard.

As explained in the previous comment, scientists were nervous about "black box spurious pattern", "experimental artifacts" or "elsewhere effect". This was a good thing. The limitations were not there because of budget or access to infrastructure, but because people were conscientious of doing good science.

Remember the NN examples where the NN is given pictures of horses and pictures without horses and had to classify them, and it turned out one criteria was to detect the signature, in the bottom right, of the photographer that specializes in horse pictures? It meant that if you were giving a new picture of a bird but with that signature, the NN would say "it is a horse". Now, how do you make sure that something similar does not occur when treating billions of collision events? The categorized data, especially for the signal, is coming from simulation. What if your NN detects that in the signal, the pixel number 231 is not "hot" like the one in real data (because it turns out that, as sensor can be sometimes, this pixel is hotter in the real detector than it is in the simulation), and uses that to select the signal? Or that the NN overfits part of the data (the majority is classified on sensible cuts, but for more extreme cases, it classifies as signal events where there is an electron with pT between 24.5678 and 24.5685, but as background if it is before or after, because it happens to be what the training data looks like)?

Because of that, there were a lot of cross-checks and precautions being taken. One common approach was to compare more black-box-y methods with other methods that are more easily explainable. That was certainly a good thing. And this was not being seen as a chore: no one was approaching it as if people being good scientists where being personally against your new method. Proving that your new method was checking all the boxes of the scientific qualities was not seen as a bad thing, it was seen as the fun part of building new robust scientific advances.

> This is true, but unrelated to your original claim, that LLM algorithms and agentic algorithms are reducible to, exhaustively go down a list.

Well, first, this is not my claim. I'm saying that the behaviour of LLM algorithms and agentic algorithms are closer to "exhaustively go down a list" than "behaving like a persistent human".

But second, yes, they are _just_ systematically exploring the possibilities. They are not "just" a for loop, or they don't "just reduce" to a for loop, but they don't have any characteristics that make them different from a for loop in a way that grant them the attribute "persistent" while it is not granted to a for loop.

What does a agent do that is different from a for-loop and that means that the agent is "persistent" but the "for loop" (or a trivial variation of it that exists and that no one thought of calling it "persistent") is not?

> You're missing the objective here. It has an objective of Z, and so it tries approach X in furtherance of objective Z. Approach X does not work, so it analyzes the failure mode, then devises a new approach Y which takes that failure mode into account. It then tries approach Y, and succeeds at its objective of Z. This is persistence in pursuit of objective Z.

Again, there are 3 usages of "persistence": sense 'a', sense 'b', sense 'c'. I'm saying that there is a confusion between 'b' and 'c'.

In one of its definition, "persistent" means "overlasting". But it is ridiculous to say that people will call their postman "persistent" because the postman keep existing in the real world for more than one day. Obviously, when they say their postman is persistent, they using a different meaning, which correspond to what I've called 'b'.

What you describe here is just a normal decision chart, with one arrow linking one bottom box back to the top box (something that we can call "a loop"). It is persistent in the meaning that I've called 'c'.

> Just look at the definition.

I did. Did you? Cambridge dictionary mentions for example: "Someone who is persistent continues doing something or tries to do something in a determined but often unreasonable way".

You are claiming that there is no difference nuance between 'b' and 'c', that "persistent" is ALWAYS used in the way "try a lot" or "do a lot until it's done". If it is the case, how do you explain that this definition contains these nuance. Why are these nuances there if, according to you, these nuances are not part of the definition.

(unless your point is: "I look in a dictionary and amongst the definitions, I saw one that is used this way", which is a really bad logic mistake: the dictionary also contains the definition "sharp = has pointed edges", but it is not an argument against someone who says "if you say 'he is sharp', it does not mean he has pointed edges")

And, again, when you ask if a postman is persistent, it is ridiculous to not understand that normal human being will put that in context and will use the definition related to human beings (they will not answer: "yes, my postman is persistent because I also have a persistent cough and I saw my postman back at my door as often as I see my cough re-appearing").

Your answer seems to be: "'b' and 'c' are the same thing". This is not true. Dictionaries tell you it is not true. People in the street would tell you it's not true. Even LLM will tell you it's not true. If you are insisting that you are not able to understand this nuance, that exists according to everyone else, then you are just useless in this conversation.

> And I'm saying, that is, in fact, not how they work

I don't think you are right (I was ready to give you the benefice of the doubt, but the rest of your comment makes me think I should not trust your judgement). It is what they do under the wood, and they output text. You read the text, and this text says "I have feelings and I really want to achieve my goal". But this text is just what the LLM returns, not what the LLM really does: the LLM does not understand what this text means, it just understands that it is a valid and convincing sentence in the given context.

> To simplify, just ask the question: is it continuing to work towards an end, even when challenges are encountered? Yes, therefore, it is persistent.

No, they don't continue even when challenges are encountered. They try X, if X does not work, they _abandon_ X and try Y. They will query the web to find another Y, then another Z, then another one. They don't "insist", they don't "don't take no for an answer", they just explore everything. What happened with agents who got out of their sandbox is exactly that: they try to reach a flag, they noticed it was not possible in the way X, so they explore other ways, until their exploration show that going around the sandbox would help. But they did not re-asked and re-asked the same person again and again the same question. If the person says "no", they abandon this approach and move to another one.

> They certainly could be called persistent in delivering the mail

That is blatantly not the common usage of "persistent". Ask anyone in the street "is your postman persistent", and they will NOT tell you "oh, yes, they are" just because they are a postman. They will only say that for _some_ postmen, the ones that are indeed persistent: the ones that goes the extra miles that a "normal" postman do not.

> Again: that is not required by the definition or common meaning of "persistent".

That is just not true. Ask an LLM, they will confirm you that it's incorrect: people don't consider postmen "persistent" because they don't give up half way through their route.

> Again, nobody claimed that "trying all the possibilities" was the definition of "persistence". The definition of persistence here is, continuing to work towards an end when challenges are encountered.

I'm not saying that your definition of "persistence" is "trying all the possibilities". I'm just saying that "persistent agents" look and behave more like an algorithm that tries all the possibilities rather than a "persistent human".

If indeed you are saying that "for x in all_the_possibilities" is not being "persistent", then these agents are not persistent. They don't do anything else different than that: they try something, and if it does not work, they ask the LLM "this does not work, what else can I try", and then do that, over and over again. They are just a for loop.

On the other hand, a "persistent human" does not do just do a for loop. They assign a value to the goal, they care about reaching the goal, they prioritise reaching the goal between that task and all the other tasks they could do, they insist on reaching the goal when it is usually considered unreasonable or "not worth it" by other people. As a proof, a postman that visits all the houses in the street to deliver the mail is not persistent, a journalist who visits all the houses in the street to find a witness is persistent.

> What you're describing here is the exact opposite of persistence.

That's the point. It looks like the term "persistence" for these agents is "just be a normal algorithm, just try all the possibilities like any exhaustive loop would do".

In fact, they are less "persistent" than an exhaustive loop, because they will stop once they have found a solution, while an exhaustive loop will still continue and check all possibilities.

You can imagine the following agent: "ask the LLM for what to do, then assume it failed and ask the LLM for a different approach (you can ask 'it fails, what are the probable cause' and explore the solutions of these causes too), then assume it failed and ask again, and build a list of all the approach. Once done, once you have a list of unique approach and the LLM is unable to find anything more, then try all of these approaches 'for real'. Do not stop if you get the answer, try all of them"

> Maybe for you?

You did not understand. I'm saying "traditional model" are abandoning at the first hurdle, and the "persistent model" are the one just acting "normally", like a normal algorithm. When a retry with exponential retreat algorithm fails to connect, it retries, then retries again, then retries again, ... but I don't think I ever saw calling a software using such approach "persistent".

The thing is that the algorithm is just following its "loop": if it fails, it question the LLM with a different context so the LLM provide a different approach, and then it tries it. It is not different from any loop function, and it does not correspond to a "persistent human", the same way "for x in all_the_possibilities" is not "persistent" in the same way a "persistent human" is.

> When they fail, they try again, often using different approaches.

Well, then they did give up on some approaches. They try to connect on server X to reach location Z, they cannot so they try to hack server X, they cannot so they realise maybe they can try to bypass it by going to server Y to reach location Y, so, they _abandon_ the approach of breaking into server X.

If indeed they never give up on any approach, they will never get the solution, trying the same thing over and over and over in an approach that is simply not working.

I may have not explained very well, but the distinction is that a "persistent person" is more than a person who just do what should be done. A "persistent person" will try again and again where other person would have giving up. This is not present in 'c': the person just do all the possibilities. They don't try again and again where other persons have given up. They are just doing all the tasks on the list, but they will give up on a specific task as soon as any other person if there is difficulties in one task.

(edit: I should maybe not have said, in 'c' "while other models abandon", because it was misleading: my point is that these models are abandoning at the first small hurdle, or even 'forget' the task. It feels that "traditional model" should have been called "lazy model" and "persistent model" should have been called "non-as-badly-lazy model")

But isn't this approach a bias of anthropomorphism. I can teach a child to just communicate by saying "beep boop", but it does not mean that my electronic machine that randomly does "beep boop" therefore has characteristics of human _when these characteristics are not needed to explain the situation_.

> Eh, look up the more recent experimentation around 'pain' signals in models. We can induce states in said models that while running the model will do everything it can to move away from that state to any other state.

Again, I have simple algorithms that do exactly the same, especially if they are trained in data that has this exact pattern. This result is exactly what I would expect from my description before. This is a typical effect that we also observe in simple ML algorithms.

At the same time, there are a bunch of behaviors that are not expected if indeed the models were really acquiring "human" characteristics. For example, one problem is that we had the first LLMs that were obviously not having these human characteristics (for example, they were having non-sequiturs that demonstrate they did not really understand the concept they were talking about, even if one paragraph before they were really convincing at letting us think it was the case) but were still really good at passing for humans. Since then, the newer LLM are the same basis, on top of which we added tools that help hiding these behaviours. So, it justifies the idea that newer models did not suddenly moved to a totally different way of working, but just reached a state where there are less leaks from the convincing outputs.