But the soldiers didn't have the mobile phones then. This was possible by manipulation the information about reality those soldiers had.
For example, how Mallory can gain power over Alice and Bob who don't directly communicate.
First, Mallory tells Alice: "I am stronger than you. If you don't do what I say I'll kill you." So Alice decides to submit.
Then, Mallory takes Alice to Bob and says to him: "Together with Alice we are stronger than you, and kill you if you don't do what I want." So Bob submits.
This only works if Bob doesn't talk to Alice, otherwise they would together see the empty threat.
With more people, it becomes a bit trickier but hopefully you see how blocking communication helps to gain power over people. Often the blocking of communication is done through propaganda, e.g. Mallory might entice Alice and Bob to hate each other, so they wouldn't get together and figure he's the manipulator. Or Mallory might just kill someone randomly to motivate people not to talk to each other.
Anyway, this shows the importance of free speech (which is really a misnomer; it should be called a right to listen). If you can freely talk (and listen) to other people, you reduce your chances to being subjugated by someone.
(This is also why in a war, people are incentivized to dehumanize the other party and not to listen what they say, because together they could figure out that the real enemy are the war profiteers on both sides, colluding. And besides, killing is the most reliable way of silencing someone. That's why people should also universally reject killing - based on someone else's word - unless they are directly threatened themselves.)
Sorry, but I think you've kind of just dug yourself into some concept you think is neat but which doesn't really hold up. Like, this just doesn't hold up to scrutiny at all.
First, general power dynamics are in no way inherently predicated on misinforming people. That can help, but it's really quite a lot simpler than that: A commands B and C. A approaches D and says get in line or we'll kill you. D says OK or dies. ABCD approach E and repeat this process. The person with the most connections, actual real connections, wins. The challenge to building more connections than A is not having a cell phone, but rather attempting to find connections who aren't truly loyal to A, because anyone who is loyal will out you and have you killed for treason. Indeed cell phones make this harder, not easier, because they leave a paper trail of evidence that you were attempting to betray the existing group.
Second, mobile phones do nothing to change this dynamic in favor of the weak, and in fact, are one of the most powerful tools for cementing existing power structures ever created. They are both the ultimate channel to propagate misinformation, and are also 24/7 surveillance devices that will betray any attempt to conspire against those in power. If you want to foster rebellion against your evil overlords, your organization absolutely cannot use phones without giving themselves away, which puts you at a massive technical disadvantage. And even if you try to forbid members from using phones, they're so deeply ingrained into daily life that somebody will inevitably slip up and give the surveillance state info on your planned rebellion. I would go so far as to say we can expect to never see a successful rebellion against anybody with the level of surveillance as the US, in our lifetimes.
The end of Covid in China is interesting. Even the CCP, and their level of surveillance and control, were unable to maintain control of an entire population fed up with sheltering in place. If there aren't fair and open elections in 2028, it will no longer be the United States of America.
But what we're gonna manage the codebase in, then? What kind of language?
Will it be a natural language, or a formal one?
I feel that "coding" cannot collapse. Coding is just translation from natural to formal language. Somebody needs to write the specs. And writing/maintaining them in natural language brings a lot of fun - shifting interpretation, inconsistency, missing specification, etc.
I don't think it's progress for the field of SW engineering. But at least more "shareholder value" will be created.
"But seemingly models good at programming for example, would get worse at programming if you removed everything not-programming. Train a model solely on syntax, and it'll be worse than a general purpose LLM on syntax, in general at least."
That might be because emergence of capabilities to reason about programs requires abstractions (such as fuzzy and modal logic) that are rarely present in software sources. That doesn't mean the reasoning model itself has to be large; neither does it have to emerge from the ML training on large language corpus, we might construct it by different means.
I partly agree. Theory (of computation) shows it must be possible, however nobody has produced the small model (well, depends who you ask, what is small, article disputes that) and the database yet.
To go very small (thousands of rules) so that the reasoner can be understood by humans and proven sound - might be computationally quite difficult.
The cost you pay is in additional reasoning the SLMs have to do. As I write elsewhere, LLM "remembers" that "Socrates is mortal", or other commonly useful deduction. SLM might need to derive it first by reasoning from the DB, which slows it down. (Or worse, it might miss the correct reasoning because it's just too much side quests to follow.) But the advantage is flexibility.
I believe it is true, and likely there exists a class of even smaller models than what they call "small".
You can imagine a reasoning model as a huge set of rules that generate the next statement from previous statements (written in context). In that sense, a reasoning model can be compared to a logical theory - you have certain deduction rules which can generate new judgments.
Often, logical theories are structured that the rules are remade into axioms, and the deduction rule is only modus ponens (which corresponds to function application and is a building block of program execution).
In the case of an LLM, the set of rules (or axioms) they have in the theory is quite large, but most likely semantically unsound (with respect to their their own representation of truth) - that's why LLM's make mistakes.
It would be desirable to break the logical theory represented by LLM into a smaller set of axioms, which would:
a) remove rules easily deductible from the smaller core of axioms (for example, LLM doesn't need to remember "Socrates is mortal", as it can derive it from "Socrates is a man" and "all men are mortal")
b) remove rules that have low value (facts that aren't used often or have weak validity) which cause ruleset to become unsound
I suspect that's what SLM distillation is doing, to some extent.
The question is, how far this process can go? I personally believe there is a useful logic for commonsense reasoning that has less than thousand rules (still several orders more than your typical mathematical logic, but orders less than SLMs). These axioms do not contain much facts about the world, but that could be added.
So I believe there is a sweet spot (deductive core, encyclopedic shell) which we have not yet found (it's a little bit more formal language than natural language) but is very efficient for general reasoning.
Oh it would change a lot. It would be an enormous psychological boost for everyone to find a practical algorithm.
In any case, I think it's better to read PP as somebody would find a practical, albeit incomprehensible, algorithm for solving NP complete problems.
Although I probably disagree with PP, because even a candidate algorithm that mysteriously works without proof would have practical value, so this case is not predicated on proving.
I think a better example of genuinely practical but rather uninteresting (YMMV) mathematical proofs are proofs of convergence of numerical methods, FEM for example. (I have been through it in school, it was a torture.)
b) You have to convince many other people as well (that you're a magic oracle), because for the effect to work, lot of people would have to work on the problem (or at least spend tokens)
Nevertheless, a plausible magic oracle (such as Lean-verified proof, even if non-constructive and incomprehensible for humans) would convince many to take a 2nd look.
> a practical, albeit incomprehensible, algorithm for solving NP complete problems.
It would not not necessarily be practical, even if it ran in polynomial time. It may have cost O(n^c), with a totally out of order exponent like c=A(5,5) or whatever.
I don't understand why people who don't like fake news and manipulation won't embrace the social graph as a public good.
If enough people were willing to publicly certify that their fellow contacts are human, anybody could then assign trust to each social graph node based on the trust they have in the path to them. It would completely decentralize the algorithms and remove the fake accounts as less trustworthy.
I think people tried this with PGP but it never really caught on.
They do. It's already like this with business recommendations, always use a personal reference before anything else.
I've thought about making some digital reputation system that cannot be gamed. You can rep people you know and then query if there's any path of rep from you to a random person. The global number of reps you have doesn't matter, only paths. Problem is this only works if the target person can't tell that you repped them, which is impossible to hide because they can just rep you with a fake account then see if there's a path to their real account. But maybe with some fuzzing.
It doesn't scale as a consumer good. Letting go of consumerist habits is just as hard as breaking any other habit.
Also, it could just as easily be faked, like so much else. Even if someone offered such an assurance, I wouldn't trust random strangers on the internet. At best it would become an arms race between "this is not a real person" and those who sell fake assurances. And it would be one more weapon to damage anyone's reputation you don't like. "not a real person!"
I am not really sure how it could be faked. The fake assurance, in order to work, must be connected to you.
By default you could choose not to trust. If you don't trust random strangers it's OK. So I don't see how it would damage someone's reputation worse than today.
It would potentially only add trust. Arguably, today we have bots because we have no other option than to trust without justification. With the public social graph, the trust above the baseline would be justifiable.
So what happens when people are paid or otherwise incentivised to 'trust'?
This model was used in the beginning of the web, where links to your site from a well trusted website would increase the score and therefore SEO of your own site. This very quickly turned into a business of people selling hidden paid site links, and evolved into the paid editorial model we see on every news site today.
Hm, that's an interesting point. But wasn't problem of that model that the social graph (links) were not really public, but rather hidden within a search engine such as Google? Maybe if they are public the problem would be mitigated.
The social graph is the source of the fake news and manipulation. Before social media the social graph was email and it was all the same slop and misinformation. Before that it was literally physical mail. Look up chain letters. Truly nothing is new.
If I certify my racist thanksgiving ruining uncle is a real person that doesn’t actually help you avoid misinformation.
I honestly don’t care if the information I consume comes from a person or a robot. I only care if it is accurate or not. Those dimensions are orthogonal.
This is exactly how bubbles of influence appear. Rarely do people from different leanings (social, political, economical etc) have spheres of opinion which intersect, and therefore get trapped in areas of general agreement. The social graph cannot be trusted to create a generally trusted source, because peoples innate distrust of things which differ from their own opinion skew this model heavily.
I should have noted, my comment is about facts. Opinion you can have, if you think it's beneficial for you not to trust (or trust) some nodes, do so!
The public social graph would be about who is a human, that can certify facts. Their opinion wouldn't really matter until you chose it to matter for you. Them being a human witness would only add credence to the accounts of the facts they witnessed, nothing more. You can still choose to disbelief the event if you have a good reason to (for example, even if you might believe a guy from Russia is a real person based on his social graph, if he certifies an event in Michigan, you might be skeptical of that account and decide to lower your own trust in that person). So there is a difference between the shared social graph - which is about a collective belief of who is a person, and your own trust, which you can modify as you wish. Unlike with Google and other big tech providers, there is not a singular "algorithm for trust" that can be manipulated.
You seem to be saying it will fail because people are tribal. I believe it will not fail, because the benefits of knowing the local social graph of each person will outweigh the tendency for opinion to split based on tribe. And the reason I think so is that trust evolved and exists in society; we do not only trust ourselves, and that's only possible if something like a social graph can work. The only issue is the scale, which can be solved by using a computer instead of computing it in our little heads.
Mass reporting means spending huge amount of reputation which doesn't really invalidate reputation of people who still certify that the person exists.
The problem with the current systems is that reputation buying is not transparent. In my system, it would be a public record, who endorsed who. So you could go back and track the fake reputation.
Also real people have some TTL with their accounts. Unlike links, "I am real person" is not nearly as fungible.
They are not saying what the cause of the "downplay" is. It might be as simple as when scientists speaks publicly and present a consensus, they will stay on the safe side and give conservative estimates.
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