I’d definitely call any assumption about which forms preferred explanations should take as a “prior”. Maybe I have a more flexible concept of what counts as Bayesian than you, in that sense? Priors don’t need to be free parameters, the process has to start somewhere. But if you already have some data and then acquire some more data, obviously the previous data will still affect your conclusions.
dr_s
Karma: 1,895
I’m not sure how that works. Bayes’ theorem, per se, is correct. I’m not talking about a level of abstraction in which I try to define decisions/beliefs as symbols, I’m talking about the bare “two different brains with different initial states, subject to the same input, will end up in different final states”.
Differences in opinions between two agents could instead be explained by having had different experiences, beliefs being path dependent (order of updates matters), or inference being influenced by random chance.
All of that can be accounted for in a Bayesian framework though? Different experiences produce different posteriors of course, and as for path dependence and random chance, I think you can easily get those by introducing some kind of hidden states, describing things we don’t quite know about the inner workings of the brain.
To be fair, any beliefs you form will be informed by your previous priors. You try to evaluate evidence critically, but your critical sense was developed by previous evidence, and so on so forth back to the brain you came out of the womb with. Obviously as long as your original priors were open minded enough, you can probably reach the point of believing in anything given sufficiently strong evidence—but how strong depends on your starting point.
I am sceptical of recommender systems—I think they are kind of bound to end up in self reinforcing loops. I’d be more happy seeing a more transparent system—we have tags, upvotes, the works, so you could have something like a series of “suggested searches”, e.g. the most common combinations of tags you’ve visited, that a user has a fast access to while also seeing what precisely is it that they’re clicking on.
That said, I do trust this website of all things to acknowledge if things aren’t going to plan and revert. If we fail to align this one small AI to our values, well, that’s a valuable lesson.
It’s generally also very questionable that they started creating models for research, then seamlessly pivoted to commercial exploitation without changing any of their practices. A prototype meant as proof of concept isn’t the same as a safe finished product you can sell. Honestly, only in software and ML we get people doing such shoddy engineering.
I don’t think I disagree with you on anything; my point is more “what does creating new knowledge mean?”. For example, the difference between interpolation and extrapolation might be a rigorous way of framing it. Someone else posted a LeCun paper on that here; he found that extrapolation is the regime in which most ML systems work and assumes that the same must be true of deep learning ones. But for example if there was a phase transition of some kind in the learning process that makes some systems move to an interpolation regime, that could explain things. Overall I agree that none of this should be a fundamental difference with human cognition. It could be a current one, but it would at least be possible to overcome in principle. Or LLMs could already be in this new regime, since after all, not like anyone checked yet (honestly though, it might not be too hard to do so, and we should probably try).
Oh, I didn’t know about that paper—I’ll have to read that. Though my opinion of LeCun’s objectivity on this matter is definitely underground at this point.
Well, those three sets of points ultimately still define only one hull. But I get your intuition—there are areas inside that hull that are high density, and areas that are much lower density (but in which it might be easier to extrapolate due to being surrounded by known areas). I feel like also our inability to visualize these things in their true dimensionality is probably really limiting. The real structures must be mind-boggling and probably looking more like some kind of fractal filament networks.
Good Bings copy, great Bings steal
Given that the model eventually outputs the next token, shouldn’t the final embedding matrix be exactly your linear fit matrix multiplied by the probability of each state to output a given token? Could you use that?
This is extremely cool! Can you go into more detail about the step used to project the 64 dimensional residual stream to 3 dimensional space? Did you do a linear fit over a few test points and then used it on all the others?
I think you could, but then it would be unintelligible to most people who don’t know wtf is Solomonoff Induction.
The Ponzi Pyramid scheme IMO is sn excellent framework, but the post still suffers from a certain, eh, lack of conciseness. I think you could make the point a lot more simply with just a few exchanges from the first section and anyone worth their salt will absolutely get the spirit of the point.
I think this is an added layer though—I don’t think the responses listed here are responses of people deep enough in the transhumanism/AI rabbit hole to even consider those options. Rather, they sound like the more general kind of answers that you’d hear also in response to a theoretical offer of immortality that means 100% what you expect it to, no catches.
If immortality becomes widely available, we will lose the current guarantee that “awful people will eventually die”, which greatly increases the upper bounds of the awfulness they can spread
I mean… amazingly good people die too. Sure, a society of immortals would obviously very weird, and possibly quite static, but I don’t see how eventual random death is some kind of saving grace here. Awful people die and new ones are born anyway.
I think another big issue with codes of conduct is that they just shift the burden around. You’re still left with the issue of interpreting the spirit of the norm, deciding if everyone at least made a good faith attempt to stick to it, if good faith is enough, etc. I don’t have much experience with them but I honestly don’t know if they help that much. Seems to me like there are two types of “troublemakers” in communities no matter what:
people who are purposefully deceptive and manipulative;
people who simply lack the social grace and ability to “read the room” required to meet other’s expectations of social norms adherence rather than just stick to their own interpretation of them.
Type 1 you want to kick out. Type 2 you ideally want to be a lot more graceful and forgiving with, though in some extreme cases you might still need to kick them out if their problems are unfixable and they make no effort whatsoever to at least mitigate the issues. Writing the rules down doesn’t help as long as they’re flexible, because the problem those people have is a lack of the sort of intuition that others possess for grokking flexible rules altogether. And if you make them inflexible you just have a chilling effect on every interaction, and throw away a lot of good with the bad. After all, for example, why shouldn’t someone ask a woman out at their first meeting if they’re both clearly into each other and sparks are flying? These things happen! And people should be able to give it a try, I think it’s important to make it clear that there’s nothing sinful or bad about courtship or flirting per se; too many rigid rules about such personal interactions inevitably carry a sort of puritanical vibe with them, regardless of intention. But as usual, “use your best judgement” has very uneven effects because some people’s best judgement is just not that great to begin with, often through no fault of their own.
I would. It’s possible an election in which a third party candidate has a serious chance might exist, but it wouldn’t look like this one at this point. Only way the boat could at least be rocked is if the charges go through and Trump is out of the race by force majeure, at which point there’s quite a bit of chaos.
I mean, even so… it’s ten minutes. I’d be bored on a 2 hour trip on which I’m unable to read. For ten minutes, I can manage.
Shared biological needs aren’t a guarantee of friendliness, but they do restrict the space of possibilities significantly—enough, IMO, to make the hopes of peaceful contact not entirely moot. Also here it comes with more constraints. Again, if we ever meet aliens, it will probably have to be social organisms like us, who were able to coordinate and cooperate like us, and thus can be probably reasoned with somehow. Note that we can coexist with bears and chimpanzees. We just need to not be really fucking stupid about it. Bears aren’t going to be all friendly with us, but that doesn’t mean they just kill for kicks or have no sense of self-preservation. The communication barrier is a huge issue too. If you could tell the bear “don’t eat me and I can bring you tastier food” I bet things might smooth out.
AI is not subject to those constraints. “Being optimised to produce human-like text” is a property of LLMs specifically, not all AI, and even then, its mapping to “being human-like” is mostly superficial; they still can fail in weird alien ways. But I also don’t expect AGI to just be a souped up LLM. I expect it to contain some core long term reasoning/strategizing RL model more akin to AlphaGo than to GPT-4, and that can be far more alien.
This is a double edged sword to me. Biological entities might be very different in the details but shaped by similar needs at their core—nutrition, fear of death, need for sociality and reproduction (I don’t expect any non-social aliens to ever become space faring in a meaningful way). AIs can ape the details but lack all those pressures at their core—especially those of prosociality. That’s why they might end up potentially more hostile than any alien.
Personalization is easy to achieve while keeping the algorithm transparent. Just rank your own viewed/commented posts by most frequent tags, then score past posts based on the tags and pick a quantile based on the mixed upvotes/tags score, possibly with a slider parameter that allows you to adjust which of the two things you want to matter most.