Posts

UML XII: Dimensionality Reduction 2020-02-23T19:44:23.956Z · score: 9 (3 votes)
UML XI: Nearest Neighbor Schemes 2020-02-16T20:30:14.112Z · score: 15 (4 votes)
A Simple Introduction to Neural Networks 2020-02-09T22:02:38.940Z · score: 25 (9 votes)
UML IX: Kernels and Boosting 2020-02-02T21:51:25.114Z · score: 13 (3 votes)
UML VIII: Linear Predictors (2) 2020-01-26T20:09:28.305Z · score: 9 (3 votes)
UML VII: Meta-Learning 2020-01-19T18:23:09.689Z · score: 15 (4 votes)
UML VI: Stochastic Gradient Descent 2020-01-12T21:59:25.606Z · score: 13 (3 votes)
UML V: Convex Learning Problems 2020-01-05T19:47:44.265Z · score: 13 (3 votes)
Excitement vs childishness 2020-01-03T13:47:44.964Z · score: 18 (8 votes)
UML IV: Linear Predictors 2019-12-29T19:17:37.054Z · score: 13 (3 votes)
Understanding Machine Learning (III) 2019-12-25T18:55:55.715Z · score: 17 (5 votes)
Understanding Machine Learning (II) 2019-12-22T18:28:07.158Z · score: 25 (7 votes)
Understanding Machine Learning (I) 2019-12-20T18:22:53.505Z · score: 41 (8 votes)
Insights from the randomness/ignorance model are genuine 2019-11-13T16:18:55.544Z · score: 7 (2 votes)
The randomness/ignorance model solves many anthropic problems 2019-11-11T17:02:33.496Z · score: 10 (7 votes)
Reference Classes for Randomness 2019-11-09T14:41:04.157Z · score: 8 (4 votes)
Randomness vs. Ignorance 2019-11-07T18:51:55.706Z · score: 5 (3 votes)
We tend to forget complicated things 2019-10-20T20:05:28.325Z · score: 51 (19 votes)
Insights from Linear Algebra Done Right 2019-07-13T18:24:50.753Z · score: 53 (23 votes)
Insights from Munkres' Topology 2019-03-17T16:52:46.256Z · score: 40 (12 votes)
Signaling-based observations of (other) students 2018-05-27T18:12:07.066Z · score: 12 (4 votes)
A possible solution to the Fermi Paradox 2018-05-05T14:56:03.143Z · score: 10 (3 votes)
The master skill of matching map and territory 2018-03-27T12:06:53.377Z · score: 36 (11 votes)
Intuition should be applied at the lowest possible level 2018-02-27T22:58:42.000Z · score: 29 (10 votes)
Consider Reconsidering Pascal's Mugging 2018-01-03T00:03:32.358Z · score: 14 (4 votes)

Comments

Comment by sil-ver on UML XI: Nearest Neighbor Schemes · 2020-02-17T08:26:38.480Z · score: 1 (1 votes) · LW · GW

That sounds interesting. Can you share an example other than decision trees?

Comment by sil-ver on When None Dare Urge Restraint · 2020-02-15T17:36:34.440Z · score: 1 (1 votes) · LW · GW

I'm not sure EY meant to imply that the response is factually correct. Smarter-than-expected could just mean "not a totally vapid applause light." A wrong but genuine response could meet that standard.

Comment by sil-ver on UML VIII: Linear Predictors (2) · 2020-02-13T17:24:04.542Z · score: 2 (2 votes) · LW · GW

It's supposed to be inf (the infimum). Which is the same as the minimum whenever the minimum exists, but sometimes it doesn't exist.

Suppose is , i.e. and the point is 3. Then the set doesn't have a smallest element. Something like is pretty close but you can always find a pair that's even closer. So the distance is defined as the largest lower-bound on the set , which is the infimum, in this case 2.

Comment by sil-ver on A Simple Introduction to Neural Networks · 2020-02-10T22:55:17.146Z · score: 7 (4 votes) · LW · GW

Okay – since I don't actually know what is used in practice, I just added a bit paraphrasing your correction (which is consistent with a quick google search), but not selling it as my own idea. Stuff like this is the downside of someone who is just learning the material writing about it.

Comment by sil-ver on A Simple Introduction to Neural Networks · 2020-02-10T08:31:28.940Z · score: 3 (2 votes) · LW · GW
What's the "ℓ"? (I'm unclear on how one iterates from L to 2.)

is the number of layers. So if it's 5 layers, then . It's one fewer transformation than the number of layers because there is only one between each pair of layers.

Absolute value, because bigger errors are quadratically worse, it was tried and it worked better, or tradition?

I genuinely don't know. I've wondered forever why squaring is so popular. It's not just in ML, but everywhere.

My best guess is that it's in some fundamental sense more natural. Suppose you want to guess a location on a map. In that case, the obvious error would be the straight-line distance between you and the target. If your guess is and the correct location is , then the distance is – that's just how distances are computed in 2-dimensional space. (Draw a triangle between both points and use the Pythagorean theorem.) Now there's a square root, but actually the square root doesn't matter for the purposes of minimization – the square root is minimal if and only if the thing under the root is minimal, so you might as well minimize . The same is true in 3-dimensional space or -dimensional space. So if general distance in abstract vector spaces works like the straight-line distance does in geometric space, then squared error is the way to go.

Also, thanks :)

Comment by sil-ver on Some quick notes on hand hygiene · 2020-02-09T10:02:23.935Z · score: 1 (1 votes) · LW · GW

Good post. I would actually argue that the cost of many second activities is much lower than the cost of one block of seconds, because taking small breaks in between work isn't zero value.

Comment by sil-ver on Some quick notes on hand hygiene · 2020-02-06T15:21:20.148Z · score: 1 (1 votes) · LW · GW
Have you been doing something that puts stuff on you hands that is no already spread everywhere you are and will touch or for some reason has caused a significantly higher concentration on your hands versus the environment?

Don't think so.

Bite your fingernails, or stick you fingers, hands on/in you mouth a lot? Stop or be aware of what you've been touching since the last cleaning.

That's not at all practical, though. Changing a habit such as biting fingernails is extremely difficult, and definitely not worth it to reduce the risk of getting a virus.

Comment by sil-ver on Meta-Preference Utilitarianism · 2020-02-06T11:28:01.023Z · score: 1 (1 votes) · LW · GW

To make Wei Dai's answer more concrete, suppose something like the symmetry theory of valence is true; in that case, there's a crisp, unambiguous formal characterization of all valence. Then add open individualism to the picture, and it suddenly becomes a lot more plausible that many civilizations converge not just towards similar ethics, but exactly identical ethics.

Comment by sil-ver on Some quick notes on hand hygiene · 2020-02-06T11:18:24.246Z · score: 11 (11 votes) · LW · GW

What's missing for me here is a quantitative argument for why this is actually worth doing. Washing your hands more often would reduce risk, but is it actually worth the effort? (And for me there's also the problem that my doctor literally instructed me to wash my hands less often because of a skin infection thing.)

Comment by sil-ver on Category Theory Without The Baggage · 2020-02-04T17:24:55.429Z · score: 1 (1 votes) · LW · GW

I believe query and target category are the same here, but after reading it again, I see that I don't fully understand the respective paragraph.

Comment by sil-ver on Category Theory Without The Baggage · 2020-02-04T13:24:40.528Z · score: 1 (1 votes) · LW · GW

I think the query category is the pattern, as you say, and the target category is [original category + copy + edges between them]. That way, if the matching process returns a match, that match corresponds to a path-that-is-equivalent-to-the-path-in-the-query-category.

Comment by sil-ver on Category Theory Without The Baggage · 2020-02-04T13:20:57.603Z · score: 5 (3 votes) · LW · GW
e.g. “colou*r” matches “color” or “colour” but not “pink”.

Is this correct? I'd have thought "colo*r" matches to both "color" and "colour", but "colou*r" only to "colour".

Next-most complicated

Least complicated?

I'm very likely to read every post you write on this topic – I've gotten this book a while ago, and while it's not a priority right now, I do intend to read it, and having two different sources explaining the material from two explicitly different angles is quite nice. (I'm mentioning this to give you a an idea of what kind of audience gets value out of your post; I can't judge whether it's an answer to your category resource question, although it seems very good to me.)

I initially thought that the clouds were meant to depict matches and was wondering why it wasn't what I thought it should be, before realizing that they always depict the same stuff and were meant to depict "all stuff" before we figure out what the matches are.

Comment by sil-ver on REVISED: A drowning child is hard to find · 2020-01-31T19:26:31.322Z · score: 3 (6 votes) · LW · GW

(This is a general comment about the argument, not about the revisions.)

Neither scenario suggests that small donors should try to fill this funding gap. If they trust big donors, they should just give to the big donors. If they don't, why should they believe a story clearly meant to extract money from them?

Because some people are trustworthy and others aren't.

The reason why I believe the EA claims is pretty simple: I trust the people making them. The fact that there is a lot of altruistic value sort of lying on the sidewalks may be a-priori surprising, but we have so much evidence that maximizing altruism is extremely rare that I don't see much of an argument left at this point. EY made this point in Inqadequate Equiliria:

Eliezer: Well, mostly I’m implying that maximizing altruism is incredibly rare, especially when you also require sufficiently precise reasoning that you aren’t limited to cases where the large-scale, convincing study has already been done; and then we’re demanding the executive ability to start a new project on top of that. But yes, I’m also saying that here on Earth we have much more horrible problems to worry about.
Comment by sil-ver on Open & Welcome Thread - December 2019 · 2020-01-08T10:43:14.477Z · score: 1 (1 votes) · LW · GW
When I learned probability, we were basically presented with a random variable X, told that it could occupy a bunch of different values, and asked to calculate what the average/expected value is based on the frequencies of what those different values could be. So you start with a question like "we roll a die. here are all the values it could be and they all happen one-sixth of the time. Add each value multiplied by one-sixth to each other to get the expected value." This framing naturally leads to definition (1) when you expand to continuous random variables.

That's a strong steelman of the status quo in cases where random variables are introduced as you describe. I'll concede that (1) is fine in this case. I'm not sure it applies to cases (lectures) where probability spaces are formally introduced – but maybe it does; maybe other people still don't think of RVs as functions, even if that's what they technically are.

Comment by sil-ver on [AN #80]: Why AI risk might be solved without additional intervention from longtermists · 2020-01-04T21:25:56.219Z · score: 5 (3 votes) · LW · GW
value-conditioned probabilities

Is this a thing or something you just coined? "Probability" has a meaning, I'm totally against using it for things that aren't that.

I get why the argument is valid for deciding what we should do – and you could argue that's the only important thing. But it doesn't make it more likely that our world is robust, which is what the post was claiming. It's not about probability, it's about EV.

Comment by sil-ver on What cognitive biases feel like from the inside · 2020-01-04T20:21:38.570Z · score: 0 (4 votes) · LW · GW
Here's the thing though. Sometimes one side IS genuinely correct[/good], and the other side IS genuinely wrong[/evil].

Take the [] out, and this is one of the first things I was thinking upon reading this post. Interestingly, you don't need to bring conflict vs mistake theory into this at all.

I think this comment should be its own post/open thread comment (probably the latter) and then I'd find it reasonable (dn about others). The tolerance on this site for talking about your pet issue in the context of sth vaguely related is very low.

Comment by sil-ver on [AN #80]: Why AI risk might be solved without additional intervention from longtermists · 2020-01-03T08:35:12.451Z · score: 1 (1 votes) · LW · GW

You're right, the nature of uncertainty doesn't actually matter for the EV. My bad.

Comment by sil-ver on [AN #80]: Why AI risk might be solved without additional intervention from longtermists · 2020-01-03T07:16:57.294Z · score: 3 (2 votes) · LW · GW

I'm more uncertain about this one, but I believe that a separate problem with this answer is that it's an argument about where value comes from, not an argument about what is probable. Let's suppose 50% of all worlds are fragile and 50% are robust. If most of the things that destroy a world are due to emerging technology, then we still have similar amounts of both worlds around right now (or similar measure on both classes if they're infinite many, or whatever). So it's not a reason to suspect a non-fragile world right now.

Comment by sil-ver on [AN #80]: Why AI risk might be solved without additional intervention from longtermists · 2020-01-03T07:12:12.175Z · score: 1 (1 votes) · LW · GW
E.g. if you have a broad distribution over possible worlds, some of which are "fragile" and have 100 things that cut value down by 10%, and some of which are "robust" and don't, then you get 10,000x more value from the robust worlds. So unless you are a priori pretty confident that you are in a fragile world (or they are 10,000x more valuable, or whatever), the robust worlds will tend to dominate.

This is only true if you assume that there is an equal number of robust and fragile worlds out there, and your uncertainty is strictly random, i.e. you're uncertain about which of those worlds you live in.

I'm not super confident that our world is fragile, but I suspect that most worlds look the same. I.e., maybe 99.99% of worlds are robust, maybe 99.99% are fragile. If it's the latter, then I probably live in a fragile world.

Comment by sil-ver on Plausible A.I. Takeoff Scenario Short Story · 2020-01-01T21:30:44.094Z · score: 2 (2 votes) · LW · GW

I meant "independent person" as in, someone not part of the biggest labs

(Admittedly, not all papers are equally insightful, and maybe OpenAI & DeepMind's papers are more insightful than average, but I don't think that's a strong enough effect to make them account for "most" AI insights.)

Since most researchers are outside of big labs, they're going to publish more papers. I'm not convinced that means much of anything. I could see usefulness vary by factors of well over 100. Some papers might even negative utility. I think all of the impressive AI's we've seen, without any real exception, have come out of big research labs.

Also, I believe you're assuming that research will continue to be open. I think it's more likely that it won't be, although not 95%.

But ultimately I'm out of my depth on this discussion.

Comment by sil-ver on Plausible A.I. Takeoff Scenario Short Story · 2020-01-01T21:22:53.169Z · score: 2 (2 votes) · LW · GW

First off, let me say that I could easily be wrong. My belief is both fairly low confidence and not particularly high information.

If that were true, start-ups wouldn't be a thing, we'd all be using Yahoo Search and Lockheed Martin would be developing the first commercially successful reusable rocket. Hell, it might even make sense to switch to planned economy outright then.

I don't think any of that follows. Any good idea can be enough for a successful start-up. AGI is extremely narrow compared to the entire space of good ideas.

But why does it matter? Would screaming at the top of your lungs about your new discovery (or the modern equivalent, publishing a research paper on the internet) be the first thing someone who has just gained the key insight does? It certainly would be unwise to.

It doesn't matter that much, but it makes it a bit harder -- it implies that someone outside of the top research labs not only has the insight first, but has it first and then the labs don't have it for some amount of time.

Comment by sil-ver on Plausible A.I. Takeoff Scenario Short Story · 2020-01-01T19:14:32.941Z · score: 3 (3 votes) · LW · GW

I actually agree that the "last key insight" is somewhat plausible, but I think even if we assume that, it remains quite unlikely that an independent person has this insight rather than the people who are being paid a ton of money to work on this stuff all day. Especially because even in the insight-model, there could still be some amount of details that need to be figured out after the insight, which might only take a couple of weeks for OpenAI but probably longer for a single person.

To make up a number, I'd put it at < 5% given that the way it goes down is what I would classify under the final-insight model.

Comment by sil-ver on Plausible A.I. Takeoff Scenario Short Story · 2020-01-01T11:36:49.422Z · score: 5 (3 votes) · LW · GW
In any case, it's a story, not a prediction, and I'd defend it as plausible in that context. Any story has a thousand assumptions and events that, in sequence, reduce the probability to infinitesimal.

Yeah, I don't actually disagree. It's just that, if someone asks "how could an AI actually be dangerous? It's just on a computer" and I respond by "here look at this cool story someone wrote which answers that question", they might go "Aha, you think it will be developed on a laptop. This is clearly nonsense, therefore I now dismiss your case entirely". I think you wanna bend over backwards to not make misleading statements if you argue for the dangers-from-ai-is-a-real-thing side.

You're of course correct that any scenario with this level of detail is necessarily extremely unlikely, but I think that will be more obvious for other details like how exactly the AI reasons than it is for the above. I don't see anyone going "aha, the AI reasoned that which is clearly implausible because it's specific, therefore I won't take this seriously".

If I had written this, I would add a disclaimer rather than change the title. The disclaimer could also explain that "paperclips" is a stand-in for any utility function that maximizes for just a particular physical thing.

Comment by sil-ver on Plausible A.I. Takeoff Scenario Short Story · 2020-01-01T08:10:37.037Z · score: 4 (6 votes) · LW · GW

I think it might be useful to have stories like these, and it's well written; however:

Plausible A.I. Takeoff Scenario Short Story

,

I am running on a regular laptop computer, in a residential area in Wellington, New Zealand.

These two things are in contradiction. It's not a plausible scenario if the AGI begins on a laptop. It's far more likely to begin on the best computer in the world owned by OpenAI or something. Absent a disclaimer, this would be a reason for me not to share this.

Also, typo:

It’s creator must have shut it off.
Comment by sil-ver on 2020's Prediction Thread · 2020-01-01T07:59:51.192Z · score: 1 (1 votes) · LW · GW

That might or might not be a better proxy for the kind of overconfidence I've been meaning to predict.

The reason why it might not: my formulation relied on the idea that most people will formulate their predictions such that the positive statement corresponds to the smaller subset of positive future space. In that case, even if it's a < 50% prediction, I would still suspect it's overconfident. For example:

6) South Korea and Philippines change alliance from USA to China and support it's 9 dash line claims. Taiwan war with mainland China. 35%

Now I've no idea about the substance matter here, but across all such predictions, I predict that they'll come true less often than the probability indicates. So if we use either of the methods you suggested here, the 35% figure moves upward rather than downward; however I think it should go down.

Comment by sil-ver on 2020's Prediction Thread · 2019-12-31T07:59:42.459Z · score: 3 (3 votes) · LW · GW

Using a reasonable calibration method*, the set of predictions made in this thread will receive a better score than the set of those in the previous thread from 10 years ago (80%)

Nonetheless, lowering each confidence stated by a relative 10% (i.e. 70% to 63% etc.) will yield better total calibration (60%)

I don't know the math for this, but I'm assuming there is one that inputs a set of predictions and their truth values and outputs some number, such that the number measures calibration and doesn't predictably increase or decrease with more predictions.

I believe that the second one can technically lead to a paradox, but it's highly unlikely for that to occur.

Comment by sil-ver on 2010s Predictions Review · 2019-12-31T07:45:08.178Z · score: 20 (9 votes) · LW · GW

One of the lessons I draw from this: listen to gwern.

Comment by sil-ver on Open & Welcome Thread - December 2019 · 2019-12-28T13:05:10.934Z · score: 1 (1 votes) · LW · GW

I'm (re-)reading up on absolutely continuous probability spaces right now. The defintion for the expected value I find everywhere is this:

(1):

The way to interpret this formula is that we're integrating over the target space of rather than the domain, and is a probability density function over the target space of . But this formula seems highly confusing if that is left unsaid ( doesn't even appear in it – what the heck?). If one begins with a probability density function over a probability space and then wants to compute the expected value of a random variable , I think the formula is:

(2):

It seems utterly daft to me to present (1) without first presenting (2) if the idea is to teach the material in an easily understandable way. Even if one never uses (2) in practice. But this is what seems to be done everywhere – I googled a bunch, checked wikipedia, and dug out an old script, I haven't found (2) anywhere (I hope it's even correct). Worse, none of them even explicitly mention that ranges over rather than over after presenting (1). I get each random variable does itself define a probability space where the distribution is automatically over but I don't think this is a good argument not to present (2). This concept is obviously not going to be trivial to understand.

Stuff like this makes me feel like almost no-one thinks for themselves unless they have to, even in math. I'm interested in whether or not fellow LW-ians share my intuition here.

There seems to be a similar thing going on in linear algebra, where everyone teaches concepts based on the determinant, even though doing it differently makes them far easier. But there it feels more understandable, since you do need to be quite good to see that. This case here just feels like people aren't even trying to optimize for readability.

Comment by sil-ver on Understanding Machine Learning (I) · 2019-12-24T19:50:35.949Z · score: 3 (2 votes) · LW · GW

Yeah, it does mean that. I hadn't thought about it until now, but you're right that it's not at all obvious. The book never mentions weighing them differently, but the model certainly allows it. It may be that an asymmetric loss function complicates the results; I'd have to check the proofs.

I'll edit the part you quoted to make it a weaker claim.

Comment by sil-ver on Might humans not be the most intelligent animals? · 2019-12-24T16:06:28.023Z · score: 1 (1 votes) · LW · GW
Well, that might be true of human language -- though I'm not sure about the case of sign language for apes in captivity. Part of the problem is the physiological ability to make the sounds needed for human language. The other species simply lack that ability for the most part.
But how about flipping that view. Has any human been able to learn any language any other species might use? Sea mammals (dolphin, whales) appear to have some form of vocal communications. Similarly, I've at least heard stories that wolves also seem to communicate. Anecdotally, I have witnessed what I would take as am indication of communication between two of the dogs we used to have.

Those are decent points. Not enough to sell me but enough to make me take it more seriously.

Comment by sil-ver on Might humans not be the most intelligent animals? · 2019-12-24T14:54:17.904Z · score: 1 (1 votes) · LW · GW
There are certainly cognitive tasks that other animals can do that we can't at all or as well, like dragonflies predicting the trajectories of their prey

That's fine, but those aren't nearly as powerful. Language was a big factor in humans taking over the world, predicting the trajectory of whatever dragonflies eat wasn't and couldn't be.

Anyway, to the larger point, I actually don't have a strong opinion about the intelligence of "humans without human culture", and don't see how it's particularly relevant to anything. "Humans without human culture" might or might not have language; I know that groups of kids can invent languages from scratch (e.g. Nicaraguan sign language) but I'm not sure about a single human.

The point is that it is possible to teach a human language, and it seems to be impossible to teach a non-human animal language.

Comment by sil-ver on Might humans not be the most intelligent animals? · 2019-12-24T09:16:53.538Z · score: 1 (4 votes) · LW · GW

Isn't it the case that no non-human animal has ever been able to speak a language, even if we've tried to raise it as a human? (And that we have in fact tried this with chimps?) If that's true, why isn't that the end of the conversation? This is what's always confused me about this debate. It seems like everyone is ignoring the slam-dunk evidence that's right there.

Comment by sil-ver on Understanding Machine Learning (II) · 2019-12-23T19:24:38.101Z · score: 1 (1 votes) · LW · GW

I haven't. Would you say that it is good?

UML also includes the proof though – it hasn't skipped any important proof so far. I just didn't want to replicate it here, because I didn't feel like understanding the steps of the proof really helped my intuition in any significant way.

Comment by sil-ver on Understanding Machine Learning (I) · 2019-12-23T11:42:01.843Z · score: 1 (1 votes) · LW · GW

Thanks; fixed the second one.

On the first – I don't understand why correlation doesn't apply. "Spam" is a random variable, and whatever feature you show, like "length", is also a random variable – right?

Comment by sil-ver on Embedded Agents · 2019-12-23T08:44:13.702Z · score: 5 (3 votes) · LW · GW

Just saw this linked on SlateStarCodex. I love this style. I also think it's valuable to demonstrate that it's possible to have fun without dumbing down the content at all.

Comment by sil-ver on Understanding Machine Learning (I) · 2019-12-22T08:11:46.340Z · score: 3 (2 votes) · LW · GW

Right. I just took issue with the "unsaid" part because it makes it sound like the book makes statements that are untrue, when in fact it can at worst make statements that aren't meaningful ("if this unrealistic assumption holds, then stuff follows"). You can call it pointless, but not silent, because well it's not.

I'm of course completely unqualified to judge how realistic the i.d.d. assumption is, having never used ML in practice. I edited the paragraph you quoted to add a disclaimer that it is only true if the i.d.d assumption holds.

But I'd point out that this is a text book, so even if correlations are as problematic as you say, it is still a reasonable choice to present the idealized model first and then later discuss ways to model correlations in the data. No idea if this actually happens at some point.

Comment by sil-ver on Understanding Machine Learning (I) · 2019-12-21T22:16:15.149Z · score: 4 (2 votes) · LW · GW
the silent assumption that there are no spurious correlations in the dataset

Isn't that the i.d.d assumption?

We model the environment, which creates our labeled domain points (x,y) by a probability distribution D over X×Y as well as the i.d.d. assumption (not bolded since it's not ML-specific), which states that all elements are independently and identically distributed according to D.

If so it's not silent – it's a formal part of the model. The statements about PAC learnability are mathematical proofs, so there's no room to argue with those, there's only room to argue that the model is not realistic.

Although I admit I didn't mention the i.d.d assumption in the paragraph that you quoted.

Comment by sil-ver on Understanding Machine Learning (I) · 2019-12-20T19:40:38.061Z · score: 11 (4 votes) · LW · GW

Yes! It's in the second post, which is already (almost) finished. VC dimension was one of my favorite concepts.

Comment by sil-ver on We run the Center for Applied Rationality, AMA · 2019-12-19T20:29:39.650Z · score: 8 (7 votes) · LW · GW

What is your model wrt the link between intelligence and rationality?

Comment by sil-ver on 2019 AI Alignment Literature Review and Charity Comparison · 2019-12-19T17:40:38.968Z · score: 1 (1 votes) · LW · GW
Like, during the time that MIRI was non-non-disclosed (i.e. open), I don't think there was substantially more checking of their work than there is now. Most of academia and industry has/had no interest. There were LWers like Paul Christiano and Wei Dai and Stuart Armstrong that engaged, and I'm sad that these people aren't able to engage with the present work. But at the time Paul and Wei were basically saying "I don't get why this is going to work out" so it's not like MIRI could start getting much more negative feedback, unless Paul and Wei were going to say "This obviously fails and I can prove how," which I assign little probability to.

However, the open Philanthropy project did have people evaluate Miri's work, and they ended up sending them a substantial donation because they liked the Logical Induction paper – unless I'm misremembering how it went down.

Comment by sil-ver on Open & Welcome Thread - December 2019 · 2019-12-18T18:22:09.710Z · score: 8 (4 votes) · LW · GW

80.000 hours recommands a Machine Learning PhD as a high-impact career path – can help understand the most important technology, and a powerful entry ticket into many relevant jobs. And ML jobs are often well-paid, so they allow earning-to-give as a backup option.

I don't really like the Machine Learning institute at my university, but the professor who leads the institute for information security (whom I do like) has offered to combine the two fields. He said they're primarily interested in "privacy-preserving ML".

How valuable would such a mixed PhD be, compared to a pure ML one? And also, how much does the prestige of the university matter? Should I try to get into the most prestigious one in my country, even if it takes longer? I really struggle to approach these questions. I'm also unsure how much I should care about how I feel about the professor.

Comment by sil-ver on Open & Welcome Thread - November 2019 · 2019-12-17T10:50:42.373Z · score: 1 (1 votes) · LW · GW

Only made some fairly halfhearted attempts at that one; it didn't really lead to anything.

Comment by sil-ver on Open & Welcome Thread - November 2019 · 2019-12-03T09:07:43.707Z · score: 1 (1 votes) · LW · GW

I did. It's hard to quantify how much, but I'm falling asleep in < 20 min more reliably and am less tired during the day. I also remember dreams much more frequently, which is a welcome change.

Comment by sil-ver on Effect of Advertising · 2019-11-26T19:11:07.230Z · score: 2 (2 votes) · LW · GW

Advertisement is a component of the cost of a product, right? Some percentage of the total cost associated with producing and selling a product is ads. If they're no longer allowed, that component disappears.

I'm not saying this leads to a net decrease in cost, but it is a factor which leads to some decrease in cost, so if you want to argue that a net increase in cost takes place, you have to argue why the decreased competition matters more than the direct savings.

Comment by sil-ver on Open & Welcome Thread - November 2019 · 2019-11-24T17:19:38.221Z · score: 1 (1 votes) · LW · GW

I've gotten my hands on melatonin now, inspired by your comment. I've found a site that actually shipped it from Poland, which I believe isn't even illegal and definitely won't get me into trouble. The cost is still minimal. So far, it seems to help. Thanks again.

Comment by sil-ver on Insights from the randomness/ignorance model are genuine · 2019-11-14T18:10:48.639Z · score: 1 (1 votes) · LW · GW
That doesn't seem to follow, actually. You could easily have a very large universe that's almost entirely empty space (which does "repeat"), plus a moderate amount of structures that only appear once each.

Yeah, nonemptiness was meant to be part of the assumption in the phrase you quoted.

And as a separate argument, plenty of processes are irreversible in practice. For instance, consider a universe where there's a "big bang" event at the start of time, like an ordinary explosion. I'd expect that universe to never return to that original intensely-exploding state, because the results of explosions don't go backwards in time, right?

We're getting into territory where I don't feel qualified to argue – although it seems like that objection only applies to some very specific things, and probably not to most Sleeping Beauty like scenarios.

Comment by sil-ver on Insights from the randomness/ignorance model are genuine · 2019-11-14T10:09:59.541Z · score: 1 (1 votes) · LW · GW

But by number of bits, which is what you need to avoid repetition.

Comment by sil-ver on Insights from the randomness/ignorance model are genuine · 2019-11-14T10:04:27.941Z · score: 1 (1 votes) · LW · GW

You mean P(monday)? In that case it would be different although have some similarity. Why is the description length of the monday observer moment longer than the tuesday one?

Comment by sil-ver on Insights from the randomness/ignorance model are genuine · 2019-11-14T10:01:04.016Z · score: 1 (1 votes) · LW · GW

I actually knew about UDT. Enough to understand how it wins in Transparent Newcomb, but not enough to understand that it extends to anthropic problems.

Comment by sil-ver on Insights from the randomness/ignorance model are genuine · 2019-11-14T09:59:41.884Z · score: 1 (1 votes) · LW · GW

The solution to this kind of thing should be a wiki, I think. If the LessWrong wiki were kept up to date enough to have a page on anthropics, that would have solved the issue in this case and should work for many similar cases.