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Comment author: ChristianKl 27 August 2016 08:37:19PM 0 points [-]

Well not in current situation, but if you believe it then you that would teach you to avoid dealing with people who were not praised enough as children.

I normally don't have good information about the childhood of people I'm interacting with and the amount to which they were praised.

Comment author: PetjaY 27 August 2016 05:43:19PM 0 points [-]

Also hidden in hostile takeover is that on those assumptions (other buyer only buys if he gets all shares, your shares are worth less than 90$ if neither buys them) you could just buy 1 share for 102$, and get rest for 90$, no need for that complexity there either.

Comment author: MarsColony_in10years 26 August 2016 07:29:40PM 0 points [-]

nothing has 100% certainty, nothing can have a 0% uncertainty

That's my understanding as well. I was trying to say that, if you were to formalize all this mathematically, and took the limit as number of Bayesian updates n went to infinity, uncertainty would go to zero.

Since we don't have infinite time to do an infinite number of updates, in practice there is always some level of uncertainty > 0%.

Comment author: milindsmart 25 August 2016 04:12:25PM 0 points [-]

So someone has mentioned it on LW after all. Lots of singulatarian ideas depend heavily exponential growth.

Comment author: Rachelle11 25 August 2016 07:31:04AM 2 points [-]

Rachelle is an academic consultant at a community college in specializes in helping students with their academic problems, college stress and such. She also works part-time for an online dissertation help at dissertation corp. She’s also a hobbyist blogger and loves to do guest blogging on education or college life related topics.

Comment author: waveman 24 August 2016 11:40:19PM 0 points [-]

... and these decisions are difficult. You have very little, poor quality information, you are constantly lied to, you get very little feedback on how your decisions went, and any feedback you do get is delayed and noisy.

Comment author: waveman 24 August 2016 11:23:58PM 1 point [-]

The crazier, more-expensive, and more-difficult the method is, the more improvement it should show; craziness should filter out less-committed parents.


Your main point may well be valid; I think it probably is. But my daughter attended a Montessori kindergarten (but not a Montessori school) and I have read Maria Montessori's book. Neither seemed at all crazy to me.

The Montessori method is to engage children in activities which are challenging but not discouragingly so. Each activity produces a small increment in a skills. The children seem to become absorbed in the activities and find them very rewarding. In the adult world this would probably be something like "deliberate practice".

This idea of learning skills in small increments - in the sweet spot between "too easy and you learn nothing" and "too hard so you learn nothing and get discouraged" has wide applicability to children and adults. For example after almost a year of conventional swimming lessons and my daughter could not swim, I tried applying this method to swimming.

Swimming of course requires you to do several things at once. If you don't do them all you get a mouth full of water and learn very little.

I bought her a buoyancy vest and fins. She learned to swim with these very quickly. After a while we deflated the vest progressively and she again learned to swim that way, being now responsible for staying afloat. Then we took away the fins and she mastered that quickly. After a few lessons she was a confident swimmer. This was a very dramatic result. Back at the swim school they were surprised she could now swim, but were totally uninterested in how we achieved this.

The Montessori children seem to end up with excellent powers of concentration; that is certainly the case with my daughter. I did hear of a study that found that this was the most prominent effect of the Montessori schools. I would suggest they are worth looking at, but I would check that they are actually following the method.

Comment author: Lumifer 24 August 2016 03:36:49PM 0 points [-]

I think there is usually some transform that can convert your problem into a linear, or, in general, easy problem.

I don't think this is true. The model must reflect the underlying reality and the underlying reality just isn't reliably linear, even after transforms.

Now, historically people used to greatly prefer linear models. Why? Because they were tractable. And for something that you couldn't convert into linear, well, you just weren't able to build a good model. However in our computer age this no longer holds.

For an example consider what nowadays is called "machine learning". They are still building models, but these tend to be highly non-linear models with no viable linear transformations.

Comment author: gjm 24 August 2016 01:32:18PM -1 points [-]

I'm not sure "overreached" is quite my meaning. Rather, I think I disagree with more or less everything you said, apart from the obvious bits :-).

And that is the reason linear models are mathematically tractable : they form such a small space of possible models.

I don't think it has anything much to do with the size of the space. Linear things are tractable because vector spaces are nice. The only connection with the niceness of linear models and the fact that they form such a small fraction of all possible models is this: any "niceness" property they have is a constraint on the models that have them, and therefore for something to be very "nice" requires it to satisfy lots of constraints, so "nice" things have to be rare. But "nice, therefore rare" is not at all the same as "rare, therefore smart".

(We could pick out some other set of models, just as sparse as the linear ones, without the nice properties linear models have. They would form just as small a space of possible models, but they would not be as nice to work with as the linear ones.)

Of course nonlinear models don't have general formulae that always work : they're just defined as what is NOT linear.

If you mean that being nonlinear doesn't guarantee anything useful, of course that's right (and this is the same point about "nonapples" being made by the original article here). Particular classes of nonlinear models might have general formulae, a possibility we'll come to in a moment.

In other words, linear models are severely restricted in the form they can have.

I'm not sure what that's putting "in other words"; but yes, being linear is a severe restriction.

When we define another subset of models suitable to the specific thing being modelled, then we will just as easily be able to come up with a set of explicit symbolic formulae.

No. Not unless we cheat by e.g. defining some symbol to mean "a function satisfying this funky nonlinear condition we happen to be working with right now". (Which mathematicians sometimes do, if the same funky nonlinear condition comes up often enough. But (1) this is a special case and (2) it still doesn't get you anything as nice and easy to deal with as linearity does.)

In general, having a narrowly specified set of models suitable to a specific physical phenomenon is no guarantee at all of exact explicit symbolic formulae.

Then it will be just as "tractable" as linear models, even though it's nonlinear : simply because it has different special properties

No. Those different special properties may be much less useful than linearity. Linearity is a big deal because it is so very useful. The space of solutions to, I dunno, let's say the Navier-Stokes equations in a given region and with given boundary conditions is highly constrained; but it isn't constrained in ways that (at least so far as mathematicians have so far been able to figure out) are as useful as linearity.

So I don't agree at all that "largely there should be some transformed domain where the model turns out to be simple". Sometimes that happens, but usually not.

In response to comment by gjm on Selling Nonapples
Comment author: milindsmart 24 August 2016 06:20:10AM -1 points [-]

Thanks :) Can you elaborate a bit? Are you saying that I overreached, and that largely there should be some transformed domain where the model turns out to be simple, but is not guaranteed to exist for every model?

In response to comment by Lumifer on Selling Nonapples
Comment author: milindsmart 24 August 2016 04:59:20AM -1 points [-]

Sorry, hadn't seen this (note to self: mail alerts).

Is this really true, even if we pick a similarly restricted set of models? I mean, consider a set of equations which can only contain products of a number of variables : like (x1)^a (x2)^b = const1 ,(x1)^d (x2)^e = const2 .

Is this nonlinear? Yes. Can it be solved easily? Of course. In fact it is easily transformable to a set of linear equations through logarithms.

That's what I'm kinda getting at : I think there is usually some transform that can convert your problem into a linear, or, in general, easy problem. Am I more correct now?

Comment author: kpreid 22 August 2016 06:38:07PM 0 points [-]

Is there something not-paywalled which describes what the relevant old definitions were?

Comment author: PetjaY 22 August 2016 05:54:40PM 1 point [-]

Well not in current situation, but if you believe it then you that would teach you to avoid dealing with people who were not praised enough as children.

Comment author: milindsmart 22 August 2016 06:46:12AM *  -1 points [-]

Of course, "leading to global warming" is a subset of "harmful for the environment". Agreed on all counts.

Computing can't harm the environment in any way - it's within a totally artificial human space.

The others ("good") can harm the environment in general, but are much better for AGW.

Comment author: Romashka 21 August 2016 07:02:04PM *  0 points [-]

Why do you think "harmful for the environment" means "leading to global warming"? Lots of things are harmful for the environment. Drying swamps to make railroads harm it. Holidaying leads to decreased "old habitat" biodiversity. Building power plants on small mountain rivers leads to decreased biodiversity, too. Yes, these things are good for us. It just has no bearing on whether they are good for nature.

Comment author: milindsmart 21 August 2016 09:23:41AM -1 points [-]

Ah that particular idea of all human pleasures being harmful for the environment is pretty much religious. It's not at all what the impact is like.

Computing is basically blameless in the direct sense for global warming. We should probably enjoy it as much as possible. Electricity is good. Trains are good. Holidaying is good.

Airconditioning is bad. Air travel is bad. Short product lifetime is bad.

The situation is far more positive than some make it out to be. Even the direst climate change predictions necessitates drastic changes in some aspects of life.

AGW can't take away modern medicine or virtual reality from you.

Comment author: milindsmart 21 August 2016 09:11:45AM -1 points [-]

What do you mean by "abdicate control over the physical world"?

I fit the profile described here quite well. Feel free to ask (I know I'm 6 years late, but that's the point of internet forums).

Comment author: ThoughtSpeed 21 August 2016 08:11:58AM 0 points [-]

Did this ever get answered?

Comment author: ChristianKl 20 August 2016 10:32:42AM 0 points [-]

It would also be worthwhile to look at people who did those things and see how they ended up i.e., look from the other side.

How do you practically do that?

In response to comment by [deleted] on Science: Do It Yourself
Comment author: waveman 20 August 2016 10:19:39AM 0 points [-]

see how they got there

It would also be worthwhile to look at people who did those things and see how they ended up i.e., look from the other side.

For example if you look at rock musicians you are likely to find they neglected their studies and focused entirely on their music. But this seems to be a strategy with a pretty low expectation and very high variance in outcomes.

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