tmerr

Isn't Watson a question answering system? I don't think it's specialized for image recognition.

It seems like you've got it backward. Kazakhstan is not making the internet more secure. They're requiring citizens to install something (their own root security certificate) that compromises the security of https. The result is that their government can eavesdrop on all traffic, encrypted or unencrypted. That's the story anyway.

It sounds reasonable that fiber could reduce the rate of aborption of sugar. But I lose you when you start talking about sugar highs. I thought that was dispelled as a myth after a number of placebo controlled studies.

Any feature you remove from the API will be replaced with a python mechanize script that does the same thing but less efficiently.

Regardless of what you call the universe, we already know 1. Everything we know about it comes from sensory input, and 2. That sensory input's production can be modeled mathematically. But it's hard for me to make sense of what author really means by the claim "the universe is math". He claims after pulling away notation math is "A set of abstract entities with relations between them". Great! But then again... any idea I can conceive of can be said to be abstract entities with relations between them. That's an awfully vague definition. Then it's as if he fills in the void with baggage from his subjective understanding of mathematical structures (object movement is like 4 dimensional spaghetti). It's an interesting read but it seems like he just wants his idea of the universe to be more literal than it is.

Though you may have read the title as "game written in webgl" I'm pretty sure it's meant to be read as "game using webgl". My guess is you and frik read it using the former interpretation while others used the latter.

I think users were pissed off because of the lack of transparency. No one knew what the admins were deleting. It was up to the community to find out which subreddits were banned and why. Further the admins never logically explained their decisions, for example, to ban fph over srs. From the outside it seemed like an arbitrary power trip. And for what? Reddit's moderation system is perfect: let users form their own communities and moderate them as they wish. Some of the communities will be terrible but that's the beauty of it; you don't have to go to them. This system is what let reddit grow to the size it is today. While hackernews takes a different approach (moderation at the admin level isn't unusual) that is only manageable for a site of a smaller size.

Listening again in context you're 100% right! Disregard my previous comment.

Russel makes a mistake at 30:00 when he says computers are "totally unable to play checkers". Excerpt from J Schaeffer et al (2007). Checkers is Solved:

>In this paper we announce that checkers has been weakly solved. From the starting position (Fig. 1, top), we have a computational proof that checkers is a draw. The proof consists of an explicit strategy that never loses — the program can achieve at least a draw against any opponent, playing either the black or white pieces.

Not the focus of the talk, just thought I'd point it out.

Not to mention there's a game of whack-a-mole going on where similar subreddits have been banned including fatpeoplehate2, 3, 4, 5, 8, and 9.

I have finite attention. Attention (time and effort) is probably more important to my learning than the quality of my teacher. Without attention you fail. With infinite attention you get a perfect grade.

When you take a hard course it consumes a disproportionate amount of attention. Even if the teacher is bad at his/her job a harsh grading scheme will drive you to spend hours in the library. You will learn a lot because you are burning valuable attention; attention other classes can not have. So such a class necessarily good? Of course not. Not if the learning benefit is outweighed by learning opportunity cost.

So regarding the finding of the study

    The better the professors were, as measured by their
    students' grades in later classes, the lower their
    ratings from students.

I'm not confident that performance in later classes of the same sequence is a fair measure of learning; what matters to me is performance in ALL later classes. How do evaluations correlate then?

The summary says the main question addressed is whether synesthesia is a brain disorder. But that's a more loaded question than what the paper actually looks at. The paper only asks whether it's a neurological condition. Without too much nitpicking I'll say if you ask whether it's a disorder, you're accidentally pulling in a question of whether synesthesia causes suffering, which is irrelevant. All the cited paper investigates is whether synesthesia is detectable at all by physically measuring the brain as opposed to relying on subjective experience.

Aside I have to admit I am confused by the word "neurological". If a condition is neurological does that mean it is rooted in the nervous system (which includes the brain)? Is a condition that is rooted in the nervous system, but we do not yet know how to observe or study it, still "neurological"? That seems like the case for synesthesia.

If you're going to be pedantic at least do it well. Going by the dictionary definition of drug: "a medicine or other substance which has a physiological effect when ingested or otherwise introduced into the body" both caffeine and cannabis fit the bill.

>We both got horrible grades in high school despite having the intelligence to do better

I'm not sure that's true, other sites report he got a 4.0.

http://www.notablebiographies.com/news/A-Ca/Carmack-John.htm... http://www.statemaster.com/encyclopedia/Carmack

I don't see why "weather forecasting" is similar to "brain simulation" in difficulty. The comparison would be more valid if the problem were "brain forecasting", that is to build an AI that would behave exactly the same as a particular human, but that's an even harsher measure of intelligence than the turing test that I doubt anyone would take seriously. I'm not saying the brain's easy to simulate, it's just the analogy here seems shaky. Where is the source of exponential difficulty?

If you knew how the atoms were arranged in an animal simulating the animal's behavior would be as simple as simulating each individual atom. In practice that's not tractable but it shows that in theory, since the behavior of atoms is computable (blah blah quantum physics shut up), anything an animal can do can be simulated by a turing machine including will. Just because it's not simple to express in a programming language doesn't mean it not possible.

In short this article looks at aspects of programming and says if you're bad at each aspect you're probably bad at the sum of them. I'm not sure what the purpose is... you can figure out more directly whether you're a bad programmer by comparing the code you produce to that of your peers.

Aside from that the made up terms are annoying. It would be more readable if he used

  voodoo code => dead code
  bulldozer code => high cohesion subroutines  
  pinball programming => unreliable code

I can't think of anything good to say about this article.

>>the whole language is verbose: compare these 10 lines (https://github.com/andreaferretti/kmeans/blob/935b8966d4fe0d...) with this single line (https://github.com/andreaferretti/kmeans/blob/master/nim/alg...)

The Nim code's more concise in this case but the Rust code can be more clearly written:

  impl Add for Point {
    type Output = Point;
  
    fn add(self, other: Point) -> Point {
      Point(self.0 + other.0, self.1 + other.1)
    }
  }

The "type Output = Point" line isn't boilerplate, it makes it possible to define the result of an addition as something other than a Point. (Off of the top of my head I can't think of any use cases, but I'm happy with the capability personally).

On the topic of how representations relate to programming... if you have ever tried to express some tricky math in code you might have had a sense that it would be more clear if it were written out on paper with the proper notation. That's because mathematicians have streamlined their reasoning by deciding one day, well, I use the sum function a lot, let's call it Σ. Or I'd like to be able to recognize integrals from a mile away so let's call it ∫. Not to mention those symbols come along with a spatial organization: the lower limit of integration goes below, the upper limit goes on top.

Programmers can't easily streamline like this. Maybe there are multiple forces locking us in: the keyboard, text editor, and programming language. Sure, maybe the optimal way to write code is with a string of ascii characters arranged left to right top to bottom but I doubt it. So even in the visual-symbolic space there is unexplored potential.

I'm glad someone is out there tackling these assumptions and much more, I should keep an eye on his work.

On an unrelated note, his website is entertaining: http://worrydream.com/

Designing a mapping from a new language to machine code is easier than retroactively trying to map two languages together that were never meant to be. Especially if those languages are complex and ill-defined.

brainfuck.

I thought that was what he meant. Is there any sharp distinction between "interpreting" and "evaluating" in python that I am unaware of? I've always used the words more or less interchangeably. But now that I think about it that might be a little naive since I have no idea how it works under the hood

Adding a point to a size can give you a corner of a shape. You can have functions for scaling to aspect ratios, normalizing, and stretching. I don't see why any would be specific to one type or the other. In math you don't usually deal with points or sizes, you deal with vectors.

But admittedly conversion between Points and Sizes is not a pain point for most people. It's much worse when dealing with types that have the exact same purpose, just from different libraries.

I believe gw's intended notion of a data structure extends beyond Lists and Hashmaps. For example consider the following two structs.

  struct Point { int X; int Y; ... }
  struct Size { int Width; int Height; ... }

In either case the data structure is (int, int). But they're typed differently: one is typed as Point and the other as Size. This makes it very annoying to write functions that are compatible with both. Let's say we write

  AddThenSquare(Point A, Point B) {
    return new Point((A.X + B.X)*(A.X + B*X),
                     (A.Y + B.Y)*(A.Y + B.Y));
  } 

To make Size compatible with that function you need to either refactor your code so that both Point and Size adhere to the same interface, or alternatively implement conversion functions. The latter option is what C#'s .NET framework opts for where Point and Size are taken as parameters to each others constructors. But it doesn't scale. What happens when you use a third party math library with its own point implementation? Your number of conversion functions grow by n*(n-1) where n is the number of classes that need to be converted between. To be fair I think C# has technical reasons for not having an interface between Point and Size (structs don't play nicely with interfaces) but even if it was included it would still be a royal pain making sure all other math libraries adhered to the same one.

In practice it's rare anyone will have the foresight to put interfaces everywhere they're needed, and it's even rarer that programmers will use the same interfaces across libraries. It begins to sound like the "specialization within functions that inhibits and penalizes casual cooperation" that Alan Perlis was talking about.

At some point you start to wonder why the compiler cares at all what the name of the data is if the underlying information is the same. You could have dodged the headache altogether if you were in Python where a point is a tuple (x, y).

Still I'm not convinced static typing is to blame... it's more that the kind of static typing employed by Java, C++, C# is especially rigid.

Most good ideas I have surface after a break from coding, be it a walk, weekend, or night of sleep. Those ideas start depleting as soon my hands hit the keyboard, and once they're gone I enter full code monkey mode. When I'm conscious this transformation is taking place I usually hit up pen and paper or a white board, which can buy me extra hours. It probably comes out to about 50% of time planning, 50% coding, and as long as I don't spend too much time in the latter I can avoid getting burnt out. I figure if I have to try when coding I'm doing something wrong though it's sometimes unavoidable.

The article says it's based on "the first 500K tests completed" of http://vocabulary.ugent.be/wordtest/start

Then the sample is probably taken from internet dwellers who are interested in seeing how good their vocabulary is. I wonder if that's also why Paladin is so high up on that list.

Not all companies have as much power as Newegg to fight back. I'm guessing it does often make financial sense to just pay it, otherwise companies would have turned the tables already. I don't think it's a lack of long term thinking as much as it is a tragedy of the commons related situation.

Based on computing power alone you may be right, but human brains are idiosyncratic to say the least. While on one hand we are simple neural net algorithms, on the other we are dirty hacks woven together throughout evolution. Even given the former, if the latter lags behind AI will continue to feel distinctly unhuman.

I bet we'll produce a really interesting brain within the next ten years that doesn't seem human at all.

When you say there's more slavery now than there ever was I can't tell whether you're exaggerating or know something that I don't. As far as America goes, it seems like a stark difference between now and 150 years ago when 13% of the population consisted of slaves [0]. If you're referring to third world countries that's more understandable due to the number of young workers building products for wealthier countries.

[0] http://en.wikipedia.org/wiki/1860_United_States_Census

If you want something closer to what you'd expect of CS from a college check out MIT OpenCourseware, it should have everything you need for undergrad CS