Dzugaru

The idea that we may be living in a virtual reality someone created is a disturbing one. It doesn't matter if objects around us are fundamentally real or simulated - that's true. What matters is our minds may be simulated too. What if that simulation has some deep flaws in it? What if there are things we could never understand no matter how we try because of that?

"Stuck"? Cmon, imagenet winning deep nets are 5 (five) years old. Give it time.

Benchmarks are tricky and hard to find for dlang as its not that popular, but I have common sense to back that statement. Dlang garbage collector is really really slow for now [0], and C# has a very fast GC and overall is almost as fast as zero-overhead languages like Rust or C++ [1]. So, its reasonable that for anything that involves GC (we all can agree that web server does) D is not that fast as manual memory management languages yet.

[0] https://olshansky.me//gc/runtime/dlang/2017/06/14/inside-d-g...

[1] http://benchmarksgame.alioth.debian.org/u64q/binarytrees.htm...

ASP.Net MVC is basically this, but much more mature and feature packed :) And C# is no slower than D.

I'm pretty sure noone on planet Earth has a good understanding of AI yet. I stopped reading about "what AI is, what AI isn't" completely.

> Almost always there is no easy way to install several libraries of the same name but different versions in parallel.

How is this possible is beyond my comprehension. Someone, anyone break something and I have no standard way to bypass "dll hell" (putting space problems aside)? what the actual f.

Try googling "go" instead of "golang" then. Try "dlang dub" after that. Thanks.

Its because D has way less developers, support and, consequently, way less hype, than a language backed by one of the biggest world corporations in existence.

Anyway, care to elaborate whats wrong with excellent build/package/dependency system in D called Dub? Never had any problems with it.

This is what OP project is, no?

Two people see cool sideproject in Go, his thoughts "damn this looks good, I need to learn Go", my thoughts "Whyyy you do this in Go and not D? Simplistic Go has no strong sides here! Why nobody promotes my favourite language with things like this, it deserves hype no less!"

Few of these, honestly, benefit one man side projects. If you want to learn Go (for whatever reason) its fine, but otherwise I personally would prefer more expressive and less dogmatic language.

I can't help it but I can't find any reason to consider this as having > 0 information. You are absolutely forced and 100% expected to do this in a situation now, right?

I, honestly, find this very disturbing (black mirror way), regardless of my opinion on the matter at hand.

I've always thought that functional programming is about structuring your program in functions and their composition (as opposed to classes) - nothing to do with immutability either.

As for JS, I've read "Javascript: The good parts" one day and realized that I can do everything I want using just functions and closures - it's really elegant imo. (even use this approach in Python sometimes)

> how many people can get into a train

Can't speak for everyone, but I'd turn away and walked out the instant I hear this or similar BS (which is totally unrelated to "approaching new problems" or "stress management" in programming at least)

In my experience, D is like more powerful and feature-packed C#. It doesnt impose any limitations on you and your coding style/paradigm and strives to be "the one to rule them all" tool which has everything and can be used for everything from scripting to systems programming (when stdlib will be more @nogc friendly).

And yes, templates are so much better in D than in C++ or in C# :)

D is the most promising "one to rule them all" languages for me, given it's expressive power, speed, compilation speed and support for multiple paradigms. That said, D severely lacks manpower in its development.

I'd like to port author's effort to Windows, but I don't have OS-level programming experience, so I don't even know what are the differences and how they affect GC algorithms described.

That's quite a bold promise.

I wish I knew the Functional Way :)

You can also make free games just for the challenge and fun and getting some hundreds of people to play it is easy for web-based games.

Yes.

I thought AlphaGo is trained in an adversarial manner already (it plays against itself).

I'm working in the field (and winning contests) without a bachelor. As was said here [0]

"Overall, machine learning systems can be thought of as a machine learning core — usually an advanced algorithm which requires a few chapters from Ian’s book to understand — surrounded by a huge amount of software engineering."

[0] https://blog.gregbrockman.com/define-cto-openai

So that's what I mostly do - write code, try new ideas :) Surely, I had to refresh my knowledge in some areas like probabilities, and have a general understanding how math works, but anyone can do that.

Inference (forward pass) in convnets is really cheap even in floats, there are some awesome hardware like NVidia Jetson and most deep learning framework (i.e. Caffe) support it right out of the box. So we were doing realtime inference in embedded for years now, what am I missing?

If you don't HS because of RNG, try DireWolf games, namely Eternal.

Computers are far better now in solving complex tasks widely considered as requiring intelligence like video captioning and speech recognition, automatic driving and playing complex games. The change is due to hardware engineering that enabled enormous computing and data acquision/storage power compared to 1990s and a possibility to conduct machine intelligence experiments at unprecedented scale and speed which lead to better algorithms.

If, instead, you want to know when or if AI will match human intelligence or become self-consciuos - sadly no one knows that. We may be "advancing" in totally wrong direction.

I'm doing ML in Python 2 and I can't see a single reason to move to Python 3. Every article is about strings, but in fact I needed to work with Unicode once (mostly doing computer vision tasks, but once trained a RNN on a book in my native language just for fun) - and I don't remember ANY problem with it in Python 2.

So, why should I bother migrating? I moved to C# 7 instantly and never looked back, for example, because it has tons of stuff. But the only thing I hear about Python 3 is "it's so much better!!!111" and "strings, you need it".

I bet images like Neural style transfer are boring to artists just like ML poems :) Actual digital art is no less complex [0]. That aside, it would be interesting to look at ML model used, all I've seen were simple ones like hidden markov chains for the next letter, but hidden state is managed by RNN. You need to learn to "grasp" some underlying meaning if you want more than a semi-random word salad and if this can actually be done without building a strong AI in the process :)

[0] https://www.artstation.com/artwork/0ogb8

Online computing power is not the same as your own - it's like taxi vs your own car. You can't do what you want when you want. Turned on your Amazon machine? No sleep till you fix the bugs and load all GPUs :) Every "downtime" costs. I, personally, find it very disturbing and despite the fact my employer pays for my Amazon time I often prefer my laptop with GeForce 840M :)

> what is so off-putting about these types of mistakes?

Basically when I see something like this I involuntary start thinking: "Is it really a typo? Or is it the writer doesn't understand what he is writing about, because he cannot explain it to me in a clear and precise way?". Maybe this "BS filter" I have is a bad thing for me :(

About writing articles - I think one shouldn't worry about audience knowing more about a subject - it's inevitable, and it's what discussions in comments are for. So, errors due to not knowing something are ok, I think. Other errors can easily be corrected by proof reading (by a friend or by oneself after a day). That what I would do if I actually decided to start a blog :)

> The real valued zeta function is given for r and n, two real numbers

followed by a function of one real variable with an infinite sum of expressions containing integer r.

Sorry, but little things like these completely put me off in math articles.

Are DL-based reinforcement learners that observe the environment and make decisions a "mere pattern recognition" too? What is different about "true" intelligence then? What is major breakthrough? Self-consciousness?