HN user
I'm the developer of an Android calculator, called Algeo [1] and I wonder which part of it that makes it feel like slow/not snappy? I'm trying to constantly improve it, though UX is a hard problem.
[1] https://play.google.com/store/apps/details?id=com.algeo.alge...
Pytorch and tensorflow is pretty big. It implies all state of the art research code is not written in Julia, so it is a non-starter for any neural network based project.
Because it only increases high single digit each release. If they keep up the 10% improvement for the next 10 release, we will reach a speedup of around 2.5 times. That's very small, considering how Python is like 10-20 times slower than JS (not even talking about C or Java like speeds).
I always wondered where the integral sign was coming from. This gives a very simple explanation: it's just the letter 's', the shorthand for sum!
This rings so true with me. I have a side project [1] that I try to promote and it always feels hard. Where do I start? Should I post comments in random subreddits? Should I write blog posts that may nobody read in the end? Start doing ads? I think having the multiple options kinda freezes me and it is so hard to start doing something.
Congrats! It's about the same I make with Android with my app (a graphing calculator) [1]. Everyone says on Android you can earn less, I'm curious what's your experience will be.
I don't really get the first part of your comment. You say an NN is "just" compression + kNN and does no representational learning. But finding a compression (a transformation in other words) that makes kNN feasible on the data is exactly what people mean when they say it finds a hidden representation. It is a highly non-trivial task: e.g. simple distance in pixel space between images would get you useless results.
Slightly related: I got the first C compiler restored and ported to modern C [1]. It runs on Linux and can call libc functions, though it is restricted to 32bit mode.
Actually, MobileNetV3 is a supporting example of the bitter lesson and not the other way round. The point of Sutton's essay is that it isn't worth adding inductive biases (specific loss functions, handcrafted features, special architectures) to our algorithm. Having lots of data, just put that into a generic architecture and it eventually outperforms manually tuned ones.
MobileNetV3 uses architecture search, which is a prime example of the above: even the architecture hyperparameters are derived from data. The handcrafted optimizations just concern speed and do not include any inductive biases.
Back of a napkin calculation: showing OP 100 ads of blinds probably costs 0.1$ in the US. The cost of a blind is 100$ (I have no idea, don't live in the US). So if the probability of buying a second blind is at least 0.1% it was worth running the campaign.
The fact is, online ads are super cheap.
As others said, the active number of downloads is way lower (50k). Even then, I'm pretty bad at marketing and have no idea how to grow it or optimize the monetization.
It seems from 10 ideas 9 doesn't work and even the 10th brings only modest results.
I have an android app (https://play.google.com/store/apps/details?id=com.algeo.alge...).
It brings in right around $500 a month. It is fun to develop, especially that I can dabble into frontend and UI design which is quite far away from what I'm doing daily.
Interestingly, it used to bring in much more but the heydays of apps are over.
There is a blogpost linked in the annotations: http://jeanmariechauvet.com/papers/curttrig.html
That's true for all software development. In seven years most of your team is replaced.
I remember my school ran a contest where you had to find obscure information on the net. Things like when the inventor of the saxophone was born? You had to submit an URL so using the library was not an option. It was insanely hard, nowadays it's just one wikipedia click away.
I wonder how much of those shares can BlackRock/etc actually sell. BlackRock has many index funds GME part of so they must hold on to those shares
which is all illegal and there is no indication that was happening with Gamestop
Why would shorting Gamestop mean making it to go bankrupt? The falling stock price of a company doesn't cause a company to go bankrupt, the causality is in the other direction. Putting downward pressure on price is useful only if you want to do a hostile takeover.
Also, don't card companies pay net30/60? So even if customers were able to pay their orders, Robinhood only receives the money in 30 days but has to pay to the clearinghouse in two days. That would wreck RH in a volatile period like this.
Schrödinger's stock price
What GP meant is that after 5 years, you are just solving the same puzzles again and again.
It seems it is Python. The author specifically mentions an upgrade to Python 2.7
That's quite funny sentiment: basically you are saying the only reason for some people to use Linux if they are forced to use it by some library. An operating system shouldn't rely on that, if it wants to be truly general purpose.
That must have been really long time ago, I remember having no problem dual-booting XP with linux.
I think they also need the historical rules kept for whatever reporting/cross checking it is needed. So essentially they would have to rewrite the rules of the last 40-50 years.
It's time consuming and that is money (granted, Elsevier still gets more money than what is paid to editors)
probably the memory requirements mean that you do need (multiple) V100s though
My tip is not to use custom styling for buttons/text/etc just use the default Material design. It is already pretty nice, certainly better than what a non-designer can come up with. If you are interested in details, check out the design guidelines at https://material.io/, they cover a lot of stuffs from colors to padding sizes.
Congrats!
+1 taking heavy inspiration from other places gives a huge headstart