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wouldn't i be faster to use ram as a swap for vram?


I was able to reproduce it with alexa app on Android


There was also a trebuchet appearance during Ukranian riots in 2014: https://www.youtube.com/watch?v=IEY4WG7P0NQ


It's funny that the letter itself uses 70 char lines


Visuals are amazing, as always! I've recently learned that 3b1b has his own animation library. https://github.com/3b1b/manim I wonder if there are any manim art out there :)


> In contrast, running the neural network takes 5μs (twenty thousand times faster) with only a small loss in accuracy. This “approximate function inversion via gradients” trick is a very general one that can not only be used with dynamical systems, but also lies behind the fast style transfer algorithm.

Very interesting! Follow up question -- how would you choose the network architecture?


Since the network only acts on a small portion of the entire system, we can constrain it in such a way that dramatically simple NNs work just fine.

`FastChain(FastDense(3,32,tanh), FastDense(32,32,tanh), FastDense(32,2))` (from [0]) would take three inputs from your basis, run it through one hidden layer and provide you with two trained parameters.

This [1] example uses two hidden layers, its one of the more complex solutions I've seen so far. To move to this complexity from a simpler chain, we first make sure our solution is not in a local minima [2], then proceed to increase the parameter count if the NN fails to converge.

[0] https://diffeqflux.sciml.ai/dev/FastChain/ [1] https://github.com/ChrisRackauckas/universal_differential_eq... [2] https://diffeqflux.sciml.ai/dev/examples/local_minima/


Maybe this jupyter book can be used as a blog?


wow, it somehow looks a lot better than previous GAN paintings I've seen. And there are weights of this network, shared by the author in twitter. https://mega.nz/#!TCgSVCTa!ZmcV381soxyqiQyHO4p60F5ogoHcaO1Pq...

StyleGAN2 takes 512 dimensional vector as an input. Would be neat to attach some physical input device, like a matrix of dials... And encode your own painting with it :)


If there are no graphs or formulas in the book, I prefer to use a text-to-speech engine. Over the years I've become able to listen to it on great speeds. It feels easier to comprehend spoken language.


I listen to books and articles via text to speech application for over 3 years. Currently i am able to listen comfortably at 3.6x speed. I don't know how to test comprehension through. My friend says i might be able to think faster than other people, because of superhuman listening powers i now posess. Don't know how to test that either.


I have made a browser extension that helps me put every webpage I read through TTS. I also get current word highlight on text and automatic page scroll. It helps me focus twice as good, I can't even stand reading without TTS support any more.

Unfortunately I can only stand one voice - "Alex" from OSX, at about 1.3x ... 1.5x speed. Other voices I find irritating. I'm following the new WaveNet TTS voices with great expectations, but they don't seem to come near my laptop.

WaveNet: https://deepmind.com/blog/wavenet-generative-model-raw-audio...


Mind sharing what application you‘re using?

Is there something open source that works great?


I use voice aloud reader for android. It is has awful ux but allows up to 4x speed.


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