41–50 of 147 posts
thinc.by the creators of spaCy https://github.com/explosion/thinc
nnabla by Sony https://github.com/sony/nnabla
LibNC by Fabrice Bellard https://bellard.org/libnc/
Dlib dnn http://dlib.net/ml.html#add_layer
> almost 9000 GitHub stars I wouldn't say that 7500 stars is almost 9000 stars ;)
They are not over 9k yet but closing.
If anybody is dealing with procrastination watch George Hotz live streaming 10h straight working on this library [1][2]. Does he take some supplements to do this? There is even 19.5h stream [3]. Actually I have local obs setup to record myself, just instead of streaming I do recordings for my own inspection. Important part is to do the inspection after. It works wonders. [1] https://youtu.be/GXy5eVwnL_Q [2] https://m…
What do you do with your own recordings afterwards? How do they help you?
There is a problem however - I work on mac m1 and obs recordings take full 4 out of 8 cores so actually I am recording only when I notice I am starting to procrastinate. All recordings I remove afterwords to save up space. Obs is turned on all the time though.
I wanted to use obs-ndi to combine output from another laptop, but I have some issues with it so I just record mac atm. I also have powerfull desktop on the side and can ssh between all those by name, but desktop is noisy so it's off most of the time. Also there is raspberry pi with simple script with which I can turn on desktop remotely via Wait On Lan udp packet, dns handled via https://www.noip.com with which my router has an integration, but I actually never used it. I've done this setup to justify purchasing this powerful desktop in the first place :) humble brag, I know.
Here is screenshot of obs recording with sneak peak of my room https://imgur.com/a/m92R7Bx
Earlier quoted context omitted.
If it's not Adderall I don't know. But, if I've ever focused for that long it's been because of Ritalin or Adderall.
Is 10 hours really _that_ strange? You are (hopefully) focusing 8 hours "straight" during work _every day_. If you watch Hotz's streams he takes small breaks to talk with chat and to meme around (just like everyone else during their work days) and he eats lunch and whatever (again just like everyone else). What I'm trying to say is that Hotz's isn't a superman on Adderall he is just working on stuff he is excited abo…
I refuse to believe that 8 hours straight focus every day is common.
I have about 4 - 6 hours of really focused, deep work focus available. 6 hours if I am really interested in the project and 4 hours for normal days. The rest is doing low focus work like writing mail, planning ahead, attending workshops, reading up on updates for relevant libraries, reading documentation etc.
Earlier quoted context omitted.
If it's not Adderall I don't know. But, if I've ever focused for that long it's been because of Ritalin or Adderall.
Is 10 hours really _that_ strange? You are (hopefully) focusing 8 hours "straight" during work _every day_. If you watch Hotz's streams he takes small breaks to talk with chat and to meme around (just like everyone else during their work days) and he eats lunch and whatever (again just like everyone else). What I'm trying to say is that Hotz's isn't a superman on Adderall he is just working on stuff he is excited abo…
If anybody is dealing with procrastination watch George Hotz live streaming 10h straight working on this library [1][2]. Does he take some supplements to do this? There is even 19.5h stream [3]. Actually I have local obs setup to record myself, just instead of streaming I do recordings for my own inspection. Important part is to do the inspection after. It works wonders. [1] https://youtu.be/GXy5eVwnL_Q [2] https://m…
What's the file size for your recordings? 5 hours of 720p would be huge.
My plan is to make this obs-ndi plugin work on ubuntu, so I will be able to record on ubuntu to take the load off of mac which is my primary laptop.
PS. I forgot to read obs-ndi instructions properly, it works ok so now I can delegate regording to second laptop
How is it compared to JAX? After TensorFlow and PyTorch, JAX seems very simple, basically an accelerated numpy with just a few additional useful features like automatic differentiation, vectorization and jit-compilation. In terms of API I don't see how you can go any simpler.
JAX is a DSL on top of XLA, instead of writing Python. Example: a JAX for loop looks like this: def summ(i, v): return i + v x = jax.lax.fori_loop(0, 100, summ, 5) A for loop in TinyGrad or PyTorch looks like regular Python: x = 5 for i in range(0, 100): x += 1 By the way, PyTorch also has JIT.
>>> import jax
>>> def a(y):
... x = 0
... for i in range(5):
... x += y
... return x
...
>>> a(5)
25
>>> a_jit = jax.jit(a)
>>> a_jit(5)
DeviceArray(25, dtype=int32, weak_type=True)If anybody is dealing with procrastination watch George Hotz live streaming 10h straight working on this library [1][2]. Does he take some supplements to do this? There is even 19.5h stream [3]. Actually I have local obs setup to record myself, just instead of streaming I do recordings for my own inspection. Important part is to do the inspection after. It works wonders. [1] https://youtu.be/GXy5eVwnL_Q [2] https://m…
It's probably the fact he has an audience. I can't speak for him, but that'd sure as hell light a fire under my ass—or at least significantly reduce procrastination.
Also, I find in periods where I've worked ~17 hours straight that the tiredness calms by brain to the point I'm normal and makes focus easy, albeit difficult in a different way due to fatigue. There's a weird drone zone there that's nice. Not something to make a habit of, though.
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I'm no expert but can you show how those techniques can be used to solve the same problems NNs can? Like SOTA image recognition, chess / go, STT, TTS etc?
>I'm no expert but can you show how those techniques can be used to solve the same problems NNs can? Sentiment analysis, classification.
Classification depends on the problem (and mostly the datasize). Boosting is certainly competitive on tabular data and widely everywhere I've worked.
No one talks about it (except on Kaggle) because it's pretty much at a local maximum. All the improvement comes from manual feature engineering.
But modern techniques using NNs on tabular data are are competitive with boosting and do away with a lot of the feature engineering. That's a really interesting development.