quill VS Pytorch

https://github.com/Kobo-InkBox/inkbox#readme appears to be the non-ddns.net version, and is GPLv3

Is it really android? that's bad. It will be also propably impossible to port to inkbox

Handwritting notes more efficient than hunting down individual characters on keyboard (aka not a touch typist).

Stenograpy much more efficient than standard keyboard typing.

Likely same reason student(s) hasn't put together open source smart glasses displaying "talk" as text to allow for real time user hightlighting (for what user wants to capture/'note').

This is way more efficient than writing/typing, as can also capture/note non-text presentations. aka inkbox[0]/epireader[1], soli[1] (finger gesture/sign the key(s)), diy open source glasses[3]

[0] : https://github.com/Kobo-InkBox/inkbox

You might be interested: https://github.com/Kobo-InkBox/inkbox

InkBox

inkbox for kobo e-readers is great. It should be possible to port to other e-readers too

if you want a better reader, consider plato or koreader one click packages from niluje: https://www.mobileread.com/forums/showthread.php?t=314220 or inkbox (https://github.com/Kobo-InkBox/inkbox). NOTE: i don't run any of these, but have tried KOReader and Plato in the past.

PyTorch (https://pytorch.org/)

torch is a package to manage tensors and dynamic neural networks in python (GitHub)

PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832

TensorFlow

TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.

> does PyTorch have a similar concept

of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...

fyi should work on most 40xx[1]

[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...

Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...

Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....

> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].

*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.

In PyTorch with @, dot() or matmul():