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\begin{document}

\title{Setups:~Janelle Shane, research scientist, neural network trainer}



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  \date{May 07, 2024}


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This document was originally posted September 07, 2017
at~\emph{\href{https://usesthis.com/interviews/janelle.shane/}{Uses
This}~}and is distributed under a
\href{https://creativecommons.org/licenses/by-sa/4.0/}{CCBY-SA 4.0
license}.

\subsection*{Who are you, and what do you
do?}

{\label{522740}}

By day I'm a research scientist at a small R\&D company. I do
holographic and other kinds of liquid crystal laser beam steering.

In my spare time, I also train neural networks to generate entertaining
nonsense. I run a blog
at~\href{http://lewisandquark.tumblr.com/}{lewisandquark.tumblr.com}~where
I've trained neural networks to generate paint colors, cookbook recipes,
and even guinea pig names.

\subsection*{What hardware do you use?}

{\label{164789}}

I'm using a~\href{http://www.apple.com/macbook-pro/}{2010 MacBook Pro},
with big dents where I dropped it twice. The screen's once-round corner
is now polygonal, and the case near the hard drive is now crumpled. The
second impact disturbed the connections between the body and the screen,
and produced weird teal stripes over everything. I tweaked the color
balance until the stripes went away, and now the display looks normal
except for everything that used to be black is now pulsating a deep
demonic red. The battery life is approximately one hour, and maybe 15
minutes if I'm running a neural network. It's got a GPU, but it's too
old to run~\href{https://en.wikipedia.org/wiki/CUDA}{CUDA}, forcing me
to do CPU-based computations instead. So I'm thinking of maybe getting a
new laptop one of these years.

I now run bigger datasets on~\href{https://aws.amazon.com/}{AWS}~(Amazon
Web Services), but still prefer to run the smaller lists of names on the
MacBook Pro.

\subsection*{And what software?}

{\label{482607}}

I do my work with recurrent neural networks, which are machine learning
frameworks that can learn to imitate input datasets. Unlike traditional
programming where a programmer figures out the rules and teaches them to
the computer, with neural networks the programmer gives a dataset to the
computer and tells it to figure out its own rules. The process is
similar in many ways to how people learn - and the earliest neural
networks were designed for studying the workings of biological brains.

The framework I started out on is
a~\href{https://github.com/karpathy/char-rnn}{char-rnn}~(character-based
recurrent neural network) programmed
in~\href{http://torch.ch/}{Torch}~by Andrej Karpathy. I still use this a
lot for the smaller datasets, because I like how simple it is to sample
from old checkpoints, or to change the temperature during sampling, and
it's lightweight enough to run on the 2010 Macbook Pro's CPU.

For bigger datasets, I like
the~\href{https://www.tensorflow.org/}{TensorFlow}-based char-rnn that
Chen
Liang~\href{https://github.com/crazydonkey200/tensorflow-char-rnn}{has
implemented}. It can take advantage of the AWS's GPU acceleration, and
what really sets it apart from the other tensorflow char-rnn
implementations is its flexibility in letting me go back and look at
earlier points in the neural network's learning process.

I've also been experimenting with the visual neural network framework by
Prof. Mark Riedl of Georgia Tech.

\subsection*{What would be your dream
setup?}

{\label{624427}}

One day, I'd like to have a MacBook Pro for everyday use and a cheap
Linux machine with a decent GPU at home to run calculations. AWS is
handy, but I always have to remember to shut down my session after my
calculations are done. An iPad would be nice to use as a lab notebook,
but it would make an even better travel computer if it could run regular
programs like
the~\href{http://www.microsoft.com/surface/en-us/support/browse/surface-windows-8-pro}{Surface
Pro}~can. Maybe one of these days.

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