
Facebook AI Research Team Open Source DeepMask and SharpMask - natthub
https://code.facebook.com/posts/561187904071636
======
said
Is there any way for those of us with average intelligence to contribute to
tools like this?

I know I'm a decent developer, but I feel entirely entirely inadequate to
participate in this enormous, scary world of AI.

~~~
dxbydt
fwiw, over 4 years ago, I quit a risk quant job at an investment bank and
joined Twitter. When I saw all the sophisticated ML systems they had deployed,
I asked the same question - How do I, a person of average intelligence with
zero exposure to ML, contribute ? Is there anything I can do to get involved?

The answer I got was rather unpleasant and won't please everybody. No you
cannot contribute. At least not in a direct meaningful fashion. You can be a
waterboy. So that's what I did for 2 years. I wrote a lot of ETL jobs using
custom Scala DSLs, that fed the input to these ML jobs. It was a total waste
of time. Sure I learnt map reduce and Hadoop and all that jazz, but end of the
day, I wasn't doing ML. I was doing ancillary tasks. These tasks no doubt have
some economic worth, because I was getting paid. But no company is going to
let you do the ML when they have 100s of ML PhDs on their payroll and you
aren't one of them. So you just do the data prep, or do ETL, or do data viz,
or crunch some numbers aka BI, and convince yourself you are doing real ML.
This went on for a while. Finally I couldn't put up with this farce and quit.
What worked for me personally was finding a very small company with a tiny
data science department, that was headed by an ML PhD who was ready to mentor
me, tell me which papers to read, get me to start working on my own papers,
get me to build ML systems for image recognition on company time, get me to
read textbooks and present topics...it was all quite painful and very
humbling, but I learnt a shit ton of stuff. So my frank suggestion is to be
brutally honest with yourself. You aren't going to get from here to there by
hanging around on coursera or writing ETL. This stuff is seriously hard. If
you want to make a genuine contribution, be willing to put in serious time -
and that means literally stopping whatever shit you are doing now as a
webdev/back-end dev/ETL dev/data-eng etc. Those ancillary tasks won't get you
anywhere. Buckle down and do the real deal. You'll thank yourself one day if
you did.

~~~
samsonradu
While I really appreciate the realism in your post, I wouldn't call
webdev/back-end dev shit though. After all, that's what brought us here in the
first place and are still heavily needed.

~~~
latch
Don't think he was saying that stuff is shit. I think he was using the word
the same way you might when saying "Boy, did I get a lot of shit done today!"

------
tectonic
Future Facebook AR goggles will float people's names above their heads,
replace billboard advertisements with live Facebook ads, and make people you
'mute' become invisible. It'll be a weird world.

~~~
azeirah
Black mirror?

~~~
timpark
For those not familiar, specifically the "White Christmas" episode:
[http://www.imdb.com/title/tt3973198/?ref_=ttep_ep1](http://www.imdb.com/title/tt3973198/?ref_=ttep_ep1)

For those who are familiar, new episodes are apparently arriving on Oct.21st.

A hackathon project inspired by White Christmas:
[http://jonathandub.in/cognizance/](http://jonathandub.in/cognizance/) (Brand
Killer)

------
iraphael
These seem to be the papers for DeepMask [1] and SharpMask [2]

[1] [https://arxiv.org/abs/1506.06204](https://arxiv.org/abs/1506.06204)

[2] [https://arxiv.org/abs/1603.08695](https://arxiv.org/abs/1603.08695)

------
minimaxir
NB: The libraries use Torch.

I'm still playing around with fasttext (which is _amazing_ btw) officially
announced last week so I'm surprised to see Facebook Research announce and
release another project so soon.

~~~
thewhitetulip
Could you share what you did with fasttext? It'd be great to see some examples
around the amazing tools being open sourced! I read that there are no
documentation comments, maybe they were removed?

~~~
minimaxir
For basic use, you can construct text vectors faster/better than
word2vec/doc2vec.

The Python package which serves as an API to fasttext
([https://pypi.python.org/pypi/fasttext/0.7.2](https://pypi.python.org/pypi/fasttext/0.7.2)
) is well documented, is constantly being updated, and is easy to use.

~~~
binarymax
Does/can fastText use GPGPU at all? I use a CUDA cbow word2vec [1] that is
really quick, and has served me quite well. Hard to know if switching to
something more accurate would be worth giving up the speed :)

[1]
[https://github.com/ChenglongChen/word2vec_cbow](https://github.com/ChenglongChen/word2vec_cbow)

~~~
minimaxir
No, fastText is CPU only.

------
dharma1
It would be nice to see results compared to other SOTA semantic segmentation
approaches like

[https://github.com/daijifeng001/MNC](https://github.com/daijifeng001/MNC)

[https://bitbucket.org/aquariusjay/deeplab-public-
ver2](https://bitbucket.org/aquariusjay/deeplab-public-ver2)

[https://arxiv.org/abs/1607.07671](https://arxiv.org/abs/1607.07671)

------
guelo
I feel less and less willing to upload personal photos to social media sites
where they will stick around forever attached to my identity while advancing
computer vision techniques extract more and more information from them.

~~~
dharma1
Not just social media sites - free searchable storage on Google Photos for
instance (as nice as it is), is in exchange for Google to mine the shit out of
your photos

------
spitfire
This is very timely for me. Right at the moment I'm working on image
segmentation for medical imaging.

If I can draft off tech developed to sell more ads to do some good I'm all for
it.

~~~
dawson
I have a colleague working on something similar, drop me an email and I'll
introduce you.

------
visarga
Is it safe to assume this release, as well as fastText are meant as PR for
hiring?

------
wibr
Looks very promising. Self-driving cars will need algorithms like this to
understand as much as possible of the environment that they see through the
cameras. I think currently things like those ropes that the shepherd is
holding in the picture are still very difficult to detect and classify
correctly but they could just as well be a line across the road, maybe with a
sign on it saying "closed".

------
achr2
How 'deep' are the networks used in something like DeepMask, and how does it
compare with the number of layers of the human brain?

~~~
sushirain
For example, ResNet from 2015 had 152 layers.

A real neuron takes in the order of 10ms to integrate and fire to the next
neuron. Many subconscious reactions take less than 1 sec, which leaves time to
a chain of length less than 100. Note that those neurons are not strictly
arranged in layers.

The human visual cortex has 10^12 synapses [1]. One popular 2015 deep learning
net (ResNet 152-layers) used 10^12 FLOPs to classify objects in one image (but
less weights.)

In terms of depth, we're there. In terms of breadth, it will take several
years. But the brain does things very differently. For example, it has top-
down signals during "prediction."

[1]
[http://www.ncbi.nlm.nih.gov/pubmed/7244322](http://www.ncbi.nlm.nih.gov/pubmed/7244322)

~~~
tkinom
"It will take several years."

A Noob question:

If it reaches the "breadth" of human brain, how close will that to the "Skynet
becomes self-aware" moment.

What would it tell us about human, our society after it study, analyze
millions, billions hours of FB, youtube videos?

~~~
visarga
As long as we do simple data processing, it won't become the dreaded Skynet.
When we stuck a Reinforcement Learning system on top, feed it with reward
signals and let it loose on the net or in real life robots, then it could
become intelligent and develop its own goals/interests. So the Skynet part
comes after reinforcement learning.

------
msie
Wow, the code is in Lua! Just a little surprised. Also I just read some
LinkedIn post on the dearth of Haskell education in schools. Always on the
lookout for more companies using Haskell and hoping in the field of AI,
machine-learning.

------
avvakum
SharpMask looks very similar to a year-old "U-Net"
[http://arxiv.org/pdf/1505.04597](http://arxiv.org/pdf/1505.04597)

~~~
mtourne
I thought that too. Just finished a kaggle competition involving segmentation,
like a lot of participant I used one form of U-net (my own implementation).

You can probably find a lot of u-net implementations from this contest. One
that performed really well [1]. It uses 'inception style' blocks feature
extraction instead of vgg. But otherwise pretty similar.

[1] [https://github.com/EdwardTyantov/ultrasound-nerve-
segmentati...](https://github.com/EdwardTyantov/ultrasound-nerve-segmentation)

------
ChristianGeek
What's the performance like? Fast enough to handle live video with a high-end
PC?

------
Happpy
Additional patent grand + bsd. Why not apache 2.0 or mpl 2.0?

------
swframe
Is there a link to get the code?

~~~
pmontra
Click the links in the "We're making the code for DeepMask+SharpMask as well
as MultiPathNet" line. They should have made them display more prominently.

They require to login to FB, then redirect to GitHub

[https://github.com/facebookresearch/deepmask](https://github.com/facebookresearch/deepmask)

[https://github.com/facebookresearch/multipathnet](https://github.com/facebookresearch/multipathnet)

