
Deep learning startup Skymind (YC W16) raises $3M, launches enterprise AI distro - vonnik
http://venturebeat.com/2016/09/28/deep-learning-startup-skymind-raises-3-million-launches-intelligence-layer-distribution/
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vonnik
Hey folks - one of Skymind'a co-founders here. My co-founder Adam Gibson has
been answering some questions I see. If you want to know anything about deep
learning in production, please let us know and we'll share what we've seen.

~~~
dragon_king
What are some typical use cases that you have worked on with your clients, and
can you give us an example of the impact it has had for a client?

~~~
vonnik
Typical use cases are:

* fraud and anomaly detection

* recommender systems

* predictive analytics (churn, forecasting)

* image recognition

With image recognition, we hit 98% accuracy on a recent project. Until a few
years ago, that was unheard of, and it's simply not possible with other
algorithms, so for many companies, deep neural nets can make a significant
difference.

Here are two news stories about work we've done for clients:

Making deep learning accessible on Openstack
[https://insights.ubuntu.com/2016/04/25/making-deep-
learning-...](https://insights.ubuntu.com/2016/04/25/making-deep-learning-
accessible-on-openstack/)

For Canonical, we built a solution that predicts server breakdowns.

For France Telecom's mobile unit, Orange, we built a fraud detection solution
using anomaly detection:

[http://www.orangesv.com/blog/orange-deep-learning-work-
featu...](http://www.orangesv.com/blog/orange-deep-learning-work-featured-in-
wall-street-journal/)

~~~
dragon_king
Really cool and interesting. Looks like deep learning and AI is going to make
some significant strides in the tech industry. I read somewhere that there is
still a lack of professionals to expedite the adoption in the wild. What
additional skills are required by your regular full stack software engineer to
be useful for a deep learning company? I know there are courses out there but
I am not sure if they are too academic. Are there specific technologies that
one should be playing with?

~~~
agibsonccc
It varies. Sometimes it's just understanding enough about data to build data
products. (Eg: a website with a recommendation engine component)

Knowing data visualization can also be useful.

Most deep learning companies focus on a particular application.

FWIW I'm actually self taught. I did client projects and learned machine
learning on my own.

You could start by branching in to data engineering and understanding how data
pipelines work. That's closer to the skills a full stack developer is likely
to have.

~~~
dragon_king
Very interesting. Thanks for the insight.

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paulsutter
> After launching in 2014, Skymind now has half a dozen customers...

Umm, is that a misprint?

~~~
rgrieselhuber
I'm not familiar with the company but there is serious money in enterprise AI,
speaking from experience. These could be very large customers.

~~~
agibsonccc
Hi,

Yes the deal sizes are mid 6 figures or larger.

We have a larger deal pipeline than that though. A lot more to come :).

Red hat/oracle style on premise (non saas) business model.

We usually target NON computer vison applications like fraud, preventative
maintenance in data centers (predicting broken machines) and other mission
critical applications.

One example:

[http://insights.ubuntu.com/2016/04/25/making-deep-
learning-a...](http://insights.ubuntu.com/2016/04/25/making-deep-learning-
accessible-on-openstack/)

This kind of stuff is a swear word on hacker news but there's actually money
in it. Fire away if you have specific questions though :).

~~~
maxpupmax
What's your strategy to source relatively large deals like that? In general
terms. Are you cold calling? conferences? Is it from online advertising?
offline? referrals?

~~~
agibsonccc
Channels based sales and lead gen from conferences.

------
kriro
As someone who has worked at an open source company before I'd love to hear
your thoughts on building a sustainable business around open source software.
Most use cases I know are basically customization/consulting in enterprise
settings build around a free base system.

From reading about the company it seems that you want to monetize on ease of
use with the distro? Do you have customers that specifically pick you because
deeplearning4j is open or do you find that it's more of a nice to have or even
don't care as long as it works type of situation?

I'd also love to hear some reasoning for picking Apache 2.0 (i.e. a non-
copyleft one). I've talked to at least one FLOSS founder who would have picked
a different license in retrospect but feel like mostly the license matters
less than most people think.

