5 ms·

> After launching in 2014, Skymind now has half a dozen customers... Umm, is that a misprint?

rgrieselhuber 10y ago
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 10y ago
  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-accessible-on-openstack/ http://insights.ubuntu.com/2016/04/25/making-deep-learning-a... 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 :).
  - harigov 10y ago
    What sort of value add do you provide on top of what the open source frameworks provide?
    - agibsonccc 10y ago
      Main thing is production deployment software and a service level agreement for models we build. In machine learning in production there are 2 phases: training and inference (usage) In training we have spark docker images where you can run cuda right from spark submit. In inference mode we sit on top of DC/OS by mesosphere embedding lightbend's (they created scala) micrsoservices technology conductr to scale out automatically on a mesos based cluster: http://www.slideshare.net/agibsonccc/deep-learning-in-production-with-the-best-66381424 http://www.slideshare.net/agibsonccc/deep-learning-in-produc... Here is more on our enterprise distribution SKIL: http://www.slideshare.net/agibsonccc/skil-dl4j-in-the-wild-meetup http://www.slideshare.net/agibsonccc/skil-dl4j-in-the-wild-m... If you're curious where the talent is, I cowrote the flagship oreilly book on deeplearning: http://shop.oreilly.com/product/0636920035343.do http://shop.oreilly.com/product/0636920035343.do We also employ deep learning phds doing everything from deep learning research in health care, ex nvidia, ex cloudera among others.
  - maxpupmax 10y ago
    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 10y ago
      Channels based sales and lead gen from conferences.
Caligula 10y ago
Probably not a misprint. They could be big enterprise customers.
- agibsonccc 10y ago
  We don't work with startups :).
  - houstonishot 10y ago
    :)
  - Shanea93 10y ago
    I presume you mean "we don't currently work with startups". This is more of a financial issue than an ideological, enterprise only issue, right? I'm assuming if Grail (http://www.grailbio.com/ http://www.grailbio.com/) who launched in 2016 with $100,000,000 in funding were knocking at your door you would be more than happy to work with them?
    - agibsonccc 10y ago
      Right. Startups typically use python/ruby or commodity hadoop clusters on EMR. It's not an audience match and they don't have a budget anyways. For anyone else we have a very active open source community: https://gitter.im/deeplearning4j/deeplearning4j https://gitter.im/deeplearning4j/deeplearning4j
doppenhe 10y ago
Enterprise sales are hard.
- agibsonccc 10y ago
  Indeed but that's what our team can do well. I've never been able to build a consumer product. Enterprise is just about understanding the incentives of the other party and knowing how to navigate the corporate latter.
agibsonccc 10y ago
FWIW we spent much of the time building the product and open source community. Many companies with infrastructure products like ours tend to "incubate" inside a big company first. We chose not to do that. So we spent much of our time just growing the user base first.

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 10y ago
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-accessible-on-openstack/ http://insights.ubuntu.com/2016/04/25/making-deep-learning-a... 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 :).
- harigov 10y ago
  What sort of value add do you provide on top of what the open source frameworks provide?
  - agibsonccc 10y ago
    Main thing is production deployment software and a service level agreement for models we build. In machine learning in production there are 2 phases: training and inference (usage) In training we have spark docker images where you can run cuda right from spark submit. In inference mode we sit on top of DC/OS by mesosphere embedding lightbend's (they created scala) micrsoservices technology conductr to scale out automatically on a mesos based cluster: http://www.slideshare.net/agibsonccc/deep-learning-in-production-with-the-best-66381424 http://www.slideshare.net/agibsonccc/deep-learning-in-produc... Here is more on our enterprise distribution SKIL: http://www.slideshare.net/agibsonccc/skil-dl4j-in-the-wild-meetup http://www.slideshare.net/agibsonccc/skil-dl4j-in-the-wild-m... If you're curious where the talent is, I cowrote the flagship oreilly book on deeplearning: http://shop.oreilly.com/product/0636920035343.do http://shop.oreilly.com/product/0636920035343.do We also employ deep learning phds doing everything from deep learning research in health care, ex nvidia, ex cloudera among others.
- maxpupmax 10y ago
  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 10y ago
    Channels based sales and lead gen from conferences.

Caligula 10y ago

Probably not a misprint. They could be big enterprise customers.

agibsonccc 10y ago
We don't work with startups :).
- houstonishot 10y ago
  :)
- Shanea93 10y ago
  I presume you mean "we don't currently work with startups". This is more of a financial issue than an ideological, enterprise only issue, right? I'm assuming if Grail (http://www.grailbio.com/ http://www.grailbio.com/) who launched in 2016 with $100,000,000 in funding were knocking at your door you would be more than happy to work with them?
  - agibsonccc 10y ago
    Right. Startups typically use python/ruby or commodity hadoop clusters on EMR. It's not an audience match and they don't have a budget anyways. For anyone else we have a very active open source community: https://gitter.im/deeplearning4j/deeplearning4j https://gitter.im/deeplearning4j/deeplearning4j

doppenhe 10y ago

Enterprise sales are hard.

agibsonccc 10y ago
Indeed but that's what our team can do well. I've never been able to build a consumer product. Enterprise is just about understanding the incentives of the other party and knowing how to navigate the corporate latter.

agibsonccc 10y ago

FWIW we spent much of the time building the product and open source community. Many companies with infrastructure products like ours tend to "incubate" inside a big company first. We chose not to do that. So we spent much of our time just growing the user base first.