2015 presentation on deep learning for the enterprise by Skymind, the commercial support arm of Deeplearning4j.

1. Distributed Deep Learning
For Enterprise
Tech Planet - Nov. 3, 2014
Presented by Adam Gibson

2. Adam Gibson | Skymind
What Are Deep Learning Nets?
● Mathematical models that mirror
human neurons
● Recognizing patterns like images,
sounds, verbal sequences
● Neural nets need those patterns
to be translated into numbers
Adam Gibson | Skymind
Define

3. Adam Gibson | Skymind
Who Is Deep Learning For?
● Chief Information Officers looking for the highest
performance in machine learning
● Businesses looking to maximize the value of small
data science teams, creating apps and cutting
costs.
● Data scientists and programmers who seek to
process huge amounts of unstructured data without
laborious feature extraction.
Users

4. Brands

5. "The biggest disruptor that we are sure about
is the arrival of big data and machine
intelligence. This disruption will not only
change every business globally, it will also
have an important impact on the consumer."
Google Chairman Eric Schmidt, Bloomberg TV, Dec. 30 2013

6. First
Movers
● Google hired Geoff Hinton, the pre-eminent deep
learning expert, last year to help build their search and ad
recommendation engines.
● Facebook hired Yann LeCun, the no. 2 deep-learning
expert, to help build a Facebook feeds that recommend
more engaging content.
● Baidu hired Andrew Ng, a Stanford deep-learning
professor, away from Google to lead its research team.
● Microsoft, Amazon and Netflix all have deep-learning
teams working to give customers more of what they want
through recommendation and search.
● Tech giants have monopolized deep learning.

7. • “A breakthrough in machine learning would be
worth 10 Microsofts.” - Bill Gates, Microsoft
• “Machine learning is the next Internet.”
- Tony Tether, DARPA Director
• “Web rankings today are mostly a matter of
machine learning.” - Prabhakar Raghavan,
Yahoo Director of Research
• “Machine learning is going to result in a real
revolution.”
- Greg Papadopoulos, Sun CTO
• “Machine learning is todayʼs discontinuity.”
- Jerry Yang, Yahoo
Deep learning is that breakthrough, and Skymind is bringing it to industry.

8. Domains
● IMAGE
○ FACES
○ MACHINE VISION
● SOUND
○ SPEECH TO TEXT
○ MACHINE TRANSLATION
● TEXT
○ SEARCH
○ INFORMATION RETRIEVAL
● TIME SERIES
○ WEATHER, BIODATA, STOCKS

9. Adam Gibson | Skymind
Faces Learned By Our DL Networks

10. Numbers Grouped by Skymind

11. Use Case
● Search => Google, Bing, Yahoo
● Information retrieval
● Document clustering
● Text, sound and image search
● Question-Answer ~ Watson

12. Use Case
● CRM
● Customer Resource Management
● Churn prediction (SaaS)
● Big spender prediction (gambling)
● Log/behavior analysis
● Sentiment Analysis

13. ● Recommendation Engine
○ E-commerce => Amazon
○ Advertising => Google, Baidu
○ See: "The ‘Chinese Google’ Is Making Big
Bucks Using AI to Target Ads"
--Wired, Oct. 20, 2014
Use Case

14. ● Enterprise Resource Management/Planning
○ Factories
○ Complex Logistics
○ Personnel Deployments
○ Oil & Gas
Use Case

15. Back-
ground

16. Cloud
● Big data lives in the cloud
● Nets train on big data for good results
● Training = computationally intensive
● Deep learning also lives in the cloud

17. Deep learning ...
● Needs scale to be powerful
● Can identify signal at scale
● Achieves scale with raw data
● And thousands of CPUs or GPUs
● Running in parallel
Signal
&
Scale

18. Difference
Amount of Data
Accuracy
Machine
Learning
Deep
Learning
Deep Learning Is Setting Records

19. Lessons
● The world is more knowable than ever before.
● Machines can measure events and human
behavior more accurately.
● Business has not caught up with its own data.
● Machines can grow smarter with deep learning.
● Analyzing huge seas of data that no human has
ever seen.
● Knowledge is only power ... if you interpret data.

20. Method
● Deep learning classifies
the world. It starts with
obvious things (which are
not obvious for
machines), and extends
to subtle things, which are
not obvious for humans.
● Nothing is obvious to
machines because they
only understand numbers.
Houses, men, dogs, cats,
trees are all numbers.

21. Why Is Deep Learning Hard?
We see this… Machines see this…
(Hat tip to Andrew Ng)
Problem

22. Take
aways
Be careful out there.

23. Contact
Adam Gibson
Skymind Founder
adam@skymind.io