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SK Planet 2014 presentation on deep learning for the enterprise. Tech Planet is a conference based in South Korea.
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Distributed Deep LearningFor Enterprise
Tech Planet - Nov. 3, 2014
Presented by Adam Gibson
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
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
Brands
"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
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.
• “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.
Domains
● IMAGE○ FACES○ MACHINE VISION
● SOUND○ SPEECH TO TEXT○ MACHINE TRANSLATION
● TEXT○ SEARCH○ INFORMATION RETRIEVAL
● TIME SERIES○ WEATHER, BIODATA, STOCKS
Adam Gibson | Skymind
Faces Learned By Our DL Networks
Numbers Grouped by Skymind
Use Case
● Search => Google, Bing, Yahoo● Information retrieval● Document clustering● Text, sound and image search● Question-Answer ~ Watson
Use Case
● CRM● Customer Resource Management● Churn prediction (SaaS)● Big spender prediction (gambling)● Log/behavior analysis● Sentiment Analysis
● 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
● Enterprise Resource Management/Planning○ Factories○ Complex Logistics○ Personnel Deployments○ Oil & Gas
Use Case
Back-ground
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
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
Difference
Amount of Data
Accuracy MachineLearning
DeepLearning
Deep Learning Is Setting Records
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.
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.
Why Is Deep Learning Hard?We see this… Machines see this…
(Hat tip to Andrew Ng)
Problem
Takeaways
Be careful out there.
