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Steve HolderNational Strategy Executive, AI
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Deep Learning
AnalyticsMachine Learning
Recurrent Neural Networks
Reinforcement Learning
Deep Forward Neural Networks
Transfer Learning
Convolutional Neural Networks
GRU
LSTM
GPUs
Backpropagation
ReLU
Stochastic Gradient Descent
Activation Function
Regularization
Cost/Loss FunctionEmbeddings
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Artificial Intelligenceis the science of training systems to emulate human tasks
through learning and automation.
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Why now?
Data
Computing Power
Algorithms
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Gartner
• In January 2016, the term "artificial intelligence" was not in the top 100 search terms
• By May 2017, the term ranked at No. 7.
• Hype and "AI Washing" Is Creating Confusion, Obscuring the Real Benefits of the Technology
Is AI something new?
0
20
40
60
80
100
120
2010 2010 2011 2012 2013 2014 2015 2015 2016 2017
AI Vs Analytics
Analytics WW AI WW
Source: Gartner https://www.gartner.com/newsroom/id/3763265 July 2017Google Trends
Siri Amazon Echo Waymo AlphaGo
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Natural Language UnderstandingBoth natural language ingestion and
generation.
Rules-based systems Simplest form of automation, the execution of rules
Text ProcessingThe addition of unstructured text
Machine Learning Advanced analytic algorithms create insight with more automation
Computer VisionThe addition of images and video
Process AutomationAutomate repetitive functions and processes
Predictive AnalyticsPredict, advise, influence,
recommend
Deep Learning Self learning algorithms that deliver even more insight and automation
AI Components
AI is a Spectrum
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What Does AI Do?
Learn Patterns
Find The Outliers
Recognize Objects
Categorize or catalog like people
or things.
Predict likely outcomes.
Find unknown patterns and relationships.
Detect anomalous or unexpected
behaviors.
See The Future
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System Approach to AI & ML
• Capacity to explore, test and create
• Scale, analytic rigor, performance
• Collaborate, tune and operate
• Ensure value is derived8
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Top 5
1. Focus on the problem
2. Avoid Black Box exercises
3. Have a data strategy
4. Build expertise
5. Have realistic expectations
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AI Capabilities
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ALGORITHMS
• Deliver robust analytic algorithms.
• More accurate analytics.
• More analytic techniques.
AUTOMATION
• Automate the analytics lifecycle including models and data preparation
• Deploy AI Applications
TEXT AND IMAGE PROCESSING
• Image processing, classification and recognition.
• Text processing, Analytics, & Sentiment Analysis.
• Natural language generation.
AI APPLICATIONS
• Embed AI in SAS applications
• Natural language interfaces to SAS.
• Build enterprise AI Applications
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Transforming a world of data into a world of intelligence
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