Delivered January 30, 2018 at Mobile Tea Boston. This is an updated version of the presentation from June 2017. Artificial Intelligence. Machine Learning. And Mobile? Yup. Every major technology company and a host of not so major ones are doing things with AI. With cheap, plentiful computing power and a growing number of open source and commercial offerings, applications that used to be the stuff of science fiction are available today from your desktop, phone, and watch. Let’s talk about what’s happening and how it affects how we think about mobile development.

1. AI and Mobile:
Power in Your Pocket
Stephen Vance
Mobile Tea
January 30, 2018

2. 2

3. 3

4. What are AI and ML?
• Artificial Intelligence, Machine Learning, and “Big Data”
• Techniques, Data, Features
• Linear Algebra, Probability, Information Theory, Numerical Methods,
Optimization, Curve Fitting, Neural Networks, etc.
• Learning, Models, Predictions
• Unsupervised, Supervised
4

5. AI Applications
• Optical Character Recognition (no longer)
• Speech recognition (mainstream)
• Machine vision (becoming commonplace)
• Purchase prediction
• Traffic routing
• Medical diagnosis and public health
5

6. ML PaaS and OSS
6

7. Mobile ML Toolkits
7

8. Mobile ML Architectures
Feature
Extraction
Training
Characterization
Anomaly
Detection
Models
Streaming Data
Data Lake
Server
8

9. Mobile ML Architectures
Feature
Extraction
Training
Characterization
Anomaly
Detection
Models
Streaming Data
Data Lake
9

10. Social Challenges
• Data bias
• Historical data sets
• Balanced representation
• Unquestioning use
• Not just “Can we?”
• But “Should we?”
• Privacy
10
Algorithmic
Justice League

11. 11
https://www.mabl.com
To Be On The Waitlist For Deeper Involvement
Talk to Me

12. Contact Me
Stephen Vance
http://www.vance.com
steve@vance.com
@StephenRVance
srvance on GitHub and LinkedIn
12

13. References
• Actions on Google: https://developers.google.com/actions
• Amazon Alexa: https://developer.amazon.com/alexa
• Amazon Machine Learning: https://aws.amazon.com/machine-learning/
• Apple CoreML: https://developer.apple.com/machine-learning/
• Apple SiriKit: https://developer.apple.com/sirikit/
• Deep Learning: http://www.deeplearningbook.org/
• Facebook Caffe2: https://caffe2.ai/
• Google Cloud Machine Learning: https://cloud.google.com/ml-engine
• IBM Watson: https://www.ibm.com/watson/
• MathWorks Machine Learning: https://www.mathworks.com/machinelearning
• Microsoft Azure Machine Learning: https://azure.microsoft.com/en-us/services/
machine-learning
• TensorFlow Lite: https://www.tensorflow.org/mobile/tflite/
13