This document summarizes a presentation given by Dr. Ned Sahin, CEO of Brain Power, about how the company is using AWS services to develop machine learning applications. Brain Power is using AWS to re-architect their web applications for improved scalability. They developed an application called Fidgetology that uses video analysis and AWS Lambda to provide real-time metrics on student attention and behaviors. Brain Power is also exploring uses of Amazon DeepLens in classrooms to provide feedback to teachers and students through their LearningEye product. The presentation outlines Brain Power's mission to help those with autism or other challenges and how AWS is enabling them to develop innovative AI-powered solutions.

1. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Bob Strahan
Principal Consultant, Public Sector, Amazon Web Services
Dr. Ned T. Sahin
CEO & Founder, Brain Power
Associate in Psychology, Harvard University
194335
Empowering Every Brain! How Brain Power is using
AWS-Powered AI in their Mission to Help People
with Autism and Other Brain-Related Challenges

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Agenda
1. Introduction to Relevant AWS Services
2. Use Case in Autism and Measurement of Attention

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Machine Learning on AWS

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A long heritage of machine learning at Amazon
Personalized
recommendations
Inventing entirely
new customer
experiences
Fulfillment
automation and
inventory
management
Drones Voice driven
interactions

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The Amazon Machine Learning Stack
AWS
DeepLens
EDUCATION
APPLICATION SERVICES
FRAMEWORKS & INTERFACES
PLATFORM SERVICES

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Bottom Layer: Frameworks & interfaces
NVIDIA
Tesla V100 GPUs
P3
AWS Deep Learning AMI
5,120 Tensor cores
128GB of memory
1 Petaflop of compute
NVLink 2.0
~14X faster than P2

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The Amazon Machine Learning Stack
FRAMEWORKS & INTERFACES
Caffe2 CNTK
Apache
MXNet
PyTorch TensorFlow Chainer Keras Gluon
AWS Deep Learning AMIs
Amazon SageMaker
AWS
DeepLens
EDUCATION
PLATFORM SERVICES
PLATFORM SERVICES
APPLICATION SERVICES

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ML is still too complicated for everyday developers
Collect and prepare
training data
Choose and
optimize your ML
algorithm
Set up and manage
environments for
training
Train and tune model
(trial and error)
Deploy model
in production
Scale and manage
the production
environment

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Amazon SageMaker
Collect and prepare
training data
Choose and
optimize your ML
algorithm
Set up and manage
environments for
training
Train and tune model
(trial and error)
Deploy model
in production
Scale and manage
the production
environment
E a s i l y b u i l d , t r a i n , a n d d e p l o y m a c h i n e l e a r n i n g m o d e l s

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Amazon SageMaker
Pre-built
notebooks for
common
problems
K-Means Clustering
Principal Component Analysis
Neural Topic Modelling
Factorization Machines
Linear Learner - Regression
XGBoost
Latent Dirichlet Allocation
Image Classification
Seq2Seq
Linear Learner - Classification
ALGORITHMS
Apache MXNet
TensorFlow
Caffe2, CNTK,
PyTorch, Torch
FRAMEWORKS
Set up and m anage
environments for
training
Train and tune
m odel (trial and
error)
Deploy m odel
in production
Scale and m anage the
production environment
Built-in, high
performance
algorithms
BUILD

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Amazon SageMaker
Pre-built
notebooks for
common
problems
Built-in, high
performance
algorithms
One-click
training
Hyperparameter
optimization
BUILD TRAIN
Deploy model
in production
Scale and manage
the production
environment

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Amazon SageMaker
Fully managed
hosting with auto-
scaling
One-click
deployment
Pre-built
notebooks for
common
problems
Built-in, high
performance
algorithms
One-click
training
Hyperparameter
optimization
BUILD TRAIN DEPLOY

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Can we do more to put ML in the
hands of all developers (literally)?

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AWS DeepLens
HD video camera
Custom-designed
deep learning
inference engine
Micro-SD
Mini-HDMI
USB
USB
Reset
Audio out
Power
HD video camera
with on-board
compute optimized
for deep learning
Tutorials, examples,
demos, and pre-built
models
From unboxing to
first inference in
<10 minutes
Integrates with Amazon
SageMaker and AWS
Lambda
10
MIN

15. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
The Amazon Machine Learning Stack
FRAMEWORKS & INTERFACES
Caffe2 CNTK
Apache
MXNet
PyTorch TensorFlow Chainer Keras Gluon
AWS Deep Learning AMIs
Amazon SageMaker
Rekognition Transcribe Translate Polly Comprehend Lex
AWS
DeepLens
EDUCATION
PLATFORM SERVICES
APPLICATION SERVICES
APPLICATION SERVICES

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Amazon Rekognition
Object, Scene &
Activity Recognition
Facial
Recognition
Facial Analysis Person Tracking
Unsafe Content
Detection
Celebrity
Recognition
Text in Images
D e e p l e a r n i n g - b a s e d i m a g e a n d v i d e o a n a l y s i s
Object, Scene &
Activity Recognition
Facial
Recognition
Facial Analysis Person Tracking
Text in Images

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Powerful speech & language capabilities
Amazon Transcribe
Automatic conversion of speech into accurate, grammatically correct
text
Amazon Translate Natural and fluent language translation
Amazon Polly Turn text into lifelike speech using deep learning
Amazon Comprehend Discover insights and relationships in text
Amazon Lex Conversational interfaces for text-based and voice-based applications

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Brain Power
Empowering Every Brain!
Dr. Ned T. Sahin
Founder, Brain Power
Associate, Harvard Psychology Dept.

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Autism / ADHD Your Content
Brain-Power.com/AWS

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Fidgetology ™
Brain-Power.com/AWS

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Agenda
1. Teaser (just happened)
2. Background: Speaker, Company, Mission
3. AWS Original Project: Web App Re-Architecture
4. Fidgetology: Background & Concept
5. Fidgetology: Implementing
6. DeepLens & Classroom Use Case
7. Future Directions

22. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Background: Your Speaker
Dr. Ned Sahin
CEO
BA
Williams
Oxford
Scholar
MIT
M.S.
Harvard
PhD
PostDoc
Salk
Fellow
STARTUP

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Background: The Company (Brain Power, LLC)
1. 4.5 years
2. AR for autism & other challenges
3. Diverse & Dynamic Team
4. $4.5 M in Grants
5. Clinical trials, peer-reviewed papers
6. 300+ Press appearances
7. Live customers, in 2 markets
8. Partnerships and Collaborations
9. Dozen awards

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Background: The Mission
1. Unlock the Power of the Challenged Brain
2. Autism: Caught between health and education systems
3. Social-Emotional : The Soft Skills are the Hard Skills™
4. Augmented Reality coaching for eye contact, emotions, etc
5. CHALLENGE: Measure how well our apps are working

25. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Agenda
1. Teaser (just happened)
2. Background: Speaker, Company, Mission
3. AWS Original Project: Web App Re-Architecture
4. Fidgetology: Background & Concept
5. Fidgetology: Implementing
6. DeepLens & Classroom Use Case
7. Future Directions

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3 Examples of Brain Power’s AR Apps for AutismEYECONTACTEMOTIONSTRANSITIONS

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Original Home-Grown Architecture

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Original Home-Grown Architecture

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Converting to AWS, with On-Site Pro Services

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New Infrastructure, Re-Architected for Scale:
Our First AWS Engagement & Accomplishment
Privacy Security
HIPAA Auto-Scaling

31. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Agenda
1. Teaser (just happened)
2. Background: Speaker, Company, Mission
3. AWS Original Project: Web App RE-Architecture
4. Fidgetology: Background & Concept
5. Fidgetology: Implementing
6. DeepLens & Classroom Use Case
7. Future Directions

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Fidgetology™ – Background and Concept
The Children

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Fidgetology – Background and Concept
Clinical Trials
At Brain Power In Schools

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Fidgetology – Background and Concept
Meeting Real-World Customers

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Fidgetology – Background and Concept

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Fidgetology – Background and Concept
Classical Medical Research

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Fidgetology – Background and Concept
Classical Medical Research Data

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Fidgetology – Background and Concept
BUT we were missing something!

39. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Fidgetology – Background and Concept

40. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Agenda
1. Teaser (just happened)
2. Background: Speaker, Company, Mission
3. AWS Original Project: Web App RE-Architecture
4. Fidgetology: Background & Concept
5. Fidgetology: Implementation
6. DeepLens & Classroom Use Case
7. Future Directions

41. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Fidgetology – Implementation
Runpeng Liu
Senior Eng.
Brain Power

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Fidgetology – Implementation
Scalable
Architecture

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Fidgetology – Implementation
Scalable
Architecture
Multi-source
Video ingestion

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Fidgetology – Implementation
Scalable
Architecture
Multi-source
Video ingestion

45. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Fidgetology – Implementation
Scalable
Architecture
Multi-source
Video ingestion
Detection &
Customizable
Analysis

46. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Scalable
Architecture
Multi-source
Video ingestion
Detection &
Customizable
Analysis
AWS Lambda
Fidgetology – Implementation

47. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Fidgetology – Implementation
Scalable
Architecture
Multi-source
Video ingestion
Detection &
Customizable
Analysis
Real-time
Metrics
visualization

48. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Fidgetology – Results
Scalable
Architecture
Multi-source
Video ingestion
Detection &
Customizable
Analysis
Real-time
Metrics
visualization

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Fidgetology™ – Results
Patents pending worldwide

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Fidgetology – DEMO

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Fidgetology – DEMO

52. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Fidgetology – DEMO

53. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Fidgetology – DEMO

54. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Fidgetology – FOR YOU
How can Fidgetology help Your company?
• Do customers engage with your ads or apps?
• Are staff paying attention? (Board meetings, or bored??)
• Clinical trials: how does device/drug alter behavior?
• Corporate training: is it effective? Why / not?
• Company culture
• Classroom: how learners learn and teachers teach

55. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Agenda
1. Teaser (just happened)
2. Background: Speaker, Company, Mission
3. AWS Original Project: Web App RE-Architecture
4. Fidgetology: Background & Concept
5. Fidgetology: Implementing
6. DeepLens & Classroom Use Case
7. Future Directions

56. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
DeepLens in the Classroom: LearningEye™

57. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
DeepLens in the Classroom: LearningEye™

58. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
DeepLens in the Classroom: LearningEye™
Patents pending worldwide

59. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

60. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
LearningEye™ by Brain Power
1. Schools can pre-order now. Brain-Power.com
2. Privacy assured: “edge device” means video stays local
1. Only processed, numerical data are sent to the cloud
3. Predict when special-needs student may get overloaded
4. For all students: attention, distraction, texting, issues, etc
5. Empowers (not replaces) the teacher
6. Feedback to the teacher AND the students
7. Useful reminders. Not Big Brother, but a nice big sister!
8. Beyond schools: corporate training and assessment

61. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Agenda
1. Teaser (just happened)
2. Background: Speaker, Company, Mission
3. AWS Original Project: Web App RE-Architecture
4. Fidgetology: Background & Concept
5. Fidgetology: Implementing
6. DeepLens & Classroom Use Case
7. Future Directions

62. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
Future Directions
1. Efficacy measure of Brain Power’s products
2. Outcome measure for clinical trials by other companies
3. Job training and employee support
4. Training for customer service, interviews, etc
5. Advanced classroom monitoring and teacher support
6. Prediction and early warning detection
7. Mental health, self-harm, well-being
8. Many more…

63. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.Brain-Power.com/AWS
SUMMARY & TAKE-HOMES
1. Brain Power: Unlocking the Power of the Challenged Brain
2. AWS helped mission-critical tasks, then helped Think Big
3. Fidgetology™ = Quantify Body Language & Engagement
4. Fidgetology for Assessing Autism and ADHD
5. Fidgetology for Your Business
6. LearningEye: Machine Learning to Foster Human Learning
7. Sign up or give feedback, on our web!

64. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
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