1. The document discusses emerging trends in artificial intelligence and machine learning towards a driverless world. Key trends discussed include recommendation engines, facial recognition using deep learning, object and person identification using computer vision, biometrics like fingerprinting, voice assistants in homes and cars, and vehicle-to-vehicle communication technologies. 2. The document also covers applications of AI and machine learning like cognitive IoT, deep learning in healthcare for disease prediction, integrating car telematics with artificial intelligence, and machine learning platforms and techniques. 3. Overall the document provides an overview of the state of artificial intelligence and machine learning technologies and their role in enabling an emerging driverless world.

1. 1
AI TRENDS TOWARDS A DRIVERLESS WORLD
SUDHA
JAMTHE,
CEO
IoTDisrup5ons
&
Stanford
CSP
AI
OpenPower
Meetup,
CA,
USA
March
25th,
2018
IoTDisruptions.com © 2018 Sudha Jamthe
Image: bigthink.com

2. SUDHA JAMTHE Background
2
CEO IoTDisruptions, Technology Futurist
Continuing Studies Instructor
Driverlesscarbook.com @sujamthe
Driving the vision of a Driverless World.

3. WHAT IS THE DRIVERLESS WORLD?
3IoTDisruptions.com @sujamthe

4. THE DRIVERLESS WORLD = IoT MEETS AV
DW
Home
Entertain
ment
Health
Work
4
Car Cognition
Robots & Smart
Mobility (MAAS)
Smart City Infrastructure
Digitization of
self & our
health
Voice engagements
Fleet optimization
© Sudha Jamthe
Car TelematicsV2V, V2I and B2V
machine communications
IoTDisruptions.com DriverlessWorldsSchool.com @sujamthe

5. AI COMPANIES LANDSCAPE
5
IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

6. WHAT IS STATE OF AI TECHNOLOGY?
6IoTDisruptions.com http://bit.ly/driverlessworld @sujamthe

7. AI TECHNOLOGY SPECTRUM
7
Machine Learning
& Deep Learning
Cognitive
IoT
AR/VR
Voice to Text
Text to Speech
Facial
Recognition
Computer Vision
NLP
Machine Intelligence
IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe
Copyright: Sudha Jamthe

8. Machine Learning teaches computers to
develop programs with large volume of
data and drive decisions without human
intervention.
8IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

9. Machine Learning Works by Building Data Models (a
geometric shape of data*)
image: Techemregence Gaussian mixture model
Training
Data &
Factors
Predict
Outcomes
to make
decisions
9IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

10. Types of AI
1. Supervised (A-B type Machine Learning)
– Get Training Data, Define factors, Remove biases
2. Unsupervised Learning aka Deep Mining (Neural Networks)
- less factors, train same architecture for generic problem solving.
3. Reinforced Learning
- Repeated learning based on a reward.
4. Transfer Learning
- AI trained on one data set transfer learning to a different problem
10IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

11. Building Products with Machine Learning
11IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe
Pick a Machine Learning Platform
(TensorFlow, ScikitLearn, Theano, Spark Mlib, H20)
Develop the right stats model (decision tree, nearest neighbor,
neural net, support vector machine) and Fit the data using right
learning procedure ( linear regression, gradient descent, boosting,
nagging)
Develop Training Data & Fit
(bias and variance, overfitting and underfitting, missing
data, data leakage)
Defining a ML Service into a Product
(Identity, Data Governance, Algorithmic accuracy/
Compliance for industry)
© Sudha Jamthe
ML
Engineer
ML
Researcher
ML Product
Manager

12. AI TRENDS TOWARDS
THE DRIVERLESS
WORLD
1
2
IoTDisruptions.com http://bit.ly/driverlessworld @sujamthe

13. 1. RECOMMENDATION ENGINES & SPAM FILTERS
13IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

14. 2. Facial recognition with Deep Learning
Source: https://medium.com/@ageitgey/machine-learning-is-fun-part-4-modern-face-recognition-with-deep-learning-c3cffc121d78
Credit: Adam Geitgey @ageitgey
1
4
IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

15. 3. Person Identification
Source Nest.com and Nest Lab
NestCam sends a notification
when it spots a person
IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

16. 1
6
4. Biometrics: Fingerprinting
IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

17. 5. VOICE IN THE HOME AND CAR
IOTDisruptions.com #IoTAI @sujamthe 17

18. 1
8
Objects spotted – Traffic signs, cars, people
6. CAR COGNITION
IoTDisruptions.com http://bit.ly/driverlessworld @sujamthe

19. 1
9
7. Cognitive IoT using Computer Vision
Image: Sudha Jamthe
Yumu, Collaborative Industrial Arm, ABB
Nanobots detect and kill cancer cellsKnightscope, Security Robots
IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe

20. 8. DEEP LEARNING IN HEALTHCARE
IOTDisruptions.com #IoTAI @sujamthe 20
Deepmind (Google), predict Kidney
problems
Mind Controlled Robotic Arm
Nanobots detect and kill cancer cells
Image: cnn.com
BigAu Teddy with Watson IoT

21. 9. CAR AI + TELEMATICS
21
Ref: https://newsroom.intel.com/newsroom/wp-content/uploads/.../passenger-economy.pdf
IoTDisruptions.com http://bit.ly/driverlessworld @sujamthe

22. 10. V2V, V2I ,V2B COMMUNICATIONS
22IoTDisruptions.com http://bit.ly/driverlessworld @sujamthe
Image: Nissan
Brain controlled car from Nissan

23. REFERENCE
2
3
• api.ai, Cogito, DataSift, iSpeech, Microsoft Project Oxford,
Mozscape, and OpenCalais.
• Tensorflow
• IBM Watson
• aws.amazon.com/machine-learning/
• Comparison of Machine Learning Types
• How to become a ML Engineer?
IoTDisruptions.com #IoTAI @sujamthe

24. 24IoTDisruptions.com http://bit.ly/IoTAIBook @sujamthe
Source: blog.sas.com

25. Reference: IBM OpenPower AI Hardware
2
5
https://www.ibm.com/us-en/marketplace/power-systems-ac922
IoTDisruptions.com #IoTAI @sujamthe

26. Connect with me!
Slides: slideshare.com/sujamthe
Twitter: @sujamthe
Newsletter: iotdisruptions.com
Online courses: (from April 9 2018)
http://driverlessworldschool.com
Books: http://bit.ly/sudhajamthe
26IoTDisruptions.com #IoTAI @sujamthe