1.
JenStirrup.com
DataRelish.com
http://bit.ly/JenStirrupRD
http://bit.ly/JenStirrupLinkedIn
http://bit.ly/JenStirrupMVP
http://bit.ly/JenStirrupTwitter

2.
WhatisAIandwhyisituseful?
AI Leadership for Executives

3.
•http://bit.ly/JenStirrupRD
•http://bit.ly/JenStirrupLinkedIn
•http://bit.ly/JenStirrupMVP
•http://bit.ly/JenStirrupTwitter

4.
JenStirrup.com
DataRelish.com

5.
http://bit.ly/JenStirrupRD
http://bit.ly/JenStirrupLinkedIn
http://bit.ly/JenStirrupMVP
http://bit.ly/JenStirrupTwitter

6.
AI
• Imbuing computers with human-inspired thinking
• Recognition between Marketing version of AI and AI in reality

7.
deep learning at Microsoft
• Microsoft Cognitive Services
• Skype Translator
• Cortana
• Bing
• HoloLens
• Microsoft Research
Microsoft
Cognitive
Toolkit

8.
“We tend to
overestimate the
effect of a technology
in the short run and
underestimate the
effect in the long run”
- Roy Amara

9.
Customers Products
Intelligent
customer
engagement
Transformed
products and
operations
Digital feedback loop
People
Customers ProductsData +
Intelligence

10.
Artificial Intelligence
can offer
businesses great
opportunities.
Ideas are developing
into reality at
accelerated rates.

11.
What is the Red Queen’s Race?
"It takes all the running you can
do, to keep in the same place.Ifyou
wanttogetsomewhereelse,you
mustrunat leasttwiceasfastas
that!"-TheRedQueen,ThroughtheLooking-Glass

12.
https://www.success.com/blog/why-your-comfort-zone-is-the-most-dangerous-place-to-live

13.
WhydoweneedAI?

14.
Why do we need AI?
• Customers
• Compete
• Capitalize
• Create
• Costs
• Challenges
• Calculate
• Cognition

15.
Conceptualizing AI
• Gathering Information
• What is happening now?
• Understanding

16.
Conceptualizing AI
• Gathering Information
• What is happening now?
• Understanding

17.
Image recognition
• Deep Learning recognises
objects in images
• If you use technology such as
Google Photos, you are likely
using it every day

18.
Rankbrain

19.
Parsey McParseface

20.
Conceptualizing AI
• Gathering Information
• What is happening now?
• Understanding

21.
Why speech recognition now?
• Speech Recognition is
everywhere
• Increased accuracy led to
increased uptake
• Deep Learning has been
instrumental

22.
Speech recognition issues
• Data representation of
speech
• Speech varies in speed
• Process of training is iterative

23.
Speech Recognition today
• Requirement for high
compute power
• Model parallelism
• Data parallelism

24.
Speech recognition possibilities
• Natural speech interface with
computers
• Translation of languages

25.
Parsey McParseface
• Speech Applications has
impact in other domains
such as search
• Other players include
Siri(Apple),
Cortana(Microsoft),
• Amazon Echo
• Google Home

26.
Speech recognition and AI?
• Turing Test
• Exploration of language

27.
Machine to Human Scale Data

28.
Data and The culture of now

29.
NEW WAYS for new data

30.
Lessons from the Human Brain

31.
Deep Learning Lexicon
• Scalar
• Vector
• Matrix
• Tensor

32.
Neural Networks
• Neural network
• Activation
• Feedforward
• Backpropagation
• Convolved neural networks

33.
App
DataApp
App
App
App
App
App
App
App
App