We've heard a lot lately about how the machines may be taking over our jobs. AWH founder and principal, Chris Slee, recently discussed artificial intelligence and machine learning - and how it will affect your business in the future.

1. A.I. WORKSHOP
The differences between ML and AI. How machines ”learn". How businesses are using
the technology today. What are the future of these innovations and how will they affect
your enterprise?
FEATURING: Christopher Slee

2. Christopher Slee is the founder and principal of AWH, a Dublin, Ohio
software engineering firm currently celebrating its 22nd year of creating
great digital products for business clients.
Even though Chris has been programming for more than 30-years, he
continues to push the technology envelope. From drones to artificial
intelligence, Chris continues to exemplify the spirit of continual learning in
the tech space.
Chris attended and now is an Adjunct Professor at The Ohio State
University.
Christopher
SleePrincipal @AWH

21. In short, the best answer is that Artificial
Intelligence is the broader concept of machines
being able to carry out tasks in a way that we
would consider “smart”.
What is A.I.Definitions

22. Machine Learning is a current application of AI
based around the idea that we should really just
be able to give machines access to data and let
them learn for themselves.
What is Machine
Learning?
Definitions

23. Algorithms
Algorithms are sets of rules that a
computer is able to follow.
THE BUILDING BLOCKS

24. Think about how you learned to do long division -- maybe you
learned to take the denominator and divide it into the first
digits of the numerator, then subtracting the subtotal and
continuing with the next digits until you were left with a
remainder. Well, that’s an algorithm, and it’s the sort of thing
we can program into a computer, which can perform these
sorts of calculations much, much faster than we can.
Division
Algorithm

25. There are many
algorithms and
they have been
around in
computing for a
long time.

26. So is
machine
learning just
a bunch of
code?

28. Algorithms:
The first key to
machine
learning

29. Big Data:
The second
key to
machine
learning

32. A Neural Network is a computer system designed to
work by classifying information in the same way a
human brain does. It can be taught to recognize, for
example, images, and classify them according to
elements they contain. Essentially it works on a
system of probability – based on data fed to it, it is
able to make statements, decisions or predictions
with a degree of certainty. The addition of a feedback
loop enables “learning” – by sensing or being told
whether its decisions are right or wrong, it modifies
the approach it takes in the future.
Neural
Networks

33. Deep learning is AI that uses complex
algorithms to perform tasks in domains where
it actually learns the domain with little or no
human supervision. In essence, the machine
learns how to learn.
Deep Learning

34. Federated Learning enables mobile phones to
collaboratively learn a shared prediction
model while keeping all the training data on
device, decoupling the ability to do machine
learning from the need to store the data in the
cloud.
Federated
Learning

35. If its not code
what is it?

37. AI Dreams

38. Who are the big
names?

39. What are some of the many
tools?

40. Lets look into
one

41. LUI
SLanguage Understanding Intelligent Services (LUIS) brings
the power of machine learning to your apps
One of the key problems in human-computer interactions is the ability of the computer to understand what a person wants.
LUIS is designed to enable developers to build smart applications that can understand human language and accordingly react
to user requests. With LUIS, a developer can quickly deploy an HTTP endpoint that will take the sentences sent to it and
interpret them in terms of their intents (the intentions they convey) and entities (key information relevant to the intent).
By using LUIS web interface, you can create an application, with a set of intents and entities that are relevant to your
application’s domain. For example, in a travel agent app, a user might say an utterance like "Book me a ticket to Paris". In this
utterance, there is the intention to "BookFlight" and "Paris" is the entity. Intention or the intent can be defined as the desired
action and usually contains a verb, in this case "book". The entity is a relevant information of a specific data type, in this case
"Paris" is the location entity.
Once your application is deployed and traffic starts to flow into the system, LUIS uses active learning to improve itself. In the
active learning process, LUIS identifies the utterances that it is relatively unsure of, and asks you to label them according to
intent and entities. This has tremendous advantages; LUIS knows what it is unsure of, and asks for your help in the cases
which will lead to the maximum improvement in system performance. LUIS learns quicker, and takes the minimum amount of
your time and effort. This is active machine learning at its best.

42. Emotion
API
Microsoft Emotion API, which allows you to build more personalized apps
with Microsoft’s cutting edge cloud-based emotion recognition algorithm.
The Emotion API beta takes an image as an input, and returns the confidence across a set of emotions for each face in the
image, as well as bounding box for the face, from the Face API. The emotions detected are happiness, sadness, surprise,
anger, fear, contempt, disgust or neutral. These emotions are communicated cross-culturally and universally via the same
basic facial expressions, where are identified by Emotion API.

43. Face
API
Microsoft Face API, a cloud-based service that provides the most advanced face
algorithms. Face API has two main functions: face detection with attributes and face
recognition.
Face rectangle (left, top, width and height) indicating the face location in the image is returned along with each detected face.
Optionally, face detection extracts a series of face related attributes such as pose, gender, age, head pose, facial hair, glasses
and emotion.

44. This is just one of
many

46. Netflix
What you should like
recommendation engine

47. Amazon.com
What you should buy
recommendation engine

48. Google
What you should fine search engine.
What's in your photo?
What do you want to say?
I can drive there for you.

49. Facebook
What’s in your bubble
Detecting suicidal thoughts
Who are you with face detection

50. Amazon Alexa
Tell me what you want Natural
Language Processing with learnable
skills

51. Salesforce.com
Applying machine learning to your
customers to give you insight.

52. x.ai
When do you want to meet?

53. Uber
From ride sharing to ride giving

54. Pandora
What you should hear. The music
genome project with intelligence

55. Winelayerz
What wines you will like to drink.

57. A.I. WORKSHOP
The differences between ML and AI. How machines ”learn". How businesses are using
the technology today. What are the future of these innovations and how will they affect
your enterprise?
FEATURING: Christopher Slee