These deck contains an overview of what is commercially available in terms of Artificial Intelligence for business applications. Be aware: it was created on April 2017 and this is a very fast moving industry....

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Artificial Intelligence
for Business
Nicola Mattina
April 2017

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In our imagination…

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Artificial Intelligence in everyday products…

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Why is AI becoming usable for business?
Algorithms Data Computing
Power

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Investors are interested. A lot!

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Investors are interested. A lot!

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AI is rapidly moving from inflated expectations to productivity

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Technologies and Services

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Technologies and Research
What is available on the market
Platforms, SaaS and APIs
Services built on AI

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What is available on the market

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What is available on the market

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Defining Artificial Intelligence

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A definition of human intelligence

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A definition of artificial intelligence
The capacity of a computer to
perform operations analogous to
learning and decision making in
humans.

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3 levels of Artificial Intelligence
Artificial
Narrow
Intelligence
Specialized in
one area.
Artificial
General
Intelligence
Specialized in
all area.
Artificial
Super
Intelligence
Smarter than humans
in every way.

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3 levels of Artificial Intelligence
Artificial
Narrow
Intelligence
Specialized in
one area.
Artificial
General
Intelligence
Specialized in
all area.
Artificial
Super
Intelligence
Smarter than humans
in every way.W
ork
in
Progress
Singularity

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What are (some of) the skills of Artificial Intelligence today?
Natural Language Processing
Knowledge Representation
Machine Learning
Automatic Reasoning
Automatic Planning

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What are (some of) the skills of Artificial Intelligence today?
AI understands inputs
Natural
Language
Processing
Image
Recognition
Speech
to Text
AI manages knowledge
Ontologies
and
Linked Data
Pre-Trained
Datasets
AI learns
Machine
Learning
Deep
Learning
AI executes tasks
Automatic
Reasoning
Automatic
Planning

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Understanding inputs: Speech recognition
Speech recognition can be
used to allow applications
to take commands from
humans, to transcribe
conversations or even
participate in them.
Popular commercial
examples are Apple’s Siri,
Google Now and Amazon’s
Alexa.

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Understanding inputs: Speech recognition
https://cloud.google.com/speech/ https://www.microsoft.com/cognitive-services/en-us/speech-api

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Understanding Inputs: Natural Language Processing
http://www.moshebergman.com/study-notes/text-retrieval/week1.html
Natural Language
Processing can be used to
analyse any text to extract
topics, sentiment, meaning
and ultimately to gain
knowledge.
It is used to read the
sentiment in financial
markets, to analyse product
reviews, monitor social
media,...

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Understanding inputs: Natural language processing

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Understanding inputs: Image recognition
A technology that identifies
and understands what can
be seen in images and
video. It assigns labels to
objects and situations.
Best known applications of
Image Analysis are facial
recognition, quality controls
and self-driving technology.

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Understanding Inputs: Image recognition
https://cloud.google.com/vision/ https://clarifai.com

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Managing knowledge: Ontologies and Linked Data
An ontology is a formal
naming and definition of the
types, properties, and
interrelationships of the
entities that really or
fundamentally exist for a
particular domain of
discourse.

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Nicola teaches many different things, including user experience to
many different audiences, including students at
Roma Tre University.
Managing knowledge: Ontologies and Linked Data
Ontologies work very well but are domain-specific.
Professor Teaching Topic
Univesity

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Managing knowledge: Ontologies and Linked Data

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Managing knowledge: Ontologies and Linked Data
http://dbpedia.org/page/God_Save_the_Queen

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Managing knowledge: Ontologies and Linked Data

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Managing knowledge: Data Sets and Models

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Machine Learning: Basics
Machine learning provides
computers with the ability
to learn without being
explicitly programmed
Today it is used to better
detect diseases,
recommend content,
improve products and
services and many other
applications.

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Machine Learning: Types of learning

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Machine Learning: Problem Types
Classification is a general process related to
categorization, the process in which ideas
and objects are recognized, differentiated,
and understood.
Regression analysis is a statistical process
for estimating the relationships among
variables.
Clustering is the task of grouping a set of
objects in such a way that objects in the
same group (called a cluster) are more
similar (in some sense or another) to each
other than to those in other groups (clusters)
Anomaly detection is the identification of
items, events or observations which do not
conform to an expected pattern or other
items in a dataset.

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Machine Learning: Platforms
https://aws.amazon.com/it/machine-learning/https://studio.azureml.net/

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Machine Learning: Deep Learning
Deep Learning is part of the machine
learning field of learning
representations of data. Exceptional
effective at learning patterns.
It utilizes learning algorithms that
derive meaning out of data by using a
hierarchy of multiple layers that
mimic the neural networks of our
brain.
If you provide the system tons of
information, it begins to understand it
and respond in useful ways.

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Machine Learning: Deep Learning
A deep neural network consists of a
hierarchy of layers, whereby each
layer transforms the input data into
more abstract representations (e.g.
edge -> nose -> face).
The output layer combines those
features to make predictions

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Executing tasks: Filter spam

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Executing tasks: Play games
DeepMind DP Q-Learning
outperform humans in over
30 Atari games just by
receiving the pixels on the
screen with the goal to
maximize the score
(Reinforcement Learning).

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Executing tasks: Suggest things

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Executing tasks: Labeling images
Neural Image Caption Generator
generates fitting natural-language
captions only based on the pixels by
combining a vision CNN
(convolutional neural Network) and a
language-generating RNN (recurrent
neural network ).

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Executing tasks: Trasform movies in 3D
Deep3D can automatically convert
image/video from 2D-to-3D with
Convolutional Neural Networks. It
learns to infer 3D representations of
the world based on training set of 3D
movies.

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Executing tasks: Drive a car

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Executing tasks: Conversate

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Building an AI product

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Developers
Data Scientists
Data Platforms
Starting an AI project

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Sources
To make this presentation, I consulted many sources. Among these, the most relevant are:
• Sam Wouters, Demystifying Artificial Intelligence
• Luke Masuch, Deep Learning - The Past, Present and Future of Artificial Intelligence
• Nathan Pacer, Venture Scanner - AI Report Q1 2017
This deck was used for a lecture at Tag Innovation School in Milan on April 28, 2017.
It is released under a Creative Commons BY NC excepct for the contents that are extracted from the
presentations listed above. Those contents are property of their authors.

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