In this second session of the Elements of AI Luxembourg series of webinars, we have the pleasure to have Dr. Sana Nouzri as a guest speaker. More information, and a recording of the session, can be found on our reddit page:
eofai.lu/reddit
1. Elements of AI :
AI: Reflections, History
and Challenges
Nouzri Sana
Postdoctoral Researcher at AI Robolab
Department of Computer Science
UNIVERSITY OF LUXEMBOURG
Nouzri Sana 1
2. Agenda
I. History of AI
II. What is artificial intelligence?
III. Domains covered by AI and Related fields
IV. Demand for AI
V. AI applications
VI. AI Art applications
VII.Types of AI
VIII.Implications
Nouzri Sana 2
3. History of AI
1950
Alan Turing published a landmark paper in which he speculated about the possibility of
creating machines that think.
Alan Turing (1912-1954) was an English mathematician and logician. He is
rightfully considered to be the father of computer science
Turing Test
4. History of AI
1950 1951
Alan Turing published a landmark paper in which he speculated about the possibility of
creating machines that think.
Christopher Strachey wrote a checkers program.
And Dietrich Prinz wrote one for chess
Christopher S. Strachey (16 November
1916 – 18 May 1975) was a British
computer scientist. He was one of the
founders of denotational semantics, and
a pioneer in programming language
design and computer time-sharing.
5. History of AI
1950 1951 1956
Alan Turing published a landmark paper in which he speculated about the possibility of
creating machines that think.
Christopher Strachey wrote a checkers program.
And Dietrich Prinz wrote one for chess
John McCarthy first coined the term of “Artificial intelligence” at the Dartmouth Conference
The Dartmouth Summer Research Project on
Artificial Intelligence was a 1956 summer workshop
widely considered to be the founding event of
artificial intelligence as a field.
John McCarthy (September 4, 1927 – October 24,
2011) was an American computer scientist and
cognitive scientist
6. History of AI
1950 1951 1956 1959
Alan Turing published a landmark paper in which he speculated about the possibility of
creating machines that think.
Christopher Strachey wrote a checkers program.
And Dietrich Prinz wrote one for chess
John McCarthy first coined the term of “Artificial intelligence” at the Dartmouth Conference
MIT AI lab first set up. The research on AI began
Massachusetts Institute of Technology
7. History of AI
1950 1951 1956 1959 1960
Alan Turing published a landmark paper in which he speculated about the
possibility of creating machines that think.
Christopher Strachey wrote a checkers program.
And Dietrich Prinz wrote one for chess
John McCarthy first coined the term of “Artificial intelligence” at the
Dartmouth Conference
MIT AI lab first set up. The research on AI began
First robot was introduced to general motors assembly line
8. History of AI
1950 1951 1956 1959 1960 1966
Alan Turing published a landmark paper in which he speculated about the possibility of
creating machines that think.
Christopher Strachey wrote a checkers program.
And Dietrich Prinz wrote one for chess
John McCarthy first coined the term of “Artificial intelligence” at the Dartmouth Conference
MIT AI lab first set up. The research on AI began
First robot was introduced to general motors assembly line
First AI chatbot called Eliza was introduced by by MIT professor Joseph Weizenbaum, a
German American computer scientist
9. History of AI
1950 1951 1956 1959 1960 1966 1997
Alan Turing published a landmark paper in which he speculated about the possibility of
creating machines that think.
Christopher Strachey wrote a checkers program.
And Dietrich Prinz wrote one for chess
John McCarthy first coined the term of “Artificial intelligence” at the Dartmouth Conference
MIT AI lab first set up. The research on AI began
First robot was introduced to general motors assembly line
First AI chatbot called Eliza was introduced
IBM's Deep Blue was a chess-playing computer developed by IBM, it beats the world
champion Garry Kasparov, in the game of chess 9
……….
AI Winter
10. History of AI
1950 1951 1956 1959 1960 1966 1997 2002
Alan Turing published a landmark paper in which he speculated about the possibility of
creating machines that think.
Christopher Strachey wrote a checkers program.
And Dietrich Prinz wrote one for chess
John McCarthy first coined the term of “Artificial intelligence” at the Dartmouth Conference
MIT AI lab first set up. The research on AI began
First robot was introduced to general motors assembly line
First AI chatbot called Eliza was introduced
IBM's Deep Blue beats the world champion
Garry Kasparov, in the game of chess
In 2002, iRobot Roomba can autonomously navigate and clean homes 10
11. History of AI
2005
Stanford's racing team’s autonomous robotic car, Stanly win the 2005 DARPA Grand Challenge
The DARPA Grand Challenge is a prize competition
for American autonomous vehicles
12. History of AI
2002 2011
IBM Watson is a question-answering computer system capable of answering questions posed
in natural language, it won the $1M prize for winning in Jeopardy
13. History of AI
2002 2011
Personal assistants like Siri, Alexa, Google duplex, Cortana use speech recognition to answer
questions and perform simple tasks
2011-2014
14. History of AI
2002 2011 2011-2014 2014
Ian Goodfellow comes up with Generative Adversarial Networks (GAN)
15. History of AI
2002 2011 2011-2014 2014
Ian Goodfellow comes up with Generative Adversarial Networks (GAN)
AlphaGo beats beats world champion Ke Jie in the complex board game of Go
2016
16. History of AI
2002 2011 2011-2014 2014
Ian Goodfellow comes up with Generative Adversarial Networks (GAN)
Most universities have courses in Artificial Intelligence, AI is for every one
2016 2018-2021 And more
17. What is AI?
John McCarty definition
John McCarthy first coined in the year 1956
John McCarthy defined AI as the science and engineering of making intelligent machines 17
18. What is AI ?
AI is currently a "hot topic": media coverage and public discussion about AI is almost
impossible to avoid.
AI means different things to different people.
AI is about artificial life-forms
that can surpass human
intelligence
Almost any data processing
technology can be called AI
How should we define AI?
Nouzri Sana 18
19. What is AI?
The theory and development of computer systems able to perform task
that normally require human intelligence, such as visual perception, speech recognition and decision
making.
+ =
Intelligence
Artificial Artificial Intelligence
visual perception speech recognition decision making
19
20. What is, and what isn't AI? Not an
easy question!
Reason 1: no officially agreed definition
Even AI researchers have no exact definition of AI. The field is rather being constantly redefined
when some topics are classified as non-AI, and new topics emerge.
Automatic methods for
search and planning
Methods for processing
uncertain information
non-AI
Nouzri Sana 20
21. What is, and what isn't AI?
Not an easy question!
Reason 2: the legacy of science fiction
The confusion about the meaning of AI is made
worse by the visions of AI present in various
literary and cinematic works of science fiction.
Nouzri Sana 21
22. What is, and what isn't AI? Not an
easy question!
Reason 3: what seems easy is actually hard…
Another source of difficulty in understanding AI is that it is hard to
know which tasks are easy and which ones are hard.
While easy for you, grasping objects by a robot is extremely hard,
and it is an area of active study
…and what seems hard is actually easy
By contrast, the tasks of playing chess and solving mathematical exercises can seem to be very
difficult, requiring years of practice to master
Nouzri Sana 22
23. So what would be a more useful
definition?
Autonomy
The ability to perform tasks in complex environments
without constant guidance by a user.
Adaptivity
The ability to improve performance by learning from
experience.
Nouzri Sana 23
24. Words can be misleading
“Intelligent“ : system is intelligent, perhaps because it delivers accurate
navigation instructions or detects signs of melanoma in photographs of
skin lesions.
“Understand” : a computer vision system understands images because
it is able to segment an image into distinct objects such as other cars,
pedestrians, buildings, the road, and so on
Intelligence is not a single dimension; different AI systems cannot be compared on a single axis or
dimension in terms of their intelligence
Nouzri Sana 24
25. AI vs ML vs DL
Artificial intelligence
Machine learning
Artificial Intelligence
A technique which enables
machines to mimic human behavior
Machine learning
Subset of AI technique which
use statistical method to enable
machines to improve with
experience
Nouzri Sana 25
Deep learning
Deep learning
Subset of machine learning that
uses the concept of neural networks
to solve complex problems.
27. Related fields
Data science is a recent umbrella term (term
that covers several sub disciplines) that
includes machine learning and statistics, certain
aspects of computer science including
algorithms, data storage, and web application
development.
Robotics means building and programming
robots so that they can operate in complex, real-
world scenarios. In a way, robotics is the ultimate
challenge of AI since it requires a combination of
virtually all areas of AI.
Nouzri Sana 27
28. Demand for AI
More computational
power
BIG DATA Better algorithms Broad Investment
Nouzri Sana 28
29. AI applications
google predictive search
engine
JP Morgan chase’s contract
intelligence Platform
IBM AI technology
(healthcare)
Nouzri Sana
29
30. AI applications
Facebook (Facial features)
Twitters' AI (filter out any
offensive content)
virtual assistants (siri,
alexa, google duplex)
Nouzri Sana 30
33. AI Art applications
Computational Creativity in Art
Computational creativity is the study of building software that exhibits behavior
that would be deemed creative in humans.
Such creative software can be used for autonomous creative tasks, such as, writing
poems, painting pictures, and composing music.
AI Generated Music/Sound AI Generated Movement/Dance
AI Generated Voice
AI Generated Images / Pictures
AI Generated Data Visualization
AI Drawing / AI Painting
Nouzri Sana 33
34. AI Art applications
Living Archive: A tool for
choreography powered by AI.
Wayne McGregor is an award-winning
British choreographer who uses AI to
expand the possibilities of human
movement.
Yamaha Artificial Intelligence (AI)
Transforms a Dancer into a Pianist
Computational creativity in dance
Living Archive by Wayne McGregor
November 2019 | By Bastien Girschig, Google Arts & Culture Lab
Yamaha
35. Magenta
AI Art applications
Album composed and produced with AI.
Taryn Southern is an artist and futurist
who created the first solo album
composed and produced with AI.
Magenta Studio – A
collection of music
plugins built on
Magenta’s open source
tools and models.
MuseNet – Generate
4-minute musical
compositions with
10 instruments
Computational creativity in music
35
I AM AI Album Open AI MuseNet
36. AI Art applications
Portraits of Imaginary People
By Mike Tyka.
By using GAN, it explores the latent space of human
faces by training a neural network to imagine and
then depict portraits of people who don’t exist
Computational creativity in visual arts
Nouzri Sana
36
37. AI Art applications
Deep dream generator is a creative AI tool that create impressive paintings. With this AI-
enabled tool, you can change your photos to cool paintings in different styles.
Nouzri Sana 37
40. Types of AI
ANI
Artificial Narrow
Intelligence
Weak AI
Narrow capability
AGI
Artificial General
Intelligence
General AI
AI that equals
human intelligence
ASI
Artificial Super
Intelligence
Super AI
AI that exceeds
human intelligence
Present Future ? Possible ?
Nouzri Sana 40
The most useful definition of AI consists of 2 characteristics:
Autonomy
The ability to perform tasks in complex environments without constant guidance by a user.
+One of the ultimate goals of artificial intelligence is the ability for machines to operate on their own, with little or any human interaction, The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.
Adaptivity
The ability to improve performance by learning from experience.
+Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
“Intelligent“ : system is intelligent, perhaps because it delivers accurate navigation instructions or detects signs of melanoma in photographs of skin lesions.
the word "intelligent" easily suggests that the system is capable of performing any task an intelligent person is able to perform: going to the grocery store, peel the vegetables, washing and folding laundry, and so on.
“Understand” : a computer vision system understands images because it is able to segment an image into distinct objects such as other cars, pedestrians, buildings, the road, and so on.
The word "understand" easily suggests that the system also understands that even if a person is wearing a t-shirt that has a photo of a road printed on it, it is not okay to drive on that road (and over the person)
Artificial Intelligence (AI) is not a single piece of hardware or software, but rather a constellation of technologies
AI is sort of a process or it's a methodology in which you make machines mimic the behavior of human beings
Machine learning is a method through which you can feed a lot of data to a machine and make it learn and make its own decisions.
Deep learning, on the other hand, is a subset of machine learning that uses the concept of neural networks to solve complex problems.
Artificial intelligence, machine learning, and deep learning, are interconnected fields.
Machine learning and deep learning aids artificial intelligence by providing a set of algorithms to solve data-driven problems.
+Machine learning can be said to be a subfield of AI, which itself is a subfield of computer science. Machine learning enables AI solutions that are adaptive.
+Deep learning is a subfield of machine learning. refers to the complexity of a mathematical model (neural networks), it have been applied to fields including computer vision, machine vision, speech recognition, natural language processing,
+A knowledge base (KB) is a technology used to store complex structured and unstructured information used by a computer system.
+Expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge.
+Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos, detect objects in an image, estimate their position or handle them with care
The first reason is the computational power, AI requires a lot of computing power, one of the greatest technologies that made this possible are GPUs (A graphics processing unit)
Second most important reason is lot of data, the data is generated at an immeasurable pace through social media, trough devices, every possible way, there’s a lot of data,
Next reason is better algorithms, very effective algorithms which are based on neural networks, the concept behind deep learning
Another reason is that universities, governments, startup are all investing in AI because they believe that AI is the future
google predictive search engine, when you begin typing a search term, google makes recommendations for you to choose, so predictive searches are based on data that google collect about you, such as your browser history, your location, your age and other personal details, so by using AI, google attempts to guess what you be trying to find, now behind this is ML, DML involved
finance sector, JP Morgan chase’s contract intelligence Platform uses ML, AI and image recognition software to analyze legal documents, manually reviewing around 12 000 agreement took over 36 000 hours that o lot of time but as soon as this task was replaced by AI machine, it was able to do this in a matter of seconds so that the difference between AI and manual or human work, even though AI cannot think and reason like humans but their computational power is very strong compared to humans
healthcare, IBM is one of the pioneers that has developed AI software specifically for medicine
social media platforms like Facebook. All the auto tagging feature that you see in Facebook only AI behind it in order to detect facial features and tag your friends,
Twitters' AI which is being used to identify any sort of hate speech and terroristic languages in tweets.
virtual assistants, like siri, alexa right now, and newly another released, Google’s virtual assistant called the Google duplex, which has astonished millions of people around the world
self-driving cars, so AI implements computer vision, image detection, Deep learning in order to build cars that can automatically detect any objects or any obstacles and drive around without human intervention,
netflix, Netflix has developed a personalized movie recommendation for each of its users. 75% of what you watch are recommended by Netflix
gmail uses AI, to separate sections, for example, primary section, social section, and all of that, spam section, gmail uses AI to classify emails as spam and non spam
Will a robot take my job as an artist?
How is AI likely to change or improve my job in the next ten years?
If we teach the machine about art and styles and push it to generate novel images, what would it generate?
If we teach the machine about sound and push it to generate new sounds, can it make music?
GANs’ potential for both good and evil is huge, because they can learn to mimic any distribution of data. That is, GANs can be taught to create worlds eerily similar to our own in any domain: images, music, speech, prose. They are robot artists in a sense, and their output is impressive. But they can also be used to generate fake media content, and are the technology underpinning Deepfakes.
Artificial narrow Intelligence, (weak AI), it involves applying AI only to specific task, So, many currently existing systems that claim to use artificial intelligence are actually operating as weak AI focused on a narrowly defined specific problem.
Artificial general Intelligence (strong AI), it involves machines that possess the ability to perform any intelligent task that a human being can. Machines don’t possess human like abilities, they have very strong processing unit that can perform high level computations, but they ‘re not yet capable of doing the simple and the most reasonable things that a human being can.
Artificial super Intelligence (super AI) is a term referring to the time when the capabilities of computers will surpass humans, presently it’s seen as a hypothetical situation as depicted in movies and any science-fiction books.
