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Artificial Intelligence overview

Jan 21, 2018

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Page 1: Artificial Intelligence overview
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Quantum leaps in the quality of a wide range of everyday technologies

thanks to the Artificial Intelligence

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Credits:https://www.yahoo.com/tech/battle-of-the-voice-assistants-siri-cortana-211625975.html

we are increasingly interacting with “our” computers by just talking to them

SpeechRecognition

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Google Translate now renders spoken sentences in one language into spoken sentences in

another, for 32 pairs of languages and offers text translation for 100+ languages.

Natural LanguageProcessing

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Google Translate now renders spoken sentences in one language into spoken sentences in

another, for 32 pairs of languages and offers text translation for 100+ languages.

Natural LanguageProcessing

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Google Translate now renders spoken sentences in one language into spoken sentences in

another, for 32 pairs of languages and offers text translation for 100+ languages.

Natural LanguageProcessing

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Now our computers can recognize images and generate descriptions for

photos in seconds.Computer

Vision

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All these three areas are crucial to unleashing improvements in robotics,

drones, self-driving cars, etc.

Source: http://edition.cnn.com/2013/05/16/tech/innovation/robot-bar tender-mit-google-makr-shakr/

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All these three areas are crucial to unleashing improvements in robotics,

drones, self-driving cars, etc.

Source:http://axisphilly.org/article/military-drones-philadelphia-base-control/

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All these three areas are crucial to unleashing improvements in robotics,

drones, self-driving cars, etc.

Source:http://fortune.com/2016/04/23/china-self-driving-cars/

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Many of these breakthroughs have been made possible by a family of Artificial Intelligence techniques popularly known as DEEP LEARNING

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Many of these breakthroughs have been made possible by a family of Artificial Intelligence techniques popularly known as DEEP LEARNING

Although the greatest impacts of deep learning may be obtained when it is integrated into the whole toolbox of other AI techniques

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Artificial Intelligence, Neural Networks,

are not a new concepts!

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John McCarthy coined the term Artificial Intelligence

in the 1950s

http://www.independent.co.uk/news/obituaries/john-mccarthy-computer-scientist-known-as-the-father-of-ai-6255307.html

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In 1958 Frank Rosenblatt built a prototype neural net, which he called the Perceptron

Source:http://www.enzyklopaedie-der-wirtschaftsinformatik.de/wi-enzyklopaedie/Members/wilex4/Rosen-2.jpg/image_preview

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Even the FIB in Barcelona, was

teaching AI in 1982

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Why, Artificial intelligence has, all of a sudden, become the next big thing

again during this decade?

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Source:Economist

,Feb25th,2010http://w

ww.econom

ist.com/node/15579717

now AI algorithms can be “trained” by exposing them to large data sets that were previously unavailable.The data deluge

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and the Computing Powernecessary to implement

AI algorithms is now available

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Do you know what “my” computer was like in 1982?

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Credits: http://w

ww

.ithistory.org/sites/default/files/hardware/facom

230-50.jpg

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Credits: http://w

ww

.ithistory.org/sites/default/files/hardware/facom

230-50.jpg

FACOM 230 – FujitsuInstructions per second: few Mips * (M = 1.000.000) Processors : 1

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Convex Computer C3480 Instructions per second: 800 Mips (400 Flops)Processors : 8

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IBM RS6000 SPInstructions per second: 192.000 MFlopsProcessors : 128

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MARENOSTRUM III - IBMInstructions per second: 1.000.000.000 MFlopsProcessors : 6046 (48448 cores)

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Until then, the increase in computational powerevery decade of “my” computer, was mainly

thanks to CPU improvements!

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Why is Deep Learning so popular and in demand these days?

(CPU improvements?)

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SOURCE: https://www.hpcwire.com/2016/11/23/nvidia-sees-bright-future-ai-supercomputing/?eid=330373742&bid=1597894

Since then, the increase in computational power for deep learning has not only been from CPU improvements …

but also from the realization that GPUs (NVIDIA) were 20 to 50 times more efficient than traditional CPUs.

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And Intel … (*) Intel spent more than $400 million to buy this deep-learning startup.

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And AMD…

https://www.hpcwire.com/2016/12/13/amd-instinct-machine-intelligence/?eid=330373742&bid=1617147

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And Google ...

Google revealed few months ago, that for over a year it had been secretly using its own tailor-made chips, called tensor processing units, or TPUs, to implement applications trained by deep learning.

SOURCE: Google

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Marenostrum 4 will have more than 3,400 new generation Intel Xeon processors nodes & emerging technologies as

Power + NVIDIA GPUs, Intel Knights Landing and Intel Knights Hill, ARMv8, …

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COMPUTING POWER is the real enabler!

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What if I do not have this hardware?

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However, now we are entering into an era of computation

democratization for companies !

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And what is “my/your” computer like now?

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Source: http://www.google.com/about/datacenters/gallery/images

And what is “my/your” computer like now?

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28.000 m2

Credits:http://datacenterfrontier.com/server-farms-writ-large-super-sizing-the-cloud-campus/

Huge data centers!

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Foto:Go

ogle

28.000 m2

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Foto:Go

ogle

28.000 m2

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Foto:Go

ogle

28.000 m2

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For those (experts) who want to develop their own software, cloud services like Amazon Web Services

provide GPU-driven deep-learning computation services

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And Google ...

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And what about the software that we require for AI?

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An open-source world for the AI software

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Plentiful open-source software have greased the innovation process

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as has an open-publication ethic, whereby many researchers publish their results immediately on one

database without awaiting peer-review approval.

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And for “less expert” people, various companiesare providing a working scalable implementation of

ML/AI algorithms as a Service (AI-as-a-Service)

Source: https://twitter.com/smolix/status/804005781381128192Source: http://www.kdnuggets.com/2015/11/machine-learning-apis-data-science.html

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Artificial intelligence will transform everything

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Even the food we eat or the beer we drink will be affected!

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Even the food we eat or the beer we drink will be affected!

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Source: http://edition.cnn.com/2013/05/16/tech/innovation/robot-bartender-mit-google-makr-shakr/

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Source: http://edition.cnn.com/2013/05/16/tech/innovation/robot-bartender-mit-google-makr-shakr/

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Robot bartender creates crowd-sourced cocktails

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Artificial Intelligence application areasSo

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Artificial Intelligence application areasSo

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Computers can now teach themselves

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No human being has programmed a computer to perform any of the stunts described above.

Expose a learning algorithm to terabytes of data to train it, and then allow the computer

to figure out for itself how to proceed.

Source: https://cs.byu.edu/artificial-intelligence-and-machine-learning

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AlphaGo wasn’t designed to play Go, it learnt it by playing!

Source: http://fortune.com/2016/04/23/china-self-driving-cars/Source: https://gogameguru.com/alphago-defeats-lee-sedol-game-1/

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And this can be applied to many sectors, not just for playing!

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IBM has bought a handful of companies with vast stores of medical data databases and is using Artificial Intelligence

to try to help doctors spot diseases more rapidly.

http://www.techradar.com/news/calling-dr-watson-ibms-ai-helps-to-diagnose-diseases

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A bit of provocation!(To stimulate further discussion during Q&A)

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source:http://www.express.co.uk/sport/football/779169/Barcelona-manager-news-Ernesto-Valverde-Luis-Enrique-Mauricio-Pochettino

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AlphaGo: can we use it for doing a step further?

Remember: It wasn’t designed to play Go, it learnt to compete by himself!

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• Opta Sports• Instat• Stats Prozone• Tracab• Beemray• nac• Wyscout• Er1c• Metrica Sports• Mediacoach• ...

Some of my friendstold me about:

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ADVERSARIAL SEARCH TREE: example Tic-Tac-Toe

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Fortunately...

Football is a complex game of strategy,

a field of imperfect information!(this is not the case of GO)

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Libratus?

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19.0000.000hoursofcomputation

Poker: an imperfect information game with 10160 combinations

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Like Poker, football has an enormous amount of potential game states, in which heaps of different actions are possible in every game situation

Libratus: can we use it for doing a step further?

T. Sandholm: “The algorithmswe used are not poker specific,they take as input the rules ofthe game and output strategy.”

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http://www.csmonitor.com/USA/Society/2017/0204/NFL-viewership-decline-Was-2016-a-turning-point-for-fans

A little more provocative!

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https://machinelearnings.co/artificial-intelligence-and-humanless-sports-33-70a8b6eb2ede#.hss2cfs67

Will robots, controlled by AI, one day replace humans in our most widely-viewed sports?

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And ....

We talk later J

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In the past, a lot of companies wished they had started thinking earlier about their Internet strategy.

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In the past, a lot of companies wished they had started thinking earlier about their Internet strategy.

I think in a few years from now there will be a number of companies that wish they had started thinking earlier about their AI strategy.

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In the past, a lot of companies wished they had started thinking earlier about their Internet strategy.

I think in a few years from now there will be a number of companies that wish they had started thinking earlier about their AI strategy.

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http://www.JordiTorres.Barcelona

[email protected] - @JordiTorresBCN