Secular Technological Tailwinds

Trends vs. Predictions

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“ A prediction or forecast is a statement about the way

things will happen in the future (…) ” Wikipedia

“Trend: To extend in a general direction : follow a general course ”

Webster Dictionary

http://en.wikipedia.org/wiki/Forecasting

http://en.wikipedia.org/wiki/Future

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Predictions

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Trends

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• Concerned about learning theprocess, the interactions and theemerging laws.

Trends Predictions

• Concerned about being right.

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Yes, we may use trends to make predictions.

Steve Ballmer, former chief executive of Microsoft, on the iPhone shortly

after Steve Jobs announced it. Ballmer went on to promote Microsoft's cheaper phones,

saying "right now we're selling millions and millions and

millions of phones a year. Apple is selling zero."

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More information doesn’t imply more accuracy.

There is no free lunch.


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“Trend: To extend in a general direction : follow a general course ”

Webster Dictionary




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“Trend: To extend in a general direction : follow a general course

” Webster Dictionary




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“Trend: To extend in a general direction : follow a general course

” Webster Dictionary

This is what this presentation is about.



Secular Technological Tailwinds(or trends!)

Dionisio Chiuratto AgourakisFounder / CEO – J!Quant

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Dionisio [email protected]

https://plus.google.com/+DionisioChiuratto/

Facebook: Dionisio Chiuratto

Twitter: josaum

YO!: DIONISIO

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Business (BBA)FGV-EAESP

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MSc Comp. Eng.ITA

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FounderJ!Quant

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Cloud

Computing

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Cloud for what?!

Why should we let things go from our premises?

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Cloud for what?!

IT Overall Hardware Costs are Decreasing...

but change in IT is very expensive.

And it takes lots of time.

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Cloud for what?!

So came outsourcing.

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Cloud for what?!


Outsourcing was the first attempt to have IT-as-a-service.Whenever there was change, the contractor adapted (or should have).

“If IT isn’t our core business, why have it in-house?”

So the servers, databases, developers and support team were gone.

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Cloud for what?!


Outsourcing was the first attempt to have IT-as-a-service.Whenever there was change, the contractor adapted (or should have).

“If IT isn’t our core business, why have it in-house?”

So the servers, databases, developers and support team were gone.

And so there was a bug...... and the company was unable to invoice customers for a week.

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Cloud for what?!

There was (and there is) a need for reliability in IT, but with tight budgets and control over the process.

There was (and there is) a need for quickly scaling storage, processing, networking and licensing.

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Cloud for what?!

I don’t want someone to take care of my ERP. I have the right guys.

I want someone to take the burden of hosting the infrastructure for my ERP.

I don’t want someone to take care of my DB. I have my DBA.

I want someone to take the burden of hosting the infrastructure for my DB.

And updating them.And taking care of their maintanance, power shutdowns, backups...

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Cloud for what?!

The cloud concept can be understood as a evolution from the IT outsourcing desires.

Outsourcing

Infrastructure-as-a-Service (IaaS)

Platform-as-a-Service (PaaS)

Software-as-a-Service (SaaS)

Monitoring-as-a-Service (MaaS)

Communication-as-a-Service (CaaS)

AWS (EC2, RDS, ...)

AWS – Elastic Beamstalk

Office 365

Datadog

Skype

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Got it. Now why so much buzz about it?

Conceptually, both for users and enterprises, the cloud allowed a detachment from the physical IT.

Before After

My computer with:my hardware, my apps, mymusic, my documents, mydata, my contacts, my e-mails and my games.

There is this place called“Cloud” which holdseverything, no matter thedevice I’m using to accessit.

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We just need a minute (or twenty) to getthrough the evolution of the...

Ok! Hold on about cloud computing!

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Internet1.0

Read-Only WEB

The Shopping Cart

Company Page

Your own (html-coded) Personal Home Page!

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Internet 1.0

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Internet 1.0The internet of pages!

Site 1 Site 2LINK

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Internet2.0

Read/Write WEB

Blogs

Social Networks

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Internet 2.0

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Internet 2.0Social Internet / Collaborative

Open-sourceLike

ShareRepositories

Crowd-sourcingCrowd-funding

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Internet 2.0PROSUMER

It became easy for anyone not only consume, but also produce content over the internet.

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Everybody started producing contents, usingPaaS and SaaS.

Social media emerged.

Ok! We’re back with the cloud!

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http://articles.economictimes.indiatimes.com/2012-05-27/news/31860969_1_instagram-largest-online-retailer-users

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The cloud enabled us all to be creators in the internet.

The cloud enabled the mobile smart-devices widespread.

The cloud enabled companies to process and store HUGE amounts ofdata (more of that soon in the big data section)

The cloud enabled us all to connect with each other and share.

Without buying more hardware or dealing with any IT-specificproblems.

RESPECT THE BUZZ!

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Semantic Web

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Internet 2.0 – 3.0

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It’s all about context!

The cloud got us covered with the infrastructure, platform andsoftwares. Now other questions arise:

“Who’s in the picture?”Twitter Trending Topics

#hashtagApple Siri

Microsoft CortanaGoogle Now

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It’s all about context!

People have been producing and interactingwith contents over the internet. We’veevolved so much!

...

Meh.

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The problem. Yes there is a problem.

The internet was made for people…Limited Time

Limited KnowledgeLimited Accuracy

Ambiguous Concepts…

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How do we search for and fetch information?

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How do we search for and fetch information?

How do we make a potato salad?

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Internet < 3.0

A person browses, searches, filters and reports the results.

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Semantic WebLinked DataOntologies

Internet > 3.0

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Internet > 3.0A thing browses, searches, filters and reports the results.

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Internet > 3.0URL = http://www.receitas.com.br/Palmirinha/Batata.html

Page with Recipes

Why only define addresses for pages?Pages are for people…

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Internet > 3.0URI

A universal address for…anything.

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Internet > 3.0

URI http://www.productontology.org/id/Potato_salad

URI http://purl.org/goodrelations/v1#ProductOrService

URI http://purl.org/goodrelations/v1#closes

http://www.productontology.org/id/Potato_salad

http://purl.org/goodrelations/v1#ProductOrService

http://purl.org/goodrelations/v1#closes

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Internet > 3.0The Semantic Web has the purpose of conecting and relating data.

The Semantic Web is based on LINKED DATA.

The Semantic Web is MACHINE READABLE.

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RDF triples?

Sorocaba , belongs to , SP stateSubject Predicate Object

SP state, has climate , Subtropical

RDF – Resource Description Framework

Subject Predicate Object

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SPARQL

SELECT ?cityWHERE {

?city relationship:belongs ?state?state relationship:hasClimate “Subtropical”

}

List all cities in the state of SP that has the Subtropical climate.

How to make queries in a knowledge graph.

57http://commons.wikimedia.org/wiki/File:Rdf_graph_for_Eric_Miller.png

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Wikipedia

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Ontologies

Explicit representation of knowledge –definitions and relationships

Formal 1st order logic

XML-based

Object-Oriented(?!)

OWL – Ontology Web Language

http://www.inf.unibz.it/~franconi/dl/course/slides/kbs/kbs-modelling.pdf

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Internet of Things

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Ok, so far we’ve seen that:

• Cloud computing gave us a smart(cheap?) andscalable way of using platforms, softwares andinfrastructure;

• We are producing A LOT of content through;

• Semantic web is giving context, meaning andrelationship to data.

• Semantic web makes data machine-readable.

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Now...The machines! (and other things)

As the cloud concept is interesting because wedetached from physical devices...

...the semantic web is interesting because it willdetach us from the graphical user interfaces. (andfrom browsing the internet)

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• Hardware costs are falling. (and are more powerfull)

• M2M (machine to machine) communication is growing fast

• Advanced Software

• Cloud Services

http://www.microsoft.com/en-us/server-cloud/internet-of-things.aspx

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http://www.opensource.com

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Dev

ices

, se

nso

rs, c

ame

ras,

....

KnowledgeBase

Processing Results

Dev

ices

, se

nso

rs, c

ame

ras,

....

Cloud Services (IaaS, PaaS, SaaS)

Internet...of things

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A lot of things connected throughthe internet, talking to each otherand living within the world aroundthem, creates data...a lot of data...

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Big Data

71http://www.binarylaw.co.uk/2010/11/08/the-hype-cycle/

The hype cycle! (or the buzz evolution chart)

Take my money!!!

Meh. Doens’t work.

Interesting. Shouldanalyse the pros andcons!

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What is Big Data?

• Companies have been producing and storing data since the ERP’s, CRM’s, BI’s, WMS’s, etc. adoption waves.

• Users have been producing content, giving away personal informations, and (lettingbig cloud tech companies) storing it since the PROSUMER feature of the web >= 2.0.

• With the widespread of IoT, billions of new devices are starting to produce and storedata.

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What is Big Data?

That’s Big Data.

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What is Big Data?

That’s Big Data. Really.

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What is Big Data?

That’s Big Data. Really.

Just tons and tons of data that are now being created and stored.

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So...?

Big Data by itself is nearly useless.There were important developments on processing and storing peta/hexa/yota-scale

data.But as for business and individuals, there were very few outcomes.

Nice solutions were deployed: visualization of twitter hash-tags in real time and geo-located. Truck-tracking, health-care experiments on collecting patient’s data, and so on.

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So...?

But the killer application for Big Data is yet to come.

And other buzz-words (Analytics? Deep learning?) might take the merit for themselves.

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So...?

And the reason is that...

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Big Data won’t do anything without “Big Algorithms”.

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Insights do not emerge by themselves.They need algorithms for Optimization, AI, Data Mining, Graphs, ...

And these requires processing power.

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Parallelism

82http://5gnews.org/critique-pure-speed/

83http://5gnews.org/critique-pure-speed/

3-4 GHz

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Where is the 100GHz processor?

CPU’s have been advancing in speed since they were born.

There are a number of factors resulting in the overall speed of a CPU, but by far themost straightforward is the clock speed (the MHz, GHz !)

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Now it is easy to aknowledge that companies such as Intel or AMD are no longerincreasig the clock speed.

A barrier was hit around 3-4GHz. Why is that?

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HEAT!

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We can’t afford any more frequency increases with silicon boards.

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But...computing power continues to expand, right?

Yes. There are two major avenues of computing power growth.

New Materialsand Hardwares

Parallelism

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New Materials andHardwares

Parallelism

Post-SI Computing

• Graphene• Silicene• Quantum Computing

materials (nanotechnology)

Coarse-Grain Parallelism

• Distributed Computing• Hadoop

Fine-Grain Parallelism

• Multi-Core Processing• Many-Core Processing




• Multi-Core Processing• Many-Core Processing

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New Materials andHardwares

Post-SI Computing

• Graphene• Silicene• Quantum Computing

materials (nanotechnology)

Under Research! In Stock!

Parallelism

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Parallelism



Master

Slave Slave ... Slave

TaskTask

Task

MAP

Master

REDUCEPartial Ans.Partial Ans.

Partial Ans.

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Parallelism



How many letters in this sentence?

Slave Slave Slave

Counts: 7 Counts: 9 Counts: 12

Master

Sum Reduce: 7 + 9 + 12 = 28

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Parallelism


• Multi-Core Processing

http://www.techpowerup.com/reviews/Intel/Core_i7-5960X_5930K_5820K_Comparison/2.html

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Parallelism


• Many-Core Processing


Massively Parallel Processing Paradigm

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Parallelism





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Parallelism





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Paralellism is the way to go on speeding up applications and data processing.

All major tech companies are using parallelism (GPU’s, Xeon Phi’s, Hadoop) toanalyse, process and store data.

Parallelism is the way to go with Big Data.

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Paralellism is the way to go on speeding up applications and data processing.

All major tech companies are using parallelism (GPU’s, Xeon Phi’s, Hadoop) toanalyse, process and store data.

Parallelism is the way to go with Big Data.

http://www.networkworld.com/article/2167576/tech-primers/hadoop---gpu--boost-performance-of-your-big-data-project-by-50x-200x-.html

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But even with lots of data and the correct processingapproach through parallelism,

one question remains:

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Where does insights comes from?

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Algorithms

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An algorithm is a set of instructions to be performed.

To be honest, all codes are algorithms by definition.

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There are, however, non-trivial sets of instructions (i.e. algorithms) that aims tosolve specific problems.

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What is the shortest path between two nodes in a directed graph?

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Graphs 101:

Vertices (nodes) – Circles

Edges – Lines connecting them

If the lines have arrows – Directed Graph (Digraph)

If the lines doesn’t have arrows – Undirected Graph

The numbers over the edges indicates the weight of each one.

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http://www.googlemaps.com

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Ok! There’s an app for that!

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Ok! There’s an app for that! algorithm for that!

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Dijkstra Algorithm (1956)

http://en.wikipedia.org/wiki/Dijkstra%27s_algorithm

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Dijkstra Algorithm (1956)

Shortest path is considered solved by the academia.

The computational time complexity is

This means that if you run the algorithm in your computer with say, 5 vertices, and it takes 10s to run.

When you run it with 10 vertices (2x), it is guaranteed that in the worst case it will take 40s (4x) to run.

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Nice, but not every problem is under our control.

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What is the shortest path in a directed graph, leaving from node A, passingthrough all vertices and returning to A? (TSP = Travelling Salesman Problem)

A A

http://mathworld.wolfram.com/TravelingSalesmanProblem.html

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This is called NP-Complete. No one knows the time complexity of the problem, and there is no known analytical solution to it.

A A

http://mathworld.wolfram.com/TravelingSalesmanProblem.html

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And there are the so-called “Learning Algorithms”

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How do algorithms learn anyway?

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How do algorithms learn anyway?

2 steps:

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Step 1: Trainning

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Number of Ed. Institutions in the city Ipads sold (x100)

1 1

2 4

3 4

… …

10 20

Trying to learn the law relating Ipad sales with educational institutions

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Here, learn is the process in which we seek the best red-dotted line.

Because once we find it, we’ll know a mathematical formula relating the two variables.

Best can mean anything you like. In most cases, we are looking for the best fit, i.e. the line that minimizes the error across the training set.

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Looking at past data, applying some black-box “learning algorithm” and inferring a mathematical relationship between variables.

The trainning phase is the most time and resource-consuming part of the process.

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Step 2: Processing

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Once we’ve learned the relationship, let’s say it is:

Ipads sold = 2*ed.Inst

If now we want to predict the number of ipads sold in a city with 20 educational institutions, we only need to do a few operations.

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Running already-trained algorithms is lightweight (compared to trainning).

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That’s how Siri (and Cortana, and Google Now) talks to you.

They’ve been trained for long hours on powerful hardwares, and they now can rely on the smartphone hardware to execute the algorithm and “understand” what you meant with “I am hungry”.

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Trainning

• Heavyweight• Time and resource-

consuming• Seeks minimize

errors and maximize generality

• Take place in huge processing clouds

Processing (predicting, classifying, …)

• Lightweight (relative)• Real-time (or almost)• Only apply the pre-

determined operations• Might take place even

in mobile devices

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Trainning

• Heavyweight• Time and resource-

consuming• Seeks minimize

errors and maximize generality

• Take place in huge processing clouds

Processing (predicting, classifying, …)

• Lightweight (relative)• Real-time (or almost)• Only apply the pre-

determined operations• Might take place even

in mobile devices

Both processes can be severely sped-up with parallel computing.

129http://www.gputechconf.com/

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(really) nice

evidences

Drones, 3D-Printers, Self-Driving Cars, 4.0 Manufacturing, ...

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Drones (UAV)

http://nypost.com/2015/04/12/war-against-isis-shows-limits-of-drones/

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3D-Printing

http://www.3dprinters.nl/wat-is-een-3d-printer/

133http://www.telegraph.co.uk/motoring/road-safety/10570935/Autonomous-cars-is-this-the-end-of-driving.html

Self-driving cars

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The 4th Industrial Revolution

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One last thing…

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One only prediction:

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Algorithms will be the new standard.

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For people’s jobs.

140http://www.forbes.com/sites/roberthof/2015/01/31/now-even-artificial-intelligence-gurus-fret-that-ai-will-steal-our-jobs/

“The U.S. took 200 years to get from 98% to 2% farming employment,”

“Over that span of 200 years we could retrain the descendants of farmers.”

“With this technology today, that transformation might happen much faster,”

Self-driving cars, he suggested could quickly put 5 million truck drivers out of work.

Andrew Ng

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For companies' competition.

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For companies' competition.

For countries’ sovereignty.

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That’s why...

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50 billionsNew devices will be connected by 2020

http://share.cisco.com/internet-of-things.html

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14 trillionDollars added to the global economy by 2030

http://www.accenture.com/SiteCollectionDocuments/PDF/Accenture-Industrial-Internet-of-Things-Positioning-Paper-Report-2015.PDF

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get ready!

Thanks!

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Dionisio Chiuratto [email protected]

mailto:[email protected]

Technology

Secular Technological Tailwinds