iDate: AI and blockchain

AI and blockchain
Will the highly hyped technologies change
telco and media industries?
Bertrand Copigneaux - IDATE
Bertrand COPIGNEAUX
+33 (0)4 67 14 44 05
b.copigneaux@idate.org

www.idate.org
AI and Blockchain
Seeing beyond the buzz words

www.idate.org © IDATE DigiWorld 2017 – p. 3
The Buzz words of our time
There’s a need to see beyond the buzz to understand the
strategic implications of these technologies, in the short and long
term.

AI – Blockchain a comparative analysis
The technology foundations
Defining what we’re talking about exactly
Looking at the origins of the technologies
Understanding the basic technological principles and the recent innovations
Short term applications
What’s happening today ?
What is commercially available ?
Long term vision
What are the current limitations ? What remains to be solved ?
What these technologies might become ?
What are the potential impacts ?
Which actors to benefit ?

www.idate.org
AI – Blockchain : Technology Foundations
What’s really in there ?

AI Technology Foundation
Artificial Intelligence can be defined in several ways:
 Autonomy: The ability for a machine to act on its own,
perceiving its environment, and taking actions to
maximize its chances of success in a defined task
 Problem solving: The ability for a machine, given
defined inputs to produce outputs that maximize
predefined criteria of success.
 Machine Learning: The ability to get better over time at a
defined task. Or said differently, the ability for a machine
to progress autonomously at problem solving.
 Automation
 Robotics
 IoT
 Algorithmic
 Machine Learning
 Deep Learning

AI Training and Predictions
Machine Learning, is the ability of a computer to perform tasks that go beyond the
initial static programming instructions it received.
The core principle of Machine Learning is to be able to “train” a computer program on
a data set so that, once trained, it can make use the defined model to make
prediction on its own given similar data.
“Predictions” include: detection of patterns, categorization of inputs, sorting,
predicting future trends, etc.
“Predictions” retains a strong dependency on the data fed to the algorithm

A.I. Technology Foundation - Summary
 A data analysis technology
 A large range of applications
Key Benefit:
- Software that Evolve, Learn, Predicts

Blockchain : Technology Foundations
Blockchain
(or DLT) is a
data storage
technology
Various implementations
co-exists and compete
Not limited to a specific
application type or domain
Blockchain is an information storage technology:
Decentralized
There is no need of
a central authority
« Trusted Third
Party » to validate
and store
information.
Duplicated
Numerous
synchronized are
kept, ensuring the
resilience of
information.
Immutable
Everything that is
written in a
blockchain is
written there
forever, with no
possibility of
modification or
suppression.
Authenticated
Everything written
in a blockchain is
linked in a unique
and verifiable way
to a unique user
(pseudonymous).
Public
Some of the most
notorious
blockchain are
publicly open both
for reading and
writing, others
require
permissions.

Evolutions of Blockchains
Ledger for all manner of information
Registry for any
type of data
Today the Bitcoin blockchain is still the most heavily used, but a
host of alternative initiatives have emerged for storing all types
of information in blockchains.
Use case: Transaction Ledger
• A common history easily verifiable
(audit)
• Guarantee against « double
spend » transactions
• Without necessity of a third party
authority acting as regulator and
control of transactions.
Use case: Archive and timestamping
• Clear authentication of owners
• Precise datation of when a data
has been inserted in the
blockchain
• Data is stored in a secure,
decentralized, and immutable
database.

Evolutions of the blockchain
Automated conditional transactions
The parties define
the contract
The
contract is
a set of
rules
The programme is stored
in a blockchain
It is stored in a computer
programme that codes these
rules
The nodes of the
blockchain network
execute the
programme
Smart contracts
Financial transactions are executed when the contract’s
conditions are met.
The contract is automatically executed by the network nodes:
no intermediaries
Source: IDATE DigiWorld, Blockchain, October 2016

Blockchain Technology Foundation - Summary
 A data storing technology
 Many variations around a few common principles (Decentralization,
Duplication, Authentication, Immutability)
 Many Evolutions and Application:
 Ledger of Transactions
 Archive
 Timestamping
 Automated Transactions (i.e. Smart Contracts)
 Decentralized Applications
Blockchain is a technological disruption in secured infrastructure.
• Secure and immutable data storage
• With no need for a trusted third party
Key Benefit:
- An infrastructure to share data between people with varying,
potentially competing, interests.
- without anyone having a full control of the storage infrastructure.

AI and Blockchain compared

www.idate.org
AI – Blockchain : Short Term Applications
What’s really happening ?

AI – Image Recognition
The initial application case for Deep Learning is the field of computer vision, and
more specifically image recognition.
Applying Deep Learning to Image Recognition has enabled dramatic progresses
with computer being able to reach success rates around 95%, close and sometime
better than human results.
The potential field of application include:
• Factory: identifying defective products in assembly lines
• Medical: imagery analysis
• Security: face recognition and identification
• Social network / advertising: better identify user habits and preferences

AI – Natural Language Processing
Natural Language Processing is another field in which Deep Learning has enabled
important progresses.
Error rates in speech recognition has
dropped to level comparable to
human performances.
AI also enables progresses in
semantic processing and text
generation with application in user
interfaces and translation.

Virtual Assistants
Amazon Echo
Alexa
31 millions unit
(US – 12/17)
Google Home
Google Assistant
14 millions unit
(US)
Apple HomePod
Siri
600 000 in Q1 2018
(world)
The progresses in Natural Language Processing led to the development of a new UI :
Virtual Personal Assistants (VPAs)
They are marketed as intelligent
assistants able not just of
understanding but of taking
decisions, supporting and
potentially replacing human in
several tasks
Yet for now usage
concentrate on
mundane tasks

Data Analytics
Applying deep learning to a field where algorithms are already ahead of most
humans, such as data analytics, promises potential tremendous breakthroughs.
Using deep learning approach can help in health record data analysis to improve
diagnostics, risk analysis and preventive medication.
The Mount Sinai hospital recently showed the potential of using unstructured deep
learning on the secondary use of electronic health records to predict health
status, as well as to help prevent disease or disability.

Blockchains : Cryptocurrencies and FinTech
Far from being a threat, the blockchain opens up major opportunities for the
financial industry.
Cryptocurrency economy Optimise traditional processes
•Exchange platform
•Wallet app
•Price speculation
•Loans & investments
•Blockchain audit
•Private blockchain & back-office
•International interbank payments
•Capital market
•Smart contracts for payments when
due, or on delivery
•Insurance
•Shareholder agreements
Thanks to massive financial backing, the blockchain's financial applications still
account for the majority:
 A banking system rebuilt around cryptocurrencies
 Using the blockchain to streamline traditional services’ costs

Blockchains : The ICO Model
Implementing decentralized apps relies on a financing model that takes advantage of
the possibilities opened up by the blockchain and cryptocurrencies.
Key Benefit:
- Getting Funds without diluting shares
- A “Trendy” way to attract funds

Blockchain and ownership records
The blockchain can be used as a register for all types of property.
A unique and reliable record of ownership, shared by an entire ecosystem.
Register diamonds and artwork to:
•Facilitate police inquiries
•Detect insurance fraud
•Facilitate loans and swaps
•Provide traceability and past history
Food supply chain traceability:
• Food associated with a digital tag
• The tag refers to a blockchain entry
• Information added at each step of food
processing along the supply chain
• End customer get access to life cycle
Music royalties payment
•Free streaming and download to own
services (5% commission)
•Use the cryptocurrency principle for
crowdfunding for artists.
Experimenting with blockchain for
national land registries
•Rapid audit
•Faster procedures
•Tamper-proof
National land registries

Blockchain and Insurance: Smart Contract
Smart Contract maturity is still limited but first large scale commercial use start to
appear
Based on smart contracts using the
Ethereum Blockchain
Automatic compensation in case of
flight delay (bet on your flight delay)
Live but still in test phase, need to
attract partners for the blockchain
approach to make sense.

Cryptocurrencies
AI Blockchain
Quite
Mature
Mostly
Proof of
Concepts
Image
Recognition
NLP
VPAs
ICOs
Ownership
records
Smart
Contracts
Financial Back
Office tool
Advanced Data
Analytics

www.idate.org
AI – Blockchain : Long Term vision
What they might become

AI Long Term Vision
Extending the use of Deep Learning to a large range of use case to extract
knowledge out of data

AI Long Term Vision
Dreaming of beyond human capabilities…
> Artificial Narrow Intelligence (ANI)
 Specialized in a single task
> Artificial General Intelligence (AGI)
 Equivalent to a human intelligence
> Artificial Super Intelligence (ASI)
 Beyond human capabilities
2000 2100
Today
Median
Expert
Prediction
For AGI
(2040)
Median
Expert
Prediction
For ASI
(2060)

AI Current Limitations
VPA use and capabilities are still limited.
• Mostly use as a “hand free” user interface / gadget
• User acceptance is still limited
• Still largely unable to : follow a conversation, take context into account, learn over
time and be personalized and proactive.
Deep learning is strongly dependent upon data.
• Requires availability of large data sets (not the case for every use case)
• Data access can be an issue (data ownership, data monetization, privacy…)
• Training algorithms and validating the quality of the result on more complex tasks
than basic image recognition / NLP can be an issue.
AGI and ASI are still hypothetical.
• There is no certainty that these level of AI are reachable and that the current
solutions (deep learning) will lead there.

AI Main Benefitors
The key is in the control of the data
B2C : A new way to lock-in customers for internet giants
B2B : Opportunities for data platforms

Blockchain Long Term Vision
Traditional economy
Provide a product or service
Decentralized economy
Eliminate the middlement
Internet economy
Put parties in contact
A disruptive vision:
Bold claims:
• Cryptocurrencies replacing fiat currencies
• Decentralized applications competing with Internet Giants
• …

Blockchain Current Limitations
Performances: limits of « Proof of Work »:
Number of transactions per seconds (TPS)
Resources consumption.
Today, no clear alternative to proof of work with the same level of maturity and
security (consensus algorithm is a research topic).
Smart Contract: a technology lacking maturity
Smart contracts cannot be considered today as a stable and mature technology
except for minimal use cases.
Research topics: limitations of programming languages (non turing complete)
formal proof and code validation…
Security at the system margins
Several important stake appear in the end-to-end security of blockchain solutions:
Identity validation, interoperability with legacy systems and data, validation of
data entered in a blockchain (oracle role).
These developments are necessary to go from PoC to production.
Acceptance and legal issues
The world of cryptocurrencies remains mostly separated from the rest of the economy
and very unstable
An area of speculation and uncertainties unfit for acceptance

Blockchain Main Benefitors
The blockchain enables organizations to reduce their operating costs, particularly in
the area of inter-organization exchanges (shorter timeframes, increased reliability).
It can also help reduce the number of intermediaries involved in certain types of
application.
By and large, however, it is no expected to upset existing value chains.
The blockchain, B2B infrastructure:
The blockchain as back-office infrastructure
for transactions between established
players: banks, businesses, platforms,
government agencies.
Exchanges between consumers and
producers still go through trusted third
parties.
Main Benefitors:
- IT suppliers have a new set of solutions to sell

extending existing successes to
other fields : big data processing
and predictions, general
intelligence, beyond human
capabilities…
Good for financial back office,
ownership records, supply chain data
exchange, automated financial
transactions
A.I.
A secure infrastructure for sharing
information with parties with differing,
potentially conflicting interests
Solving complex problems by learning
from very large data sets
Blockchain
Good in Computer Vision, Natural
Language Processing, and more
generally data analytics
Going out of the sandbox and proof of
concepts and establishing a new kind of
infrastructure
What it is?
What it is good for?
The challenge ahead?

IDATE DigiWorld is one of the foremost European ICT expert houses specializing
in telecom, media & internet markets and digital territories.
Since 1977, our team has delivered consultancy services, market intelligence solutions & networking
opportunities to provide an in-depth understanding of the digital world and enhance our clients’ strategic
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AI Neural Networks
Deep Learning, is a form of Machine Learning building on the “Neural Network”
approach (that dates to the 80s)
They function by defining small and
simple individual programs, artificial
neurons (called Perceptron)
The Artificial Neurons are then
connected together and arranged in a
network
Through repeating a long training process, the weights of the connections,
transfer and activation functions of each Neuron can then be optimized to take
values that enable the overall network to provide the requested answer.

AI Neural Networks
The Deep Learning trend started at the end of the 2000s, as both very large data
sets and computing power became largely available.
In Deep Learning, layers of large numbers of Artificial Neurons are stacked together.
Low level layers are able to find basic patterns that are refined into more and more
abstract concepts by each layer.

Blockchain : Technology Foundations
Transaction …
Transaction …
…
Blocks aggregate transactionsA chain of « blocks »
What is a blockchain ?
Blocks are added at the end of
the chain
The network verifies collectively that the
new block is valid
Once added blocks cannot be
deleted
Adding information in a blockchain requires
validation by a peer-to-peer network

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


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


Evolutions of Blockchains
Transaction ledger
Ledger for all
manner of
information
Automated
conditional
transactions
Decentralized
applications
Smart contractsCryptocurrencies
2008 – The idea of Bitcoin emerges in response to the financial crisis: an
alternative, decentralized currency that is independent of both political powers
and financial institutions, governed solely by mathematical and cryptographic
principles.
2009 – The first blockchain originated with Bitcoin. It is a ledger that logs
all of transactions made, and stored securely in a distributed network.Financial Registry
Initially designed as a ledger for cryptocurrencies, the principles that underpin the
blockchain have evolved over time.

New decentralized applications
If we can store and execute
computer programmes on a
blockchain network…
Decentralized applications
… We can create fully decentralized applications,
and even organisations.
The blockchain network is used as the infrastructure for decentralized apps.
Fully peer-to-peer applications with no centralized platform.
Decentralized organisations and businesses entirely managed by smart
contracts, with no administrators or employees.
Evolution of Blockchains

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