Technology Trends for 2018ºs...• Securely extend ERP, SCM and other business processes for...

Technology Trends for 2018

Jesus Robles ([email protected])

Director, Cloud Platorm Oracle EMEARiga. February 1, 2018

Conference - Open Technologies From Data to Knowledge

Copyright © 2018, Oracle and/or its afliates. All rights reserved.Copyright © 2018, Oracle and/or its afliates. All rights reserved.

THE PACE OF INNOVATION NEVER SLOWS

Artifcial Inntelligence

Innternet of Things

Blockchain

Machine Learning

Technology Trends for 2018


“By 2018,

75% of development will include cognitve/AI or machine learning functonality in at least one applicaton.”

Copyright © 2018, Oracle and/or its afliates. All rights reserved.

‸


Artficial Intelligence for the Real

World

“ Inn 2013, the MD Anderson Cancer Center launched a ‘moon shot’ project: diagnose and recommend treatment plans for certain forms of cancer using InBM’s Watson cognitiie system. But in 2017, the project was put on hold afer costs topped $62 million—and the system had yet to be used on patients.”


Three Types of Artficial Intelligence

Process Automation using Robotics

Process Automation Technologies

71 71

Gaining insight through Data

Analysis

57 57

Engaging with Customers and

Employees

24 24

Harvard Business study of 152 projects


Gaining insight through Data Analysis (38%)

Gaining insight through Data Analysis (38%)

• Propensity to buy

• Real tme fraud detecton and insurance claims

• Safety or quality problems in manufacturing

• Personalised digital Ads

• Propensity to buy

• Real tme fraud detecton and insurance claims

• Safety or quality problems in manufacturing

• Personalised digital Ads

Engaging with Customers and Employees (16%)

Engaging with Customers and Employees (16%)

• Iintelligent agents for online 24/7 support

• Internal sites for IT support, employee benefits, and HR policy.

• Product and service recommendatons for retailers

• Health treatment recommendatons

• Iintelligent agents for online 24/7 support

• Internal sites for IT support, employee benefits, and HR policy.

• Product and service recommendatons for retailers

• Health treatment recommendatons

Process automaton using RPA (47%)

Process automaton using RPA (47%)

• Data transfer from call centres into databases.

• Automatc reconciliaton across billing systems

• Reading Legal documents (Natural Language Processing)

• Data transfer from call centres into databases.

• Automatc reconciliaton across billing systems

• Reading Legal documents (Natural Language Processing)

Artficial Intelligence support business needs…

Companies are experimentng with projects that combine elements from all three categories Companies are experimentng with projects that combine elements from all three categories

Artficial Intelligence support business needs…


Business Benefits of Artficial Intelligence

Copyright © 2018, Oracle and/or its afliates. All rights reserved.88Copyright © 2018, Oracle and/or its afliates. All rights reserved. |

Business Challenges of Artficial Intelligence


Technology Challenges of AI

SCARCInTY OF SPECInALInZED SKInLLS

Domain specifc models, machine learning skills

DEVELOPMENT COMPLEXInTY

Data integration, set up eniironments, ML frameworks, libraries, GPUs

InMMENSE COMPUTE CAPACInTY NEEDED

Storage and processing of massiie data sets


Oracle AI Platorm

Embedded AIn in SaaS & PaaS• Adaptve apps that predict outcomes, anomalies

• Intelligent platorm with AI-enabled automaton

Large-Scale Data Management

• Ingest large volumes of data

Extensiie Deielopment Platorm• Common AI libraries, ML frameworks, and dev tools

High Performance Innfrastructure• Compute instances, networks, storage, GPU as a Service

Built for the AIn-Driien Enterprise

Data Preparaton

Data Enrichment

Data Lake

Machine Learning

AI Algorithms

Deep Learning

< / >

GPUFlash Storage

25 GigEthernet

Data Management & Inntegration

AIn Deielopment Platorm

High Performance Innfrastructure

ApplicatonsTrained Models

Data

AIn Embedded in SaaS & PaaS



Simplified Set Up with Oracle AI Platorm Cloud Service

Oracle PaaS

Language

Image

Video

HREmotion

Easy Deielopment

3Publish

NormalizeDataIngeston

Train TestPre

ProcessDefine2Deielop

• Frameworks• AI libraries• Samples• GPU clusters• Connect to data• Auto scale, updates• HS network, storage

• Object Stores

• Big Data CS

• Database CS

• Spark-Hadoop

Easy Data Access

+1Set UpSetup & Managed

PublishAPI

Export Model APIs


Machine Learning is based on algorithms that can learn from data without relying on rules-based programming.

McKinsey


Propensityto Buy

Features

Basic Query

Basic Analytics

Machine Learning

Behavioral Customer Segment

“Retred Cosmopolitan”

“Afuental Executve”

“New Home Mom”

“Young Successful startup”

“Executve product collector”

Probability to Buy New Product X 31% 45% 55% 21% 72%

RFM (Recency, Frequency and

Monetary Value): Purchases in the Last 3/6/12 mo.

1 item / $35 in the last 3 mo

2 items / $150 in the last 6 mo




Age / Gender Known Known Known Unknown Unknown

Marketng Preferences Mail and e-mail e-mail e-mail and

Facebooke-mail and Google+

Mail, e-mail and Twiter

CLASSInFYInNG CUSTOMERS


Analytical Data Lake – Conceptual iiew


Analytical Data Lake –Technology components


– Backed by Artficial Intelligence

The Next Killer Apps Will be Bots

Bots will start replacing mobile apps. No more looking for an app, downloading an app, updatng an app or managing an app

Source: Gartner 2017

By 2021, more than 50% of enterprises will be spending more per annum on bots and chatbot creatons than traditonal mobile app developments.


A chatbot (also chatterbot, chatterbox) is a computer program which atempts to maintain a conversaton with a person

Conversatonal Interface Driven by Artficial Intelligence


Seamless Handof Between Bot and AgentChatbots can handle millions of incoming questons

Bring it on humans!

In 2020, AI will become a positve net job motvator, creatng 2.3M jobs while eliminatng only 1.8M jobs. Source: Gartner 2017

handof to human

Cannot compute…

, but…


Embedded AIn for Coniersational Dialog

Oracle Intelligent Bots

Channel Configurator

DialogFlow Executon

Enterprise Integraton

AI Engine

• Unified cross-channel chat interface between bots & humans

• Declaratve bot builder UI for bot fow

• State machine that executes context driven workfows with scoped variables

• Actve machine learning algorithms that identfy relatonships and extract insights from unstructured data

• SDK to consume backend API’s that satsfy human requests via the bot

Custom


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Internet of Things


50Billion devices

by 2018

8Zeta bytes

of data today

$3Trillion market

by 2020

InoT is at the top of the Hype Cycle

60% of InoT Projects Fail


IOT: Challenges

NOT FOCUSED ON BUSInNESS OUTCOMES• Priority misplaced on devices and connectvity, not

business processes; Clear ROI not artculated

PROJECTS STALL AND FAInL• Complexity due to several moving parts

• IoT data not being converted into business insights

LACKS ENTERPRInSE CONTEXT• Not integrated with Supply Chain, Transportaton,

and ERP processes


Oracle IOT CloudFocused on Business Outcomes• Improve asset utlizaton, factory performance, feet

operatons, and reduce workplace safety incidents

Large-Scale Data Management

• IOT Data lake stores huge amount of data coming from sensors

Complete InOT Platorm Made Simple • Partner ecosystem for device and gateway integraton

• Train models with device simulatons (Digital Twin)

• Extensive predictve analytcs using enterprise and IOT data

Connect to Any Enterprise Sofware• Integrated with Oracle ERP, SCM, CX, HCM apps

https://cloud.oracle.com/opc/iot/partners


Blockchain


“ $176 billion in added business value by 2025; that total reaches $3.1 trillion by 2030.”

“ More than 2,500 patents have been filed in the last 3 years.”


Blockchain: Challenges

NO PLUG N PLAY FOR ENTERPRInSES• Closed ERPs, complex integratons, must write code

InNSUFFInCInENT PRODUCTInON READInNESS• Resilience, security, recoverability, global reach

CONTInNUOUS PLATFORM EVOLUTInON• Rapid technology changes

• Operatonal challenges: Member on-boarding, supportability, lifecycle management, and limited scalability


Two Types of Blockchain

Public (a.k.a. “Permissionless”)• Anyone can join the network and have a copy of the ledger, e.g.,: Bitcoin,

Ethereum

• This involves the computer resource intensive mining process to add blocks cryptographically

• Consensus models based on computatonally expensive algorithms requiring the processing power of many nodes to ensure security.

Permissioned• Closed ecosystem: members are invited to join and keep a copy of the ledger

• Who members are in the real (legal) world is known (to at least the operators of the blockchain, but not necessarily all partcipants)

• Consensus protocols depend on knowing who the members are, e.g., PBFT, for greater scalability


Oracle Strategy: Distributed Ledger Technology Cloud Platorm

Managed PaaS for Cloud & On-Prem• Pre-assembled, ready-to-use

• Dev/Integrators focus on transacton business logic

• Dynamic configuraton, expansion of business networks

Extending Enterprise Boundary

• Built-in Integratons for SaaS, PaaS and on-premises apps

• Securely extend ERP, SCM and other business processes for trusted transactons with other organizatons

• Interact with other Blockchain Networks

Enterprise-Ready• Permissioned, highly secure, with

built-in privacy/confidentality

• Highly resilient, built-in backups and recoverability

• Industry neutral

Quick Time-to-Value • Start develop applicatons within

minutes

• API driven development

• Facilitate quick experimentaton of new business processes


Components of a Permissioned Blockchain Platorm

Nodes

Consensus

Smart Contracts

Ledger (World State)

Applicatons (D-apps)

Admin Console

Membership Service


Blockchain Use Cases in Financial Services


Blockchain in FSICross border Payments Easy to implement (adapt existng infra)- High profit impact. Micropayments Low efort to implement. Low profit impact, but strategic for FSIAssets securization Ownership and transacton history of assetsAsset tokens Any form of value can be transferred via a Blockchain-tokenPost trade processing- Clearing and settlement Complex to implement. Highest economic impact

Crowdfunding ICOs as an alternatve funding vehicle for start-ups

Bonds & Loans Blockchain-based Bonds and Loans can enable secondary markets.

Trade Finance Leters of credit, bills of lading or guarantees can be made cost-efcient via the use of Blockchain and smart contracts.

Deriiatiies Critcal size of network partcipants to demonstrate efciency gains. Know Your Customer (KYC)


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SWIFT Distributed Ledger Proof of Concept


• Adequacy of Distributed Ledger Technology for SWIFTgpi

• Automated Reconciliaton of Nostro databases in Real Time

• Data Model based on the Intraday Liquidity (IDL) standard

• 33 Global Banks partcipatng in SWIFT Blockchain PoC.

SWIFTgpi Global Payment Initatve – Phase IIIPoC using Distributed Ledger Technology


DLT Sandbox using Oracle Blockchain Soluton


Oracle Cloud Deployment – Node TypesBuilt on Hyperledger Fabric V1.0


Virtual Machines Layout in Oracle Cloud


Deployment in Oracle Cloud - Summary


PoC findings


Oracle Blockchain SolutonInndustrialized Blockchain cloud platorm for enterprise

Innfrastructure and PaaS SeriicesApplicaton Container CS (Managed Docker Containers), Identty CS (identty and key mgmt),

Event Hub CS (Kafa service), Management Service

Innfrastructure and PaaS SeriicesApplicaton Container CS (Managed Docker Containers), Identty CS (identty and key mgmt),

Event Hub CS (Kafa service), Management Service

Blockchain Nodes & ContainersPeer Nodes, Smart Contract Containers,

Membership Services, Ordering Service, REST Proxy

Blockchain Nodes & ContainersPeer Nodes, Smart Contract Containers,

Membership Services, Ordering Service, REST Proxy

REST APIns for Inntegrations

REST APIns for Inntegrations

Data Seriices

Data Seriices

AdministrationDynamic Configuraton,

Monitoring and Troubleshootng

AdministrationDynamic Configuraton,

Monitoring and Troubleshootng

Pre-assembled Managed service Producton-ready Public or private cloud

On PremisesPaaS

SaaS

Public CloudIaaS, SaaS, PaaS

REST

gRPCREST

gRPC


THE PACE OF INNOVATION NEVER SLOWS

Artifcial Inntelligence

Innternet of Things

Blockchain

Machine Learning

Technology Trends for 2018 - Summary

Copyright © 2018, Oracle and/or its afliates. All rights reserved.Copyright © 2018, Oracle and/or its afliates. All rights reserved. |

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