EIC-Enginyers Industrials de Catalunya | EIC

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IV Fòrum Indústria 4.0 · Espai Endesa – Barcelona

Què és la intel·ligènciaArtificial (AI)?

Es la ciència que fa que les màquines desenvolupincertes funcions de la mateixa manera que ho faria la ment humana.

Tot allò que fa que les màquines actuïn d’unamanera més intel·ligent.

Machine learning, deep learning, xarxes neuronals, analítica predictiva, etc. són tecnologies que capaciten la AI.


Els sistemes d’intel·ligència artificial presenten quatrecaracterístiques principals

2

RAONEN

Interpreten informació, l’organitzen, ofereixenexplicacions, formulenhipòtesis… Presenten

recomanacions perquèels humans prenguindecisions

ENTENEN

Entenen expressions humanes, llegueixentexts, veuen imatges… Analitzen tot tipus de dades, tantestructurades com desestructurades…

com fan elshumans

APRENEN

Descobreixen i reconeixenpatrons, acumulen dades, millorant continuamentamb l’entrenament, de manera que

mai parend’aprendre

INTERACTUEN

Amb les capacitats de veure, parlar i escoltar,

interactuen ambels humans d’unamanera natural


Marc teòric enconstant evolució, principalment en

entorns universitarisi de recerca.

Fonaments ievolució de la IA

Permetrà superarles habilitats

humanes, tantfísiques com

mentals

IA futur

IA aplicada a diverses àrees per resoldre tasques

unitàries, “simples”

IA avui


Breu història de la IA

Turing Machines

1940s

Analogue robots

1940s

Turing Test

1950

Minsky Neural Net

1951 Dartmouth Conference Birth

of Artificial Intelligence

1956

Checkers

1957

Semantic networks

1960s

ELIZA

1966

SHRDLU

1969

1st AI Winter

1970-80

Expert systems

1982

Hopfield net/back

propagation

1982

2nd AI Winter1982to

1993

Deep Blue beats Kasparov (chess)

1997

DARPA Grand Challenge (self-driving vehicles)

2005

Watson wins Jeopardy (quiz

show)

2011

AlphaGo(Go)

2016

Alpha Zero

2017

Dartmouth Conference

Birth of Artificial

Intelligence

Checkers


Avui

IV Fòrum Indústria 4.0 · Espai Endesa – Barcelona�

IA avui: preguntar, explorar, descobrir, decidir, visualitzar…

Knowledge toolsLanguage Translator

Machine Learning

Natural LanguageClassifier

Natural Language Understanding

Personality Insights

Speech-to-Text Text-to-Speech

Tone Analyzer

Visual Recognition

Object detection

AI Designed for Business

Discovery tools

PersonalAssistant

Components reutilitzables (open source, fabricants, start-ups, acadèmia, research…) a l’abast de la comunitat de desenvolupadors


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Anomaly


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Amb aplicació a totes les àrees de l’empresa i a tots els sectors empresarials (Sanitat, Banca, Indústria, Distribució, T&T, E&U, Govern)


Digital Owner Manual “Ask Mercedes”Virtual assistant based on AI conversational technology

� Chatbot that helps drivers get immediate responses and proactive suggestions about their cars

� ”Ask Mercedes” can be accessed via an app or Facebook and other messenger services – in future also in the vehicle itself

� AI delivers a personalized and intuitive experience added by Augmented Reality features

DevOps

Conversation

Visual Recognition


Equipment downtime can be significantly reduced by combining the power of IoT with cognitive capability. Not only can predict what and when failures can happen, it can utilize cognitive capabilities to advise a user on exactly how to fix and resolve these failures.


With quality analytics from Artificial Intelligence, manufacturers can analyze hundreds of process variables, historic and real-time, to identify issues contributing to quality issues and resolve them before they occur. This drastically improves productivity and yield while reducing operation and material costs.


By utilizing cognitive capabilities, it can bring in unstructured data such as image and video which enriches the information around manufacturing processes. Combined with other IoT data, this information can produce more accurate predictions and better insights


Urban Carsharing

Intermodal Transport

Mobility AppIntroduce new consumption model like car2go Urban Car Sharing

Transform Products/Services


Cap a on anem?

Transform Customer Experience

Virtual city showroom

Transform Products/Services

Commerce platform combined with IoT

Transform Operations

Modernize their end to end Operation


Tecnologia: no és tan sols Intel·ligència Artificial…

Artificial Intelligence

Vodafone resolves more than 70% of inquiries with its TOBi AI Chatbot

Edge Computing

5.6B IoT devices will utilize edge computing for data processing in 2020

Hybrid Cloud

The hybrid cloud market to grow to $92B in 2021, from $33B in 2016

Blockchain

Early use-cases include roaming, distribution, and fraud – where CSPs lose $38B annually

5G

5G-based FWA subscription revenue will grow from $1B in 2019 to $40B by 20251

NFV

Total spend on NFV/SDN to go up to $110B by 2022

Market Forces


El camí cap al creixement i la supervivència en elsentorns actuals, passa per estar preparat per fer unaReinvenció Digital de l’empresa

Digitization involves automating internal processes such as payroll and finance

Digital transformation involves integrating across multiple digital processes. For example development of online marketplaces integrated into supply chain and distribution networks

Digital Reinvention involves fundamental reimaging of the way the organization operates and engages with its stakeholders through use of digital technologies e.g. constructing deep collaborative partnering relationships in which the organization orchestrates a partner ecosystem to deliver value

Digitization improves efficiency by applying technology to individual resources or processes.

Digital transformation digitizes whole aspects of a business producing customer experiences that support what individuals need or want.

Digital Reinvention incorporates digital technologies like never before to create revenues and results via innovative strategies, products and experiences.

Digitization

Digital transformation

Digital Reinvention


El futur


Artificial Intelligence will evolve over five dimensions

What are the various types of inputs it can sense and interpret?

How ubiquitous is the capability?

How personalized and interactive is it?

How can capability scale to meet demand?

What is the degree of autonomy in learning?Scalability

Evolving Dimensions

Learning

Ubiquity

Sensing

Personalized Interaction


L’evolució de la IA

Narrow AI

Monotarea, monodisciplina

Gran precisió I velocitat per certes activitats

Necessita gran quantitat de dades

Broad AIMultitarea, multidisciplinar

Apren i raona amb menys dades

IA distribuida

Explicable

General AI

Aprenentatge i raonament creuaten qualsevol disciplina

Gran autonomia

AI real. Consciència?

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EmergentDisruptiva

Revolucionaria

� Som aquí 2050 i més


AI Everywhere

HealthcareFinanceInsuranceAgricultureGovernmentEducationEnergy ScienceBusiness solutions

Instrumented Planet

Environmental solutionsDigital agricultureConnected carsGeospatial-temporal data and analyticsSmart sensors

Deeper Insights

Data-centric systemsDistributed Deep LearningNeuromorphic systemsQuantum computingHomomorphic encryptionMachine foresightCognitive discovery

Engagement Reimagined

Human-machine collaboration New AI modalitiesAugmented realityBlockchain for Global trade logistics, Food Safety, Payments

Personalization at Scale

Personalized healthcareMicro-segmentationPersonalized financeTargeted marketingPersonalized learningIndividualized solutions

Què tenim per endavant?


Exemples de tecnologies que aportaran valor en la IA “ample”

Snap ML: New Accelerator Drives Up to 46x Faster Training

Creating AI with AI: NeuNets and TAPAS

Cognitive Discovery: Converting PDFs to Data using Machine

Learning

AI Hardware with Neuromorphic

Computing


Reptes de futur• Entendre i resumir

Condensar ingents quantitats de dades, resums automàtics de documents

• Justícia i rectitud (fairness) en la interpretació dels resultatsDetectar i corregir informació esviaixada. Explicabilitat automàtica.

• Eines i tècniques per accelerar l’aprenentatgeSupera les barreres de l’entrenament actual, que és llarg i manual

• Multimèdia i audiovisualHabilitar xarxes neuronals cross-modals, per ser més eficients, més robustes al “soroll” i més fàcilsd’entrenar

• Parla, llenguatge natural i conversaNova generació de sistemes de diàleg, més efectius, ràpids i naturals

• Fronteres de l’aprenentatgeReduir la quantitat de dades, temps, recursos i complexitat per millorar confiança en els resultats


Deep artificial neural networks

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100.000.000 neurones, 7000 connexions sinàptiques


Neuromorphic chips and analogue memory

This thermal image shows the FPGA on the right providing data to the neurosynaptic chip on the leftQuantum computing


hConfiança, transparència, ètica

La IA no pot ser una caixa negra


The pillars of trust

Trusted AI

Is it accountable?

Lineage services can infuse trust in AI systems by ensuring all their

components and events are trackable to manage the

complete lifecycle of AI systems.

Is it easy to understand?

Knowing how an AI system arrives at an outcome is key to trust, particularly for enterprise AI. Visualization of information

flow within models, and teaching explanations.

Is it secure?

Exposing and fixing the vulnerabilities: identifying new

attacks and defense, designing new adversarial training

methods to strengthen against attack, and evaluate robustness.

Is it fair?

We must ensure it does not take on and amplify our biases by

creating methodologies to detect and mitigate bias through the life cycle of AI applications.

TransparencyExplainability Adversarial RobustnessFairness

IV Fòrum Indústria 4.0 · Espai Endesa – Barcelona��

Les persones, primer.

L’empresa cognititva és la intel·ligència humana ampliada


Ens substituiran les màquines?

Les nostres capacitats� Sentit comú� Moral� Imaginació� Compassió� Abstracció� Dilemes� Somiar� Generalizació

Les de la IA� Trobar informació� Identificar tendències� Llenguatge natural� Aprenentatge automàtic� Eliminar prejudicis� Capacitat ilimitada de treball





Gràcies!Gràcies!

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EIC-Enginyers Industrials de Catalunya | EIC