The document discusses emerging technologies in 2019 including artificial intelligence, constant connectivity, and intuitive interfaces at massive scale. It highlights areas like AI-assisted healthcare diagnostics, intelligent and connected farming, and insurance through APIs. The document argues that next-generation technologies will enable human-centric data, computing, and connectivity at an unprecedented scale through advances in AI, machine learning, serverless architectures, and cross-platform development.
AWS at 2017 FS-ISAC APAC Summit: Move Better, Faster and More Securely: Cloud...Amazon Web Services
Cloud technology has made enterprise-wide digital transformation an achievable reality, even for the largest financial services companies. Organizations can now rearchitect operating models to improve the way they interact with customers, regulators, employees and service partners. It is also opening avenues to experiment with innovations like IoT, blockchain and machine learning, among others. However, a common misperception is blocking adoption for many organizations: on-premise IT infrastructure is more secure than the cloud. The reality is financial services organizations migrating to the cloud have access to some of the most innovative security technologies on the market today—systems so robust that they would cost millions of dollars to build in-house. In this session, you will hear an overview of how cloud-enabled programs can enhance your organization’s security postures and make you more secure than your on-premise status.
Hear how customers adopt AWS Cloud at scale. This session will be presented by Jonathan Allen – AWS Enterprise Strategist and Evangelist. Sharing some of his personal experience as the previous CTO of Capital One and his lessons learned moving to cloud and from working with many customers across the paradigms of People, Process and Technology and leveraging first-hand knowledge of the AWS Cloud Adoption Framework and Mass Migration best practice.
Speaker: John Allen, Enterprise Strategist, AWS
In this session, AWS will cover our Shared Responsibility Model in relations to Security and our Compliance Program. Customers can expect to learn about how AWS works with customers to build solutions to secure their cloud-based environments. They will also come away with an understanding of our compliance program and what security assurances they inherit as customers
AWS at 2017 FS-ISAC APAC Summit: Move Better, Faster and More Securely: Cloud...Amazon Web Services
Cloud technology has made enterprise-wide digital transformation an achievable reality, even for the largest financial services companies. Organizations can now rearchitect operating models to improve the way they interact with customers, regulators, employees and service partners. It is also opening avenues to experiment with innovations like IoT, blockchain and machine learning, among others. However, a common misperception is blocking adoption for many organizations: on-premise IT infrastructure is more secure than the cloud. The reality is financial services organizations migrating to the cloud have access to some of the most innovative security technologies on the market today—systems so robust that they would cost millions of dollars to build in-house. In this session, you will hear an overview of how cloud-enabled programs can enhance your organization’s security postures and make you more secure than your on-premise status.
Hear how customers adopt AWS Cloud at scale. This session will be presented by Jonathan Allen – AWS Enterprise Strategist and Evangelist. Sharing some of his personal experience as the previous CTO of Capital One and his lessons learned moving to cloud and from working with many customers across the paradigms of People, Process and Technology and leveraging first-hand knowledge of the AWS Cloud Adoption Framework and Mass Migration best practice.
Speaker: John Allen, Enterprise Strategist, AWS
In this session, AWS will cover our Shared Responsibility Model in relations to Security and our Compliance Program. Customers can expect to learn about how AWS works with customers to build solutions to secure their cloud-based environments. They will also come away with an understanding of our compliance program and what security assurances they inherit as customers
Amazon Web Services proporciona una amplia gama de servicios que le ayudarán a crear e implementar aplicaciones de análisis de big data de forma rápida y sencilla. AWS ofrece un acceso rápido a recursos de TI económicos y flexibles, algo que permitirá escalar prácticamente cualquier aplicación de big data con rapidez, incluidos almacenamiento de datos, análisis de clics, detección de elementos fraudulentos, motores de recomendación, proceso ETL impulsado por eventos, informática sin servidor y procesamiento del Internet de las cosas.
https://aws.amazon.com/es/big-data/
AWS Summit Berlin 2013 - Your first week with EC2AWS Germany
Amazon Elastic Compute Cloud (Amazon EC2) provides resizable compute capacity in the cloud and is often the starting point for your first week using AWS. This session will introduce these concepts, along with the fundamentals of EC2, by employing an agile approach that is made possible by the cloud. Attendees will experience the reality of what a first week on EC2 looks like from the perspective of someone deploying an actual application on EC2. You will follow them as they progress from deploying their entire application from an EC2 AMI on day 1 to more advanced features and patterns available in EC2 by day 5. Throughout the process we will identify cloud best practices that can be applied to your first week on EC2 and beyond.
In this session we will cover the most common cloud security questions that we hear from customers. We provide detailed answers for each question distilled from our practical experience working with organisations around the world. This session is for everyone curious about the cloud, cautious about the cloud, or excited about the cloud.
Organizations are using IoT to transform both internal- and customer-facing processes. However, it is difficult to add significant value without business intelligence, contextualization, and a platform that is accessible to business users. Salesforce IoT and AWS IoT enable you to securely connect a network of devices to your CRM to automate smart actions based on specific events. Easily build orchestrations using clicks, not code.
Building an Investment Case for Mass Migrations to AWS - AWS Summit SG 2017Amazon Web Services
While cloud is fast becoming the new normal for organisations of all sizes, many IT executives & budget owners struggle to articulate the business value of moving to the cloud in terms that resonate with the Board and the broader C suite. In this session, we will talk through a live customer migration investment case that we had developed for a customer to undertake a commercial evaluation of their move to the cloud. It will illustrate the true impact of cloud computing on the overall IT cost base along with migration costs and associated non-cost benefits. Finally, we will discuss how AWS can support you in developing a similar investment case for your organization through a holistic framework.
1. Cloud Adoption Journey reference framework to help Teams move to Cloud and become Cloud Native
2. Define basic Pillars to include Security & Compliance, Costs Optimization, Scalability and Performance as well as Operational Excellence, AWS Well-Architected as guidance
3. Goal is to assess and guide Companies/Teams in Portfolio to faster adopt and evolve Cloud concepts to focus on Business value
4. Governance as a key driver to boost flexibility, reduce risks and foster efficiency
5. Enterprise Transformation Architecture offerings
Interconnect with Ecosystems and Things- AWS Summit SG 2017Amazon Web Services
Today's enterprises are interdependent and cloud enabled. There are more points of engagement with more users, partners and providers across an ever-widening footprint.
Integrating Amazon SageMaker into your Enterprise - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Get an introduction to Amazon SageMaker
- Learn how to integrate Amazon SageMaker and other AWS Services within an Enterprise environment
- View a walkthrough of the machine learning lifecycle to cover best practices in the ML process
Amazon Web Services proporciona una amplia gama de servicios que le ayudarán a crear e implementar aplicaciones de análisis de big data de forma rápida y sencilla. AWS ofrece un acceso rápido a recursos de TI económicos y flexibles, algo que permitirá escalar prácticamente cualquier aplicación de big data con rapidez, incluidos almacenamiento de datos, análisis de clics, detección de elementos fraudulentos, motores de recomendación, proceso ETL impulsado por eventos, informática sin servidor y procesamiento del Internet de las cosas.
https://aws.amazon.com/es/big-data/
AWS Summit Berlin 2013 - Your first week with EC2AWS Germany
Amazon Elastic Compute Cloud (Amazon EC2) provides resizable compute capacity in the cloud and is often the starting point for your first week using AWS. This session will introduce these concepts, along with the fundamentals of EC2, by employing an agile approach that is made possible by the cloud. Attendees will experience the reality of what a first week on EC2 looks like from the perspective of someone deploying an actual application on EC2. You will follow them as they progress from deploying their entire application from an EC2 AMI on day 1 to more advanced features and patterns available in EC2 by day 5. Throughout the process we will identify cloud best practices that can be applied to your first week on EC2 and beyond.
In this session we will cover the most common cloud security questions that we hear from customers. We provide detailed answers for each question distilled from our practical experience working with organisations around the world. This session is for everyone curious about the cloud, cautious about the cloud, or excited about the cloud.
Organizations are using IoT to transform both internal- and customer-facing processes. However, it is difficult to add significant value without business intelligence, contextualization, and a platform that is accessible to business users. Salesforce IoT and AWS IoT enable you to securely connect a network of devices to your CRM to automate smart actions based on specific events. Easily build orchestrations using clicks, not code.
Building an Investment Case for Mass Migrations to AWS - AWS Summit SG 2017Amazon Web Services
While cloud is fast becoming the new normal for organisations of all sizes, many IT executives & budget owners struggle to articulate the business value of moving to the cloud in terms that resonate with the Board and the broader C suite. In this session, we will talk through a live customer migration investment case that we had developed for a customer to undertake a commercial evaluation of their move to the cloud. It will illustrate the true impact of cloud computing on the overall IT cost base along with migration costs and associated non-cost benefits. Finally, we will discuss how AWS can support you in developing a similar investment case for your organization through a holistic framework.
1. Cloud Adoption Journey reference framework to help Teams move to Cloud and become Cloud Native
2. Define basic Pillars to include Security & Compliance, Costs Optimization, Scalability and Performance as well as Operational Excellence, AWS Well-Architected as guidance
3. Goal is to assess and guide Companies/Teams in Portfolio to faster adopt and evolve Cloud concepts to focus on Business value
4. Governance as a key driver to boost flexibility, reduce risks and foster efficiency
5. Enterprise Transformation Architecture offerings
Interconnect with Ecosystems and Things- AWS Summit SG 2017Amazon Web Services
Today's enterprises are interdependent and cloud enabled. There are more points of engagement with more users, partners and providers across an ever-widening footprint.
Integrating Amazon SageMaker into your Enterprise - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Get an introduction to Amazon SageMaker
- Learn how to integrate Amazon SageMaker and other AWS Services within an Enterprise environment
- View a walkthrough of the machine learning lifecycle to cover best practices in the ML process
Join us to see how Public-sector organizations and AWS Partners are combining Smart Devices and Artificial Intelligence to create flexible, secure and cost-effective solutions. Applying machine learning models to live video/audio, cameras can be transformed into flexible IoT devices that perform critical functions around public safety, security, property management, smart parking & environmental management. Learn how these solutions are architected using AWS services such as AWS IoT Core, AWS GreenGrass, AWS DeepLens, Amazon SageMaker and Amazon Alexa.
An overview of Artificial Intelligence and Machine Learning on AWS
Join us to gain an understanding of a spectrum of easy-to-use AWS Machine Learning services such as Amazon Recognition, Amazon Polly and Amazon Comprehend that rely on AWS pre-built Machine Learning models.
In addition, hear how Amazon SageMaker allows Machine Learning practitioners to collaborate on building models using Jupyter notebooks. Craft custom Deep Learning algorithms using popular libraries such as TensorFlow, Keras, MXNet, or work with traditional Machine Learning algorithms such as XGBoost. You will also learn how to detect anomalies using Amazon Kinesis Analytics.
Amazon SageMaker is a fully-managed platform that lets developers and data scientists build and scale machine learning solutions. First, we'll show you how SageMaker Ground Truth helps you label large training datasets. Then, using Jupyter notebooks, we'll show you how to build, train and deploy models using built-in algorithms and frameworks (TensorFlow, Apache MXNet, etc). Finally, we'll show you how to use 3rd-party models from the AWS marketplace.
Amazon SageMaker is a fully-managed platform that lets developers and data scientists build and scale machine learning solutions. First, we'll show you how SageMaker Ground Truth helps you label large training datasets. Then, using Jupyter notebooks, we'll show you how to build, train and deploy models using built-in algorithms and frameworks (TensorFlow, Apache MXNet, etc). Finally, we'll show you how to use 3rd-party models from the AWS marketplace.
AWS re:Invent is an annual global conference of the Amazon Web Services community held in Las Vegas. In 2017, we held 1000+ breakout sessions and attracted over 40,000 attendees. The event offers expanded opportunities to learn about the latest AWS releases, use cases and business benefits, not to mention diving deep into hot topics and meeting with our subject matter experts.
Missed it? Don’t worry, we are bringing AWS re:Invent to Hong Kong on Jan 18, 2018. Packed in a day, AWS re:Invent 2017 Recap Hong Kong will showcase new releases announced at re:Invent 2017 on Serverless & Container, DevOps & Mobile, Artificial Intelligence & Machine Learning and more. Local customers will also be invited to share their re:Invent experience and success stories with AWS.
Discover the latest services and features from Amazon Web Services and learn how to integrate them into your applications
Il Machine Learning può sembrare più difficile di quanto non lo sia perché il processo di sviluppo, training e deployment dei modelli in produzione è troppo complicato e lento. Amazon SageMaker è un servizio completamente gestito che consente a sviluppatori e data scientist di progettare, implementare e distribuire modelli di Machine Learning in qualsiasi scala. Amazon SageMaker offre una scelta di algoritmi di machine learning altamente performanti e framework preconfigurati come Apache MXNet, TensorFlow, PyTorch e Chainer; inoltre, è possibile utilizzare framework o algoritmi alternativi attraverso container Docker. In questa sessione approfondiremo l’utilizzo di Amazon SageMaker, anche attraverso alcuni pratici esempi.
Alexa transformed the smart home market segment and is now transforming how we interact with applications and technology at work. In this session, learn about how Alexa is an example of Conversational AI in Education.
AWS Summit Singapore 2019 | Building Business Outcomes with Machine Learning ...Amazon Web Services
Speaker: Barnam Bora, Head of AI/ML, APAC, AWS
Customer Speaker: Guangda Li, Co-founder & CTO, ViSenze
Note: This is part 2 of the deck.
WS offers different paths for building and deploying scalable ML solutions. This session provides an insight to how AWS customers are building intelligent systems powered by AI and ML. Learn how these services, in conjunction with the large number of complementary AWS technologies, provide a great platform for our customers to build their own AI and ML powered solutions and drive business value. Towards the latter part of this session, hear how customers are deploying their ML on AWS and can now leverage Marketplace to monetise their models.
Certification Study Group - NLP & Recommendation Systems on GCP Session 5gdgsurrey
This session features Raghavendra Guttur's exploration of "Atlas," a chatbot powered by Llama2-7b with MiniLM v2 enhancements for IT support. ChengCheng Tan will discuss ML pipeline automation, monitoring, optimization, and maintenance.
AWS Summit Singapore - Artificial Intelligence to Delight Your CustomersAmazon Web Services
Andrew Watts-Curnow, Senior Cloud Architect – Professional Services, APAC, AWS
Learn how advances in AI are enabling improvements in customer experience. This is a deep dive using machine learning frameworks for people who are familiar with building their own models. In this session, we will detail a facial recognition solution that can detect known customers and alert customer service staff.
Leverage the power of machine learning on windowsMia Chang
Note:
The Content was modified from the Microsoft Content team.
Deck Owner: Nitah Onsongo
Tech/Msg Review: Cesar De La Torre, Simon Tao, Clarke Rahrig
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Event: Insider Dev Tour Berlin
Event Description: Microsoft is going on a world tour with the announcements of Build 2019. The Insider Dev Tour focuses on innovations related to Microsoft 365 from a developer's perspective.
Date: June 7th, 2019
Event link: https://www.microsoft.com/de-de/techwiese/news/best-of-build-insider-dev-tour-am-7-juni-in-berlin.aspx
Linkedin: http://linkedin.com/in/mia-chang/
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.
2. Innovate in 2019
Artificially Intelligent, Constantly
Connected and Intuitive at Hyper-Scale
Olivier Klein
Head of Emerging Technologies Asia-Pacific
6. ARTIFICIAL INTELLIGENCE AND
DATA-DRIVEN DECISIONS
U R G E N T
X-Ray analysis
GAN rendered
dental implants
Blood sugar measurements
through breath
MRI scans analysis
Deep Learning
assisted ultra-sound
36. • Map villages in Africa to deliver right
amount of vaccines
• Provide first responders with information
during national disasters
• PSMA Australia - 200TB imagery - 7.6
million km2 - 20 million buildings
Cloud-based platform to derive insights and
convert unstructured satellite imagery into
meaningful insights using ML
Generates 80TB/day of imagery data
40. EA SI L Y A DD I NTEL L I GENCE TO A P P L I CA TI ONS
NO MA CHI NE L EA RNI NG SKI L L S REQUI RED
MACH INE L EARN ING F O R EV ERY DEVEL OP ER AN D DAT A SCIEN TIST
BU IL D, T RAIN AN D DEPL OY ML F AST
CHOI CE A ND FL EXI BI L I TY WI TH BROA DEST FRA MEWORK SUP P ORT
FA STEST A ND L OWEST - COST COMP UTE OP TI ONS
AI Services
ML Services
ML Frameworks
+ Infrastructure
41. AI Services
ML Services
ML Frameworks
+ Infrastructure EC2 P3
& P3dn
EC2
C5
FPGAs Greengrass
Elastic
inference
FR A ME WO R KS I NT E R FA CES I N F R A S T R U C T U R E
Inferentia
EC2
G4
42. AWS is framework agnostic
Run them fully managed Or run them yourself
44. Provision just the amount of GPU
you need for faster inference
Amazon Elastic
Inference
Add GPU acceleration to any
Amazon EC2 instance
Reduce the cost of running deep
learning inference by up to 75%
Capacity ranging from 1 TFLOPS
up to 32 TFLOPS
Supports TensorFlow, Apache MXNet,
and ONNX models
45. ML Services Amazon
SageMaker
Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment Hosting
ML Frameworks
+ Infrastructure EC2 P3
& P3dn
EC2
C5
FPGAs Greengrass
Elastic
inference
FR A ME WO R KS I NT E R FA CES I N F R A S T R U C T U R E
Inferentia
EC2
G4
AI Services
46. Collect and prepare
training data
Choose and optimize
your ML algorithm
Set up and manage
environments for
training
Train and tune model
(trial and error)
Deploy model
in production
Scale and manage the
production
environment
Amazon SageMaker
BRINGING MACHINE LEARNING TO ALL DEVELOPERS
47. Choose and optimize
your ML algorithm
Set up and manage
environments for
training
Train and tune model
(trial and error)
Deploy model
in production
Scale and manage the
production
environment
Pre-built
notebooks for
common problems
Collect and p rep are
training d ata
Amazon SageMaker
BRINGING MACHINE LEARNING TO ALL DEVELOPERS
Explore data close to where it’s stored
Reuse knowledge for common problems
48. Train and tune model
(trial and error)
Deploy model
in production
Scale and manage the
production
environment
Built-in, high
performance
algorithms
Choos e and op timize
y ou r ML algorithm
K-Means Clustering
Principal Component Analysis
Neural Topic Modelling
Factorization Machines
Linear Learner (Regression)
BlazingText
Reinforcement learning
XGBoost
Topic Modeling (LDA)
Image Classification
Seq2Seq
Linear Learner (Classification)
DeepAR Forecasting
Pre-built
notebooks for
common problems
Collect and p rep are
training d ata
Amazon SageMaker
BRINGING MACHINE LEARNING TO ALL DEVELOPERS
Train models on your data without writing algorithms
Explore or contribute to the ML Marketplace
49. Train and tune model
(trial and error)
Deploy model
in production
Scale and manage the
production
environment
Pre-built
notebooks for
common problems
Collect and p rep are
training d ata
Built-in, high
performance
algorithms
Choos e and op timize
y ou r ML algorithm
One-click
training
Set up and manage
environments
for training
Amazon SageMaker
BRINGING MACHINE LEARNING TO ALL DEVELOPERS
No more idle resources, pay only per seconds trained
50. Deploy model
in production
Scale and manage the
production
environment
Pre-built
notebooks for
common problems
Collect and p rep are
training d ata
Built-in, high
performance
algorithms
Choos e and op timize
y ou r ML algorithm
One-click
training
Set up and manage
environments
for training
Optimization
Train and tune model
(trial and error)
Amazon SageMaker
BRINGING MACHINE LEARNING TO ALL DEVELOPERS
Perform hyper parameter optimization automatically,
effectively allowing more experimentation for better results
51. Scale and manage the
production
environment
Pre-built
notebooks for
common problems
Collect and p rep are
training d ata
Built-in, high
performance
algorithms
Choos e and op timize
y ou r ML algorithm
One-click
training
Set up and manage
environments
for training
Optimization
Train and tune model
(trial and error)
One-click
deployment
Deploy model
in production
Amazon SageMaker
BRINGING MACHINE LEARNING TO ALL DEVELOPERS
Your trained model becomes another API endpoint
Integrate it within your existing apps easily
52. Pre-built
notebooks for
common problems
Collect and p rep are
training d ata
Built-in, high
performance
algorithms
Choos e and op timize
y ou r ML algorithm
One-click
training
Set up and manage
environments
for training
Optimization
Fully managed with auto -
scaling, health checks,
automatic handling of
node failures, and
security checks
S cale and manag e the
prod u ction env ironment
Train and tune model
(trial and error)
One-click
deployment
Deploy model
in production
Amazon SageMaker
BRINGING MACHINE LEARNING TO ALL DEVELOPERS
Automatic monitoring and scaling to what you need
53. R E K O G N I T I O N
I M A G E
R E K O G N I T I O N
V I D E O
T E X T R A C T
VISION
P O L L Y T R A N S C R I B E
SPEECH
T R A N S L A T E C O M P R E H E N D
LANGUAGE
L E X
CHATBOTS
F O R E C A S T
FORECASTING
P E R S O N A L I Z E
RECOMMENDATIONS
AI Services
ML Services Amazon
SageMaker
Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment Hosting
ML Frameworks
+ Infrastructure EC2 P3
& P3dn
EC2
C5
FPGAs Greengrass
Elastic
inference
FR A ME WO R KS I NT E R FA CES I N F R A S T R U C T U R E
Inferentia
EC2
G4
54. How do you teach machine learning models to
make decisions when there is no training data?
56. Learn by
interacting with
the real world
Model problem
as a simulation
environment
Trial and error
Observe results
Optimise learning
strategy to maximise
long-term reward
57. Vehicle routing
Objective Fulfill customer orders
STATE Current location, distance from homes …
ACTION Accept, pick up, and deliver order
REWARD Positive when we deliver on time
Negative when we fail to deliver on time
Applicable in many domains and industries
58. Amazon
SageMaker RL
New machine learning capabilities in
Amazon SageMaker to build, train and
deploy with reinforcement learning
Fully managed RL
algorithms
TensorFlow, MXNet,
Intel Coach, and Ray RL
2D and 3D simulation
environments via OpenGym
Simulate with Sumerian and
AWS RoboMaker
Example notebooks and
tutorials
60. Build machine learning models
in Amazon SageMaker
Train, test, and iterate on the track using
the AWS DeepRacer 3D racing simulator
OpenVino to accelerate Deep Learning
models for the underlying hardware
AWS DeepRacer
A fully autonomous 1/18th-scale race car
designed to help you learn about reinforcement
learning through autonomous driving
61. Build reinforcement learning model
DeepRacer League Races at AWS Summits
Winners of each DRL Race and top scorers
compete in Championship Cup at re:Invent 2019
Virtual tournaments through the year
AWS DeepRacer League
World’s first global autonomous racing league
62. and technology is changing the world
The world of technology is changing