This document provides an overview of Amazon Alexa and voice-first devices. It discusses how advances in AI and speech recognition are driving adoption of these devices. By 2020, it is predicted that 75% of US households will have a smart speaker and 30% of web requests will be via voice. The document then describes Amazon Alexa, the Alexa Skills Kit for developing voice skills, and how account linking using OAuth 2.0 allows skills to connect to external systems on a user's behalf.
The document discusses Alexa skills and the Alexa skills kit. It covers building skills with Node.js using the Alexa skills kit SDK and AWS Lambda. It also describes setting up an Amazon developer account and AWS account to build Alexa skills. Finally, it outlines sections for a "My Assistant" Alexa skill project, including creating basic skills, handling intents, complex conversations, database storage, state management, and account linking.
Nikko Strom presented on Amazon's Alexa technologies at the AWS Stockholm Summit on May 3, 2017. He discussed Alexa Voice Service which allows developers to integrate Alexa directly into their devices, the Alexa Skills Kit which allows developers to extend Alexa's capabilities, and Amazon's growing catalog of over 10,000 skills. He also covered the Alexa Smart Home Skill API and Amazon Polly text-to-speech service. Strom concluded by discussing Amazon's investments in deep learning for speech recognition and natural language processing through programs like the Alexa Prize and Alexa Fund.
AWS Community Day Copenhagen 19.02.2019. - Alexa skill development
Alexa is the speech and personal assistant technology that powers Amazon Echo. It can be used to listen music, check weather and traffic, answer questions, control household devices and much more. In this talk you’ll get a hands-on introduction to Amazon Alexa and its ecosystem, and you’ll learn how to build Alexa skill from scratch. You'll also get introduction to the SSML (Speech Synthesis Markup Language). Target audience for this talk are developers who would like to extend their knowledge in order to be able to develop and publish skills for Alexa.
Discussed in detail about how to design and develop custom skills (think custom apps) for Amazon Alexa Voice service.
Discusses how to design voice based experiences in detail.
The document discusses Alexa Skills Kit (ASK) and how to build skills for Alexa. It describes that ASK provides APIs, tools, documentation and code samples to build skills. Skills can be used to order food, get transportation, control smart devices, check accounts and more. There are three main types of skills: custom skills, smart home skills, and flash briefing skills. Custom skills have a customizable interaction model while smart home skills control devices and flash briefing skills add content to flash briefings. The document provides examples of how skills work and guides users through setting up and testing their own skills.
Alexa-An intelligent voice-controlled personal assistant by AMAZONAnusha Deva
A presentation about Alexa which is an intelligent voice enable personal assistant by AMAZON.further it tells about amazon skill set and companion app.Also shows the general architecture of Alexa when used with AMAZON ECHO.The ppt also gives a sample algorithm and ecosystem to make the understanding of the topic better.
This document discusses best practices for AWS Identity and Access Management (IAM). It defines IAM as a service that helps securely control access to AWS resources. The main IAM components are users, groups, roles, and policies. It provides several rules for security best practices, including: never using the root account for daily tasks; locking away root access keys; granting least privileges; using roles to delegate permissions; using roles for EC2 applications; rotating credentials regularly; and monitoring account activity.
Virtual assistant with Amazon Alexa Virtual Assistant. Amazon Alexa is a virtual assistant developed by Amazon, first used in the Amazon Echo and the Amazon Echo Dot smart speakers developed by Amazon Lab126.
The document discusses Alexa skills and the Alexa skills kit. It covers building skills with Node.js using the Alexa skills kit SDK and AWS Lambda. It also describes setting up an Amazon developer account and AWS account to build Alexa skills. Finally, it outlines sections for a "My Assistant" Alexa skill project, including creating basic skills, handling intents, complex conversations, database storage, state management, and account linking.
Nikko Strom presented on Amazon's Alexa technologies at the AWS Stockholm Summit on May 3, 2017. He discussed Alexa Voice Service which allows developers to integrate Alexa directly into their devices, the Alexa Skills Kit which allows developers to extend Alexa's capabilities, and Amazon's growing catalog of over 10,000 skills. He also covered the Alexa Smart Home Skill API and Amazon Polly text-to-speech service. Strom concluded by discussing Amazon's investments in deep learning for speech recognition and natural language processing through programs like the Alexa Prize and Alexa Fund.
AWS Community Day Copenhagen 19.02.2019. - Alexa skill development
Alexa is the speech and personal assistant technology that powers Amazon Echo. It can be used to listen music, check weather and traffic, answer questions, control household devices and much more. In this talk you’ll get a hands-on introduction to Amazon Alexa and its ecosystem, and you’ll learn how to build Alexa skill from scratch. You'll also get introduction to the SSML (Speech Synthesis Markup Language). Target audience for this talk are developers who would like to extend their knowledge in order to be able to develop and publish skills for Alexa.
Discussed in detail about how to design and develop custom skills (think custom apps) for Amazon Alexa Voice service.
Discusses how to design voice based experiences in detail.
The document discusses Alexa Skills Kit (ASK) and how to build skills for Alexa. It describes that ASK provides APIs, tools, documentation and code samples to build skills. Skills can be used to order food, get transportation, control smart devices, check accounts and more. There are three main types of skills: custom skills, smart home skills, and flash briefing skills. Custom skills have a customizable interaction model while smart home skills control devices and flash briefing skills add content to flash briefings. The document provides examples of how skills work and guides users through setting up and testing their own skills.
Alexa-An intelligent voice-controlled personal assistant by AMAZONAnusha Deva
A presentation about Alexa which is an intelligent voice enable personal assistant by AMAZON.further it tells about amazon skill set and companion app.Also shows the general architecture of Alexa when used with AMAZON ECHO.The ppt also gives a sample algorithm and ecosystem to make the understanding of the topic better.
This document discusses best practices for AWS Identity and Access Management (IAM). It defines IAM as a service that helps securely control access to AWS resources. The main IAM components are users, groups, roles, and policies. It provides several rules for security best practices, including: never using the root account for daily tasks; locking away root access keys; granting least privileges; using roles to delegate permissions; using roles for EC2 applications; rotating credentials regularly; and monitoring account activity.
Virtual assistant with Amazon Alexa Virtual Assistant. Amazon Alexa is a virtual assistant developed by Amazon, first used in the Amazon Echo and the Amazon Echo Dot smart speakers developed by Amazon Lab126.
What i-wish-i-knew-about-aws-certificationAndrew Brown
This document provides an overview of considerations for obtaining AWS certifications. It outlines certification levels including foundational, associate, professional, and specialty certifications. It discusses how certifications can help with employment and roles like cloud engineer, cloud security engineer, and DevOps engineer. It provides recommendations on study resources like courses, practice exams, hands-on labs, and AWS documentation. It emphasizes the importance of practical experience and not just focusing on exams. The overall message is that certifications validate cloud knowledge but soft skills and real-world experience are also needed for cloud roles.
Adapting the capacity of your compute infrastructure to the demands of your applications is the domain of Auto Scaling. Adding and removing Amazon EC2 instances is only part of the story, though – there is more to it than first meets the eye. This session introduces the basics of how to use Auto Scaling before moving on to more advanced topics such as mixing Spot and On-Demand instances to optimize cost or strategies for blue/green deployments. If you have used Auto Scaling before, you can learn about useful new features like lifecycle hooks and step scaling policies that make Auto Scaling even more widely applicable.
Amazon Alexa is an intelligent personal assistant created by Amazon that is capable of voice interaction, music playback, providing real-time information, and controlling smart home devices. It is most popularly used through Amazon Echo and Echo Dot smart speaker devices that are voice controlled using Alexa.
Alexa, the voice service that powers Amazon Echo and Amazon Fire TV, provides a set of built-in abilities, or skills, that enable customers to interact with devices in a more intuitive way using voice. Application developers are also able to create custom applications and skills that can be published in the Alexa App Store for consumers to use. Some examples of these today include Uber, Spotify and Domino’s Pizza.This session will advise on why voice is a relevant additional user engagement model for businesses, what a good VUI (Voice User Interface) sounds like, and also demonstrate how simple it is to build custom Alexa applications by utilising the hosted Alexa Voice service and the AWS cloud.
This session introduces the concepts of AWS Identity and Access Management (IAM) and walks through the tools and strategies you can use to control access to your AWS environment. We describe IAM users, groups, and roles and how to use them. We demonstrate how to create IAM users and roles, and grant them various types of permissions to access AWS APIs and resources.
This document discusses test automation, including what it means, when it should be used, best practices, and examples of automation tools. Test automation involves writing software to reproduce the steps of a manual test process. It is useful for speeding up testing, improving coverage, and ensuring consistency. Tests that are repeated or will be run frequently are good candidates for automation. Common automation tools include NUnit, JUnit, Sahi, QTP, JMeter and Load Runner. Best practices include choosing the right tool, only automating repeated tests, identifying automatable cases, and using a data-driven approach.
This document discusses AWS Auto Scaling, which automatically launches and terminates EC2 instances based on demand. It describes the key components of Auto Scaling including launch configurations, Auto Scaling groups, scaling policies, and CloudWatch alarms. It provides step-by-step instructions for setting up a simple Auto Scaling group to support a web application, including creating an AMI, load balancer, launch configuration, Auto Scaling group, scaling policies, and CloudWatch alarms to dynamically scale the number of EC2 instances.
This document provides an overview and agenda for a presentation on automation testing using IBM Rational Functional Tester. It discusses what automation testing is, why it is useful, and when it should be implemented. It also addresses common myths about automation testing and provides tips for successful automation. Finally, it covers features of IBM Rational Functional Tester, including how to set up a test environment and record scripts to automate testing.
This dataset consists of a nearly 3000 Amazon customer reviews (input text), and 5 variables which are star ratings, date of review, variant, verified reviews and feedback of various Amazon Alexa products like Alexa Echo, Echo dots, Alexa Firesticks etc.
AWS Interview Questions Part - 1 | AWS Interview Questions And Answers Part -...Simplilearn
This presentation about "AWS interview questions" will take you through some of the most popular questions that you face in an AWS interview. Cloud computing is quickly becoming the norm among enterprises that want more flexibility, greater efficiencies, lower costs, and improved disaster recovery. AWS is by far the dominant provider, with 40% of the market share and $14 billion in revenue projected for 2017. That’s not only good news for Amazon’s bottom line. It’s also good news for yours if you’re moving into the field as an AWS Solution Architect Associate. If that’s the career move you’re making, and you’re preparing for an AWS Solution Architect job interview, then this is a video for you. Here are some of the most common AWS interview questions and answers that can help you while you prepare for Amazon web services related roles in the industry. Learn and get a deeper understanding of these questions to set you apart from the crowd in this booming cloud industry.
This AWS certification training is designed to help you gain in-depth understanding of Amazon Web Services (AWS) architectural principles and services. You will learn how cloud computing is redefining the rules of IT architecture and how to design, plan, and scale AWS Cloud implementations with best practices recommended by Amazon. The AWS Cloud platform powers hundreds of thousands of businesses in 190 countries, and AWS certified solution architects take home about $126,000 per year.
This AWS certification course will help you learn the key concepts, latest trends, and best practices for working with the AWS architecture – and become industry-ready aws certified solutions architect to help you qualify for a position as a high-quality AWS professional.
The course begins with an overview of the AWS platform before diving into its individual elements: IAM, VPC, EC2, EBS, ELB, CDN, S3, EIP, KMS, Route 53, RDS, Glacier, Snowball, Cloudfront, Dynamo DB, Redshift, Auto Scaling, Cloudwatch, Elastic Cache, CloudTrail, and Security. Those who complete the course will be able to:
1. Formulate solution plans and provide guidance on AWS architectural best practices
2. Design and deploy scalable, highly available, and fault tolerant systems on AWS
3. Identify the lift and shift of an existing on-premises application to AWS
4. Decipher the ingress and egress of data to and from AWS
5. Select the appropriate AWS service based on data, compute, database, or security requirements
6. Estimate AWS costs and identify cost control mechanisms
This AWS course is recommended for for professionals who want to pursue a career in Cloud computing or develop Cloud applications with AWS. You’ll become an asset to any organization, helping leverage best practices around advanced cloud based solutions and migrate existing workloads to the cloud.
Learn more at https://www.simplilearn.com/cloud-computing/aws-solution-architect-associate-training
This AWS Tutorial ( Amazon AWS Blog Series: https://goo.gl/qQwZLz ) will give you an introduction to AWS and its domains. This AWS tutorial is ideal for those who want to become AWS Certified Solutions Architect.
Below are the topics covered in this tutorial:
1. What is Cloud?
2. What is AWS?
3. Different Domains in AWS
4. AWS Pricing
5. Migrate Your Application to AWS Infrastructure
6. Use case
#awstraining #cloudcomputing #awstutorial
Auto scaling using Amazon Web Services ( AWS )Harish Ganesan
In this article i would like to share some of the insights on AWS Auto Scaling in following perspectives:
• Need for Auto Scaling
• How AWS Auto scaling can help to handle the various load volatility scenarios
• How to configure an Auto scaling policy in AWS
• Things to remember before Scaling out and down
• Understand the intricacies while integrating Auto scaling with other Amazon Web Services
• Risks involved in AWS Auto scaling
This document introduces Amazon CloudFront, a content delivery network (CDN) that provides fast, secure, and cost-effective global delivery of content. Some key features of CloudFront include its full-featured caching network with a global infrastructure tuned for optimal performance, high security, robust analytics, and self-service capabilities. CloudFront can deliver content for various market segments like media/entertainment, gaming, eCommerce, and software downloads. It aims to provide high performance, reach a wide global audience, and ensure financial feasibility for scalable content delivery.
This document provides an overview of architecting applications for the AWS cloud. It discusses key AWS cloud computing attributes like scalability, on-demand provisioning, and efficiency of experts. It also outlines best practices like designing for failure, loose coupling, dynamism, and security. Specific AWS services are mapped to common application needs like compute, storage, content delivery, databases, and more. Overall the document aims to educate readers on how to leverage AWS architectural principles and services.
AWS Lambda is a serverless compute platform that allows users to upload code and create functions that can be triggered by events from other AWS services like S3, DynamoDB, SNS, and Kinesis. Lambda handles provisioning and managing servers so users do not have to worry about infrastructure management. It provides a pay-per-use model where users are charged only for the compute time used to process events. The presentation provided examples of using Lambda for image thumbnailing from S3 uploads, sending notifications from DynamoDB updates, and processing streaming data from Kinesis.
Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale. It allows developers to manage multiple versions and stages of APIs, monitor access by third party developers, and handle traffic spikes without operational burden. API Gateway supports features like throttling, authorization, caching of responses, and SDK generation to make APIs easy to consume.
Deep Dive on Amazon S3 Security and Management (E2471STG303-R1) - AWS re:Inve...Amazon Web Services
In this session, learn best practices for data security in Amazon S3. We discuss the fundamentals of Amazon S3 security architecture and dive deep into the latest enhancements in usability and functionality. We investigate options for encryption, access control, security monitoring, auditing, and remediation.
Brief research on Amazon S3 for my company.
Feel free to comment/feedback. Thanks!
Connect with me on LinkedIn : sg.linkedin.com/in/yulunteo/
Seems like there are still plenty of people viewing this presentation after so long.
Maybe i should consider doing a update for Cloudfront/Glacier as well..
AWS provides a comprehensive set of global cloud computing services including compute, storage, databases, analytics, networking, mobile, developer tools, management tools, IoT, security and enterprise applications. Some key services highlighted include EC2 for virtual servers, S3 for object storage, RDS for managed relational databases, DynamoDB for NoSQL database services, EBS for block storage volumes, VPC for virtual networking, IAM for access management, CloudFront for content delivery and Route 53 for DNS services. AWS operates across multiple geographic regions and availability zones for reliability and high availability.
An Overview of AI at AWS - Amazon Lex, Amazon Polly, Amazon Rekognition - Dev...Amazon Web Services
This document provides an overview of artificial intelligence services available on Amazon Web Services, including Amazon Lex, Amazon Polly, Amazon Rekognition, Apache MXNet, and AWS Deep Learning AMIs. It discusses the capabilities and use cases of each service, such as natural language processing with Amazon Lex, text-to-speech with Amazon Polly, and computer vision with Amazon Rekognition. The document also covers deep learning frameworks like Apache MXNet and resources for running deep learning workloads on AWS.
Overview of Artificial Intelligence at AWS - DevDay Los Angeles 2017Amazon Web Services
The document provides an overview of artificial intelligence services available on Amazon Web Services (AWS), including Amazon Lex, Amazon Polly, Amazon Rekognition, and Apache MXNet. It discusses the capabilities and use cases of each service, such as converting text to speech (Amazon Polly), computer vision capabilities like object detection (Amazon Rekognition), and building conversational chatbots (Amazon Lex). It also covers deep learning frameworks like Apache MXNet and resources for developing AI solutions on AWS.
What i-wish-i-knew-about-aws-certificationAndrew Brown
This document provides an overview of considerations for obtaining AWS certifications. It outlines certification levels including foundational, associate, professional, and specialty certifications. It discusses how certifications can help with employment and roles like cloud engineer, cloud security engineer, and DevOps engineer. It provides recommendations on study resources like courses, practice exams, hands-on labs, and AWS documentation. It emphasizes the importance of practical experience and not just focusing on exams. The overall message is that certifications validate cloud knowledge but soft skills and real-world experience are also needed for cloud roles.
Adapting the capacity of your compute infrastructure to the demands of your applications is the domain of Auto Scaling. Adding and removing Amazon EC2 instances is only part of the story, though – there is more to it than first meets the eye. This session introduces the basics of how to use Auto Scaling before moving on to more advanced topics such as mixing Spot and On-Demand instances to optimize cost or strategies for blue/green deployments. If you have used Auto Scaling before, you can learn about useful new features like lifecycle hooks and step scaling policies that make Auto Scaling even more widely applicable.
Amazon Alexa is an intelligent personal assistant created by Amazon that is capable of voice interaction, music playback, providing real-time information, and controlling smart home devices. It is most popularly used through Amazon Echo and Echo Dot smart speaker devices that are voice controlled using Alexa.
Alexa, the voice service that powers Amazon Echo and Amazon Fire TV, provides a set of built-in abilities, or skills, that enable customers to interact with devices in a more intuitive way using voice. Application developers are also able to create custom applications and skills that can be published in the Alexa App Store for consumers to use. Some examples of these today include Uber, Spotify and Domino’s Pizza.This session will advise on why voice is a relevant additional user engagement model for businesses, what a good VUI (Voice User Interface) sounds like, and also demonstrate how simple it is to build custom Alexa applications by utilising the hosted Alexa Voice service and the AWS cloud.
This session introduces the concepts of AWS Identity and Access Management (IAM) and walks through the tools and strategies you can use to control access to your AWS environment. We describe IAM users, groups, and roles and how to use them. We demonstrate how to create IAM users and roles, and grant them various types of permissions to access AWS APIs and resources.
This document discusses test automation, including what it means, when it should be used, best practices, and examples of automation tools. Test automation involves writing software to reproduce the steps of a manual test process. It is useful for speeding up testing, improving coverage, and ensuring consistency. Tests that are repeated or will be run frequently are good candidates for automation. Common automation tools include NUnit, JUnit, Sahi, QTP, JMeter and Load Runner. Best practices include choosing the right tool, only automating repeated tests, identifying automatable cases, and using a data-driven approach.
This document discusses AWS Auto Scaling, which automatically launches and terminates EC2 instances based on demand. It describes the key components of Auto Scaling including launch configurations, Auto Scaling groups, scaling policies, and CloudWatch alarms. It provides step-by-step instructions for setting up a simple Auto Scaling group to support a web application, including creating an AMI, load balancer, launch configuration, Auto Scaling group, scaling policies, and CloudWatch alarms to dynamically scale the number of EC2 instances.
This document provides an overview and agenda for a presentation on automation testing using IBM Rational Functional Tester. It discusses what automation testing is, why it is useful, and when it should be implemented. It also addresses common myths about automation testing and provides tips for successful automation. Finally, it covers features of IBM Rational Functional Tester, including how to set up a test environment and record scripts to automate testing.
This dataset consists of a nearly 3000 Amazon customer reviews (input text), and 5 variables which are star ratings, date of review, variant, verified reviews and feedback of various Amazon Alexa products like Alexa Echo, Echo dots, Alexa Firesticks etc.
AWS Interview Questions Part - 1 | AWS Interview Questions And Answers Part -...Simplilearn
This presentation about "AWS interview questions" will take you through some of the most popular questions that you face in an AWS interview. Cloud computing is quickly becoming the norm among enterprises that want more flexibility, greater efficiencies, lower costs, and improved disaster recovery. AWS is by far the dominant provider, with 40% of the market share and $14 billion in revenue projected for 2017. That’s not only good news for Amazon’s bottom line. It’s also good news for yours if you’re moving into the field as an AWS Solution Architect Associate. If that’s the career move you’re making, and you’re preparing for an AWS Solution Architect job interview, then this is a video for you. Here are some of the most common AWS interview questions and answers that can help you while you prepare for Amazon web services related roles in the industry. Learn and get a deeper understanding of these questions to set you apart from the crowd in this booming cloud industry.
This AWS certification training is designed to help you gain in-depth understanding of Amazon Web Services (AWS) architectural principles and services. You will learn how cloud computing is redefining the rules of IT architecture and how to design, plan, and scale AWS Cloud implementations with best practices recommended by Amazon. The AWS Cloud platform powers hundreds of thousands of businesses in 190 countries, and AWS certified solution architects take home about $126,000 per year.
This AWS certification course will help you learn the key concepts, latest trends, and best practices for working with the AWS architecture – and become industry-ready aws certified solutions architect to help you qualify for a position as a high-quality AWS professional.
The course begins with an overview of the AWS platform before diving into its individual elements: IAM, VPC, EC2, EBS, ELB, CDN, S3, EIP, KMS, Route 53, RDS, Glacier, Snowball, Cloudfront, Dynamo DB, Redshift, Auto Scaling, Cloudwatch, Elastic Cache, CloudTrail, and Security. Those who complete the course will be able to:
1. Formulate solution plans and provide guidance on AWS architectural best practices
2. Design and deploy scalable, highly available, and fault tolerant systems on AWS
3. Identify the lift and shift of an existing on-premises application to AWS
4. Decipher the ingress and egress of data to and from AWS
5. Select the appropriate AWS service based on data, compute, database, or security requirements
6. Estimate AWS costs and identify cost control mechanisms
This AWS course is recommended for for professionals who want to pursue a career in Cloud computing or develop Cloud applications with AWS. You’ll become an asset to any organization, helping leverage best practices around advanced cloud based solutions and migrate existing workloads to the cloud.
Learn more at https://www.simplilearn.com/cloud-computing/aws-solution-architect-associate-training
This AWS Tutorial ( Amazon AWS Blog Series: https://goo.gl/qQwZLz ) will give you an introduction to AWS and its domains. This AWS tutorial is ideal for those who want to become AWS Certified Solutions Architect.
Below are the topics covered in this tutorial:
1. What is Cloud?
2. What is AWS?
3. Different Domains in AWS
4. AWS Pricing
5. Migrate Your Application to AWS Infrastructure
6. Use case
#awstraining #cloudcomputing #awstutorial
Auto scaling using Amazon Web Services ( AWS )Harish Ganesan
In this article i would like to share some of the insights on AWS Auto Scaling in following perspectives:
• Need for Auto Scaling
• How AWS Auto scaling can help to handle the various load volatility scenarios
• How to configure an Auto scaling policy in AWS
• Things to remember before Scaling out and down
• Understand the intricacies while integrating Auto scaling with other Amazon Web Services
• Risks involved in AWS Auto scaling
This document introduces Amazon CloudFront, a content delivery network (CDN) that provides fast, secure, and cost-effective global delivery of content. Some key features of CloudFront include its full-featured caching network with a global infrastructure tuned for optimal performance, high security, robust analytics, and self-service capabilities. CloudFront can deliver content for various market segments like media/entertainment, gaming, eCommerce, and software downloads. It aims to provide high performance, reach a wide global audience, and ensure financial feasibility for scalable content delivery.
This document provides an overview of architecting applications for the AWS cloud. It discusses key AWS cloud computing attributes like scalability, on-demand provisioning, and efficiency of experts. It also outlines best practices like designing for failure, loose coupling, dynamism, and security. Specific AWS services are mapped to common application needs like compute, storage, content delivery, databases, and more. Overall the document aims to educate readers on how to leverage AWS architectural principles and services.
AWS Lambda is a serverless compute platform that allows users to upload code and create functions that can be triggered by events from other AWS services like S3, DynamoDB, SNS, and Kinesis. Lambda handles provisioning and managing servers so users do not have to worry about infrastructure management. It provides a pay-per-use model where users are charged only for the compute time used to process events. The presentation provided examples of using Lambda for image thumbnailing from S3 uploads, sending notifications from DynamoDB updates, and processing streaming data from Kinesis.
Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale. It allows developers to manage multiple versions and stages of APIs, monitor access by third party developers, and handle traffic spikes without operational burden. API Gateway supports features like throttling, authorization, caching of responses, and SDK generation to make APIs easy to consume.
Deep Dive on Amazon S3 Security and Management (E2471STG303-R1) - AWS re:Inve...Amazon Web Services
In this session, learn best practices for data security in Amazon S3. We discuss the fundamentals of Amazon S3 security architecture and dive deep into the latest enhancements in usability and functionality. We investigate options for encryption, access control, security monitoring, auditing, and remediation.
Brief research on Amazon S3 for my company.
Feel free to comment/feedback. Thanks!
Connect with me on LinkedIn : sg.linkedin.com/in/yulunteo/
Seems like there are still plenty of people viewing this presentation after so long.
Maybe i should consider doing a update for Cloudfront/Glacier as well..
AWS provides a comprehensive set of global cloud computing services including compute, storage, databases, analytics, networking, mobile, developer tools, management tools, IoT, security and enterprise applications. Some key services highlighted include EC2 for virtual servers, S3 for object storage, RDS for managed relational databases, DynamoDB for NoSQL database services, EBS for block storage volumes, VPC for virtual networking, IAM for access management, CloudFront for content delivery and Route 53 for DNS services. AWS operates across multiple geographic regions and availability zones for reliability and high availability.
An Overview of AI at AWS - Amazon Lex, Amazon Polly, Amazon Rekognition - Dev...Amazon Web Services
This document provides an overview of artificial intelligence services available on Amazon Web Services, including Amazon Lex, Amazon Polly, Amazon Rekognition, Apache MXNet, and AWS Deep Learning AMIs. It discusses the capabilities and use cases of each service, such as natural language processing with Amazon Lex, text-to-speech with Amazon Polly, and computer vision with Amazon Rekognition. The document also covers deep learning frameworks like Apache MXNet and resources for running deep learning workloads on AWS.
Overview of Artificial Intelligence at AWS - DevDay Los Angeles 2017Amazon Web Services
The document provides an overview of artificial intelligence services available on Amazon Web Services (AWS), including Amazon Lex, Amazon Polly, Amazon Rekognition, and Apache MXNet. It discusses the capabilities and use cases of each service, such as converting text to speech (Amazon Polly), computer vision capabilities like object detection (Amazon Rekognition), and building conversational chatbots (Amazon Lex). It also covers deep learning frameworks like Apache MXNet and resources for developing AI solutions on AWS.
Raleigh DevDay 2017: Distributed Deep Learning on AWS with Apache MXNetAmazon Web Services
This document provides an overview of artificial intelligence capabilities on AWS, including text-to-speech with Amazon Polly, computer vision with Amazon Rekognition, deep learning with Apache MXNet, and conversational interfaces with Amazon Lex. It discusses common use cases for each service and highlights their key features such as life-like speech synthesis, facial analysis and comparison, scalable deep learning, and building chatbots and voice interfaces.
Artificial Intelligence (AI) services on the AWS cloud bring deep learning (DL) technologies like natural language understanding (NLU), automatic speech recognition (ASR), image recognition and computer vision (CV), text-to-speech (TTS), and machine learning (ML) within reach of every developer. In this session, you will be introduced to several new AI services: Amazon Lex, to build sophisticated text and voice chatbots; Amazon Rekognition, for deep learning-based image recognition; and Amazon Polly, for turning text into lifelike speech. The opportunities to apply one or more of these DL services are nearly boundless and this session will provide a number of examples and use cases to help you get started.
Integrate drupal 8 with alexa - RakshithRakshith Tb
1) The document discusses how to integrate Drupal 8 websites with Amazon Alexa so that users can interact with websites using voice commands to Alexa.
2) The prerequisites for integration are having an internet accessible Drupal site with a valid SSL certificate and an Amazon developer account.
3) The steps to integrate involve installing an Alexa module for Drupal using Composer, enabling the module, filling in credentials, and creating a custom module to handle Alexa responses.
John Chang from Amazon Web Services presented information on Amazon Lex, a new conversational interface service. Lex allows developers to build conversational bots through the use of natural language understanding and text-to-speech. It integrates with other AWS services and can be deployed to chat platforms. Lex offers scalable and cost-effective conversational capabilities for applications, powered by the same deep learning technologies as Alexa.
An Overview of AI at AWS: Amazon Lex, Amazon Polly, Amazon Rekognition, Apach...Amazon Web Services
by Keith Steward, Solutions Architect, AWS
AI services on the AWS cloud bring deep learning technologies like natural language understanding, automatic speech recognition, computer vision, text-to-speech, and machine learning within reach of every developer. For more in-depth deep learning applications, the Deep Learning AMIs let you create managed, auto-scaling clusters of GPUs for large scale training, or run inference on trained models with compute-optimized or general-purpose CPU instances. Whether you’re just getting started with AI or you’re a deep learning expert, this session will provide a meaningful overview of how to improve scale and efficiency with the AWS Cloud. Level 200
Building voice enabled Apps with Alexa voice service and Amazon Lex. Amazon Web Services
Have you heard about Alexa? Chances are that you have.
But Amazon Echo which powers Alexa is not yet available in India.
How can I now introduce voice enabled applications to my customers?
Well, there are two ways. Use the Alexa voice service. Use the Alexa Voice Service (AVS) to add intelligent voice control to any connected product that has a microphone and speaker.
Or you could use Lex and Polly for building conversational interfaces into any application using voice and text. Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions.
This track will guide you to create real life applications using Lex to create a new
Speaker:
Shailesh Albuquerque
Manager-Solutions Archtecture, Amazon India
Announcing Amazon Lex - January 2017 AWS Online Tech TalksAmazon Web Services
Amazon Lex is a service for building conversational interfaces into any application using voice and text. Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions.
Learning Objectives:
• Learn about the capabilities and features of Amazon Lex
• Learn about the benefits of Amazon Lex
• Learn about the different use cases
• Learn how to get started using Amazon Lex
Alexapi on Amazon Ecosystem for Home Assistant Environment and IFTTT RecipesIRJET Journal
This document discusses the development of a customized speech-driven artificial intelligence assistant called AlexaPi using the Amazon Alexa platform. AlexaPi is built on a Raspberry Pi and uses Amazon's Alexa Skills Kit and AWS Lambda to create skills. It can monitor and control smart home devices using the Home Assistant platform and trigger IFTTT recipes. The paper demonstrates how to create skills for AlexaPi to glow LEDs using intents and control smart devices by voice through Amazon's cloud services.
The document provides an overview of artificial intelligence capabilities on AWS, including text-to-speech with Amazon Polly, computer vision with Amazon Rekognition, and conversational interactions with Amazon Lex. It describes several deep learning frameworks and services that can be used to build AI solutions, such as Apache MXNet and Amazon's AI offerings.
The document discusses Hackster Live, a series of community organized hardware and IoT meetups and workshops. It provides an agenda for a Hackster DFW meetup, which will include introductions, discussions about Hackster.io and challenges, pitching projects, demonstrations, and workshops. The meetup hopes to help local hardware makers connect and collaborate. The document also covers using the Amazon Echo and Alexa voice service to create voice-controlled skills and devices.
AWS re:Invent 2016: NEW LAUNCH! Introducing Amazon Lex (MAC304)Amazon Web Services
Amazon Lex is a service for building conversational interfaces into any applications using voice and text. With Lex, the same deep learning engine that powers Amazon Alexa is now available to any developer, enabling you to build sophisticated, natural language chatbots into your new and existing applications. Amazon Lex provides the deep functionality and flexibility of natural language understanding (NLU) and automatic speech recognition (ASR) to allow you to build highly engaging user experiences with lifelike, conversational interactions. In this introductory session, find out how Lex provides deep functionality and flexibility to empower you to define entirely new categories of products that are made possible through conversational interfaces.
IRJET- Automation using Alexa and Raspberry PiIRJET Journal
This document describes a system for automating devices using Alexa voice commands and a Raspberry Pi. The system connects sensors and actuators to a Raspberry Pi which is integrated with Amazon Alexa Voice Services. Voice commands are sent to AWS Lambda for processing and to control devices by triggering outputs on the Raspberry Pi. The system was created to reduce manual control of automation and make the process more intuitive with voice commands.
Serverless Generative AI on AWS, AWS User Groups of FloridaCloudHesive
This document provides an overview of a presentation on serverless generative AI. The presentation will discuss the architecture, applications, and potential business impact of serverless generative AI. It will also explore how this technology can broaden perspectives and spark new ideas for both experienced AWS users and those just starting with cloud computing. The presentation format will include questions throughout and a dedicated Q&A period at the end.
Randall Hunt introduced Amazon Lex, a new service for building conversational interfaces using voice and text. Amazon Lex provides features like text and speech language understanding powered by the same technology as Alexa, deployment to chat services like Facebook Messenger, and integration with other AWS services. It is designed to make building conversational interfaces more efficient for developers. Amazon Lex aims to help developers build powerful applications like informational, application, and enterprise productivity bots as well as bots for internet of things devices.
Building a Better .NET Bot with AWS Services - WIN205 - re:Invent 2017Amazon Web Services
With the recent introduction of AWS Tools for Visual Studio Team Services, .NET developers have more ways than ever to easily use AWS services for their .NET applications. In this workshop, we run through building a .NET chatbot as we take advantage of AWS Lambda and Amazon Lex. The best part? You can build and deploy the chatbot directly to AWS without ever leaving Visual Studio.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
2. - Why are Voice first devices getting close to mainstream?
- Why concentrating on Amazon Alexa for now?
- What is Amazon Alexa?
- Alexa Skills Development Overview – Interaction Model
- Account Linking Overview
- OAuth2.0 and OpenID Connect
Agenda
3. Why?
- Advances in AI, speech recognition and natural language processing.
- Plunging cost of processing and data storage.
What’s next?
- In 2017, will be 24.5 million devices shipped, leading to 33 million voice-first devices in circulation.
- Edison research predict 75% US households will have smart speakers [Amazon Echo, etc.] by end 2020.
- Gartner predicts 30% of web information requests by 2020 will be via audio-centric technologies.
- BMW announced Alexa will be integrated into BMWs starting in mid-2018.
“Whoever wins voice will be the dominant tech company
of the next decade, like Google was for the web
and Intel was for the computing age.”
– Adam Cheynor (Inventor of Siri and founder of Viv –
Voice startup bought by Samsung)
Why are Voice first devices getting close to mainstream?
4. Why Amazon Alexa?
"Amazon’s Echo speaker will have 70.6% of users in
2017, with Google Home at 23.8% of the market”
Forbes, May 2017
5. What is Conversational UI?
A conversational user interface is a touchpoint that enables us to use language to interact. It’s a
text message, it’s an airline sending you your boarding pass on Facebook Messenger and
switching you to window seat. It’s asking Alexa what the weather is going to be for weekend?
What is a Voice first device?
A voice-first device is an always-on, intelligent piece of hardware
where the primary interface is voice, both input and output –
Amazon Echo, Amazon Dot or Google Home.
What is Amazon Alexa?
Alexa is an intelligent personal assistant (Software) developed by
Amazon, made popular by Amazon Echo & Amazon Echo Dot
(Hardware).
What is Amazon Alexa?
7. Echo Dot - is a hands-free, voice-controlled device that uses the same far-field voice
recognition as Amazon Echo. Dot has a small built-in speaker
Alexa – provides a set of built-in capabilities, referred to as skills, that enable customers to interact with
devices in a more intuitive way using voice.
Alexa Skills Kit (ASK) – lets you add new Skills. It is a collection of self-service APIs, tools, documentation
and code samples that make it fast and easy for you to add skills to Alexa. All of the code runs in the
cloud — nothing is installed on any user device. There are 2 main types of skills – Custom Skills and Smart
Home Skills.
Custom Skills - can handle just about any type of request. You define the requests the skill can handle
(intents) and the words your customers say to invoke those requests (utterances) => Interaction Model.
Alexa Skills - Basics
10. When creating a custom skill, you create the following:
- A set of intents that represent actions that users can do with your skill. Represent the core functionality
of your skill.
- A set of sample utterances that specify the words and phrases users can say to invoke intents. You map
these utterances to your intents and this mapping forms the interaction model.
- An invocation name that identifies the skill.
- A Service or end point that accepts these intents as structured requests and act on them.
Skill Interface
16. - Account linking is needed when the skill needs to connect with a system that requires authentication.
How Account Linking Works:
To connect an Alexa user with an account in your system, you need to provide an OAuth access
token that uniquely identifies the user within your system.
Alexa service stores this token and includes it in requests sent to your skill’s service. Your skill can
then use the token to authenticate with your system on behalf of the user.
- Using account linking in the Alexa Skills Kit requires use of the OAuth 2.0 Authorization Framework.
- Two OAuth authorization grant types are supported (4 OAuth Authorization grant types in total):
- 1. Authorization code grant (More secure but more complex)
- 2. Implicit grant
Linking Alexa user with user in your system – Account Linking
17. - OAuth 2 is an authorization framework that enables applications to obtain limited access to user
accounts on an HTTP service, such as Facebook or GitHub.
- OAuth Access Token represents user's authorization to perform a certain action which is done by the
application. It is used for accessing endpoints over HTTP carried in the Authorization header
- OpenID Connect is a simple identity layer built on top of the OAuth 2.0 protocol.
- OpenID Connect is recommendation if you are building a web application that is hosted on a server and
accessed via a browser.
The OAuth 2.0 Authorization Framework: https://tools.ietf.org/html/rfc6749
OpenID Connect Core: http://openid.net/specs/openid-connect-core-1_0.html
OAuth2 Authorization and OpenID Connect
> Amazon released Echo 36 months ago
> Google home
Apple Siri (Much to be done)
Microsoft Cortana
> Soon to be released Microsoft Invoke and Apple HomePod
> Amazon released Echo 36 months ago
> Google home
Apple Siri (Much to be done)
Microsoft Cortana
> Soon to be released Microsoft Invoke and Apple HomePod
Next slides will go into more depth on interaction model
Basics of the Alexa State Machine
Tell => terminates the session with the response (Straight Forward Request Response)
Ask => Send a response but ask more questions (Keep Session Open)
The Response Object
This object returns four methods: tell, tellWithCard, ask, and askWithCard.
The Tell Methods
tell(speechOutput)
tellWithCard(speechOutput, cardTitle, cardContent)
We have two methods here which will respond to the user and end the session. First is tell, which accepts a string that Alexa will speak to the user, and tellWithCard, which accepts a string that Alexa speaks to the user, a string that serves as the card title, and a string that serves as the body of the card. The card is displayed within the Amazon Echo app.
The Ask Methods
ask(speechOutput, repromptSpeech)
askWithCard(speechOutput, repromptSpeech, cardTitle, cardContent)
These methods are just like the tell methods, except for two key differences. First, the session is kept open, waiting for a further response from the user. Second, the second argument is a string that Alexa will speak to the user if they haven’t responded to specify what they want.
Intent – determine what function within the handler will be executed.
Amazon have predefined Intents
Amazon ASK CLI for deployments rather than manually configuring in developer.amazon.com GUI.
The Response Object
This object returns four methods: tell, tellWithCard, ask, and askWithCard.
The Tell Methods
tell(speechOutput)
tellWithCard(speechOutput, cardTitle, cardContent)
We have two methods here which will respond to the user and end the session. First is tell, which accepts a string that Alexa will speak to the user, and tellWithCard, which accepts a string that Alexa speaks to the user, a string that serves as the card title, and a string that serves as the body of the card. The card is displayed within the Amazon Echo app.
The Ask Methods
ask(speechOutput, repromptSpeech)
askWithCard(speechOutput, repromptSpeech, cardTitle, cardContent)
These methods are just like the tell methods, except for two key differences. First, the session is kept open, waiting for a further response from the user. Second, the second argument is a string that Alexa will speak to the user if they haven’t responded to specify what they want.
The Response Object
Authorization versus Authentication
Emit Types Below.
This object returns four methods: tell, tellWithCard (Card gets send to the app associate with Echo Dot), ask, and askWithCard.
The Tell Methods (Closes the session after sending the response)
tell(speechOutput)
tellWithCard(speechOutput, cardTitle, cardContent)
We have two methods here which will respond to the user and end the session. First is tell, which accepts a string that Alexa will speak to the user, and tellWithCard, which accepts a string that Alexa speaks to the user, a string that serves as the card title, and a string that serves as the body of the card. The card is displayed within the Amazon Echo app.
The Ask Methods (Keep session open (Multiple request/response cycles) for asking more questions – e.g. booking a holiday, get more info)
ask(speechOutput, repromptSpeech)
askWithCard(speechOutput, repromptSpeech, cardTitle, cardContent)
These methods are just like the tell methods, except for two key differences. First, the session is kept open, waiting for a further response from the user. Second, the second argument is a string that Alexa will speak to the user if they haven’t responded to specify what they want.
The primary difference between these two types is in how the access token is obtained from your system. From the end user’s perspective, there is no difference.
> OAuth 2.0 Underlying security platform
> Alexa proprietary signature validation
Resource Owner Role: User
The resource owner is the user who authorizes an application to access their account. The application's access to the user's account is limited to the "scope" of the authorization granted (e.g. read or write access).
Resource Role / Authorization Server Role: API
The resource server hosts the protected user accounts, and the authorization server verifies the identity of the user then issues access tokens to the application. From an application developer's point of view, a service's API fulfills both the resource and authorization server roles. We will refer to both of these roles combined, as the Service or API role.
Client: Application
The client is the application that wants to access the user's account. Before it may do so, it must be authorized by the user, and the authorization must be validated by the API.
The Response Object
This object returns four methods: tell, tellWithCard, ask, and askWithCard.
The Tell Methods
tell(speechOutput)
tellWithCard(speechOutput, cardTitle, cardContent)
We have two methods here which will respond to the user and end the session. First is tell, which accepts a string that Alexa will speak to the user, and tellWithCard, which accepts a string that Alexa speaks to the user, a string that serves as the card title, and a string that serves as the body of the card. The card is displayed within the Amazon Echo app.
The Ask Methods
ask(speechOutput, repromptSpeech)
askWithCard(speechOutput, repromptSpeech, cardTitle, cardContent)
These methods are just like the tell methods, except for two key differences. First, the session is kept open, waiting for a further response from the user. Second, the second argument is a string that Alexa will speak to the user if they haven’t responded to specify what they want.