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.
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.
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.
Building Speech Enabled Products with Amazon Polly & Amazon LexAmazon Web Services
This session will introduce you to Amazon Polly, a deep learning service that turns text into lifelike speech. Polly enables existing applications to speak as a first class feature and creates the opportunity for entirely new categories of speech-enabled products – from mobile apps and cars, to devices and appliances. Polly includes 47 lifelike voices and support for 24 languages, so you can select the ideal voice and distribute your speech-enabled applications in many geographies. Polly is easy to use – you just send the text you want converted into speech to the Polly API, and Polly immediately returns the audio stream to your application so you can play it directly or store it in a standard audio file format, such as MP3. Polly supports Speech Synthesis Markup Language (SSML) tags like prosody so you can adjust the speech rate, pitch, or volume. Polly is a secure service that delivers all of these benefits at high scale and at low latency. You can cache and replay Polly’s generated speech at no additional cost. Polly lets you convert 5M characters per month for free during the first year. Polly’s pay-as-you-go pricing, low cost per request, and lack of restrictions on storage and reuse of voice output make it a cost-effective way to enable speech synthesis everywhere.
Getting Started with Amazon Lex - AWS Summit Cape Town 2017 Amazon Web Services
Amazon Lex is a service for building conversational interfaces into any application using voice and text. With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer, enabling you to quickly and easily build sophisticated, natural language conversational chatbots. No deep learning experience is required to immediately start creating chatbots that understand voice or text, to ask questions, get answers, and complete sophisticated tasks. Lex enables you to easily publish your chatbots to mobile devices, web apps, services, and platforms such as Facebook Messenger, Twilio and Slack. This session will go over the features available with Amazon Lex and how they can be used to build and deploy chatbots. Join us for this introductory presentation and learn more about Amazon Lex!
AWS Speaker: Herbert-John Kelly, Solutions Architect - Amazon Web Services
Engage your users with a natural language conversational interface using voice and text. Create a chat bot to understand your users’ intentions and fulfill their requests. Engage in a conversation to extract key pieces of data from the user. Fulfil the users’ intentions with AWS Lambda functions. Integration examples with Facebook messenger & Slack.
Building Speech Enabled Products with Amazon Polly & Amazon LexAmazon Web Services
by Dario Rivera, Solutions Architect, AWS
This session will introduce you to Amazon Polly, a deep learning service that turns text into lifelike speech. Polly enables existing applications to speak as a first class feature and creates the opportunity for entirely new categories of speech-enabled products – from mobile apps and cars, to devices and appliances. Polly includes 47 lifelike voices and support for 24 languages, so you can select the ideal voice and distribute your speech-enabled applications in many geographies. Polly is easy to use – you just send the text you want converted into speech to the Polly API, and Polly immediately returns the audio stream to your application so you can play it directly or store it in a standard audio file format, such as MP3. Polly supports Speech Synthesis Markup Language (SSML) tags like prosody so you can adjust the speech rate, pitch, or volume. Polly is a secure service that delivers all of these benefits at high scale and at low latency. You can cache and replay Polly’s generated speech at no additional cost. Polly lets you convert 5M characters per month for free during the first year. Polly’s pay-as-you-go pricing, low cost per request, and lack of restrictions on storage and reuse of voice output make it a cost-effective way to enable speech synthesis everywhere. Join this session to learn more and find out how you get can started with Amazon Polly, today!
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.
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.
Building Speech Enabled Products with Amazon Polly & Amazon LexAmazon Web Services
This session will introduce you to Amazon Polly, a deep learning service that turns text into lifelike speech. Polly enables existing applications to speak as a first class feature and creates the opportunity for entirely new categories of speech-enabled products – from mobile apps and cars, to devices and appliances. Polly includes 47 lifelike voices and support for 24 languages, so you can select the ideal voice and distribute your speech-enabled applications in many geographies. Polly is easy to use – you just send the text you want converted into speech to the Polly API, and Polly immediately returns the audio stream to your application so you can play it directly or store it in a standard audio file format, such as MP3. Polly supports Speech Synthesis Markup Language (SSML) tags like prosody so you can adjust the speech rate, pitch, or volume. Polly is a secure service that delivers all of these benefits at high scale and at low latency. You can cache and replay Polly’s generated speech at no additional cost. Polly lets you convert 5M characters per month for free during the first year. Polly’s pay-as-you-go pricing, low cost per request, and lack of restrictions on storage and reuse of voice output make it a cost-effective way to enable speech synthesis everywhere.
Getting Started with Amazon Lex - AWS Summit Cape Town 2017 Amazon Web Services
Amazon Lex is a service for building conversational interfaces into any application using voice and text. With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer, enabling you to quickly and easily build sophisticated, natural language conversational chatbots. No deep learning experience is required to immediately start creating chatbots that understand voice or text, to ask questions, get answers, and complete sophisticated tasks. Lex enables you to easily publish your chatbots to mobile devices, web apps, services, and platforms such as Facebook Messenger, Twilio and Slack. This session will go over the features available with Amazon Lex and how they can be used to build and deploy chatbots. Join us for this introductory presentation and learn more about Amazon Lex!
AWS Speaker: Herbert-John Kelly, Solutions Architect - Amazon Web Services
Engage your users with a natural language conversational interface using voice and text. Create a chat bot to understand your users’ intentions and fulfill their requests. Engage in a conversation to extract key pieces of data from the user. Fulfil the users’ intentions with AWS Lambda functions. Integration examples with Facebook messenger & Slack.
Building Speech Enabled Products with Amazon Polly & Amazon LexAmazon Web Services
by Dario Rivera, Solutions Architect, AWS
This session will introduce you to Amazon Polly, a deep learning service that turns text into lifelike speech. Polly enables existing applications to speak as a first class feature and creates the opportunity for entirely new categories of speech-enabled products – from mobile apps and cars, to devices and appliances. Polly includes 47 lifelike voices and support for 24 languages, so you can select the ideal voice and distribute your speech-enabled applications in many geographies. Polly is easy to use – you just send the text you want converted into speech to the Polly API, and Polly immediately returns the audio stream to your application so you can play it directly or store it in a standard audio file format, such as MP3. Polly supports Speech Synthesis Markup Language (SSML) tags like prosody so you can adjust the speech rate, pitch, or volume. Polly is a secure service that delivers all of these benefits at high scale and at low latency. You can cache and replay Polly’s generated speech at no additional cost. Polly lets you convert 5M characters per month for free during the first year. Polly’s pay-as-you-go pricing, low cost per request, and lack of restrictions on storage and reuse of voice output make it a cost-effective way to enable speech synthesis everywhere. Join this session to learn more and find out how you get can started with Amazon Polly, today!
Introducing Amazon Lex – Service for Building Voice or Text ChatbotsAmazon Web Services
Register for the Chatbot Challenge!
https://awschatbot2017.devpost.com/
- Learn about the features of Amazon Lex
- Learn how to build a chatbot with Amazon Lex
- Learn how to deploy to different messaging platforms with Amazon Lex from the console
- Learn how to get quickly started with Amazon Lex
Conversational interfaces through text with applications like Slack, and through voice with platforms like Amazon Alexa, are rapidly becoming mainstream. Amazon Lex enables you to quickly and easily build sophisticated, natural language conversational chatbots with the same deep learning technologies that power Amazon Alexa. No deep learning experience is required to immediately start creating chatbots that understand voice or text, to ask questions, get answers, and complete sophisticated tasks. This session will go over the features available with Amazon Lex and how they can be used, including how to easily publish your chatbots to mobile devices, web apps, services, and platforms such as Facebook Messenger, Twilio and Slack.
Building Speech Enabled Products with Amazon Polly & Amazon LexAmazon Web Services
This document provides an introduction to Amazon Polly and Amazon Lex. It discusses the features and functionality of Polly, including its wide selection of voices and languages available as well as its quality, pricing and use cases. It then introduces Amazon Lex, discussing its text and speech language understanding capabilities powered by the same technology as Alexa. It covers Lex's features such as enterprise connectors, deployment to chat services, versioning and aliases. The document concludes with examples of Lex bots and a demo of a "DevOps" chatbot integrated with Slack using Lex and AWS Lambda.
This document summarizes a workshop on architecting user authentication and authorization in apps using AWS services. The workshop covers Amazon Cognito for user management, authentication, and data synchronization across devices. It provides an overview of Cognito User Pools and Federated Identities, demonstrates an authentication workflow using the services, and discusses how to get started with a sample Angular app.
AWS re:Invent 2016: Serverless Authentication and Authorization: Identity Man...Amazon Web Services
By leveraging "serverless architectures", startups and enterprises are building and running modern applications and services with increased agility and simplified scalability—all without managing a single server. Many applications need to manage user identities and support sign-in/sign-up. In this session, we dive deep on how to support millions of user identities, as well as how to integrate with social identity providers (such as Google and Facebook) and existing corporate directories. You learn the real-world design patterns that AWS customers use to implement authentication and authorization. By combining Amazon Cognito identity pools and user pools with API Gateway, AWS Lambda, and AWS IAM, you can add security without adding servers.
Building a Chatbot with Amazon Lex and AWS Lambda WorkshopAmazon Web Services
Like coffee? Or just want to build a bot that can take your order? Come learn how to build a chatbot using Amazon Lex and AWS Lambda. And if you’re up for it, bring a cable and a mobile device so you can see how easy it is to make a real app that talks back using AWS Mobile Hub.
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
AWS re:Invent 2016: Workshop: Building Serverless Bots on AWS - Botathon (DCS...Amazon Web Services
In this session we will learn about building Serverless Bots using AWS Services. We will explore contemporary examples of Bots and Serverless architectural building blocks needed to build a Bot. Taking few sample Bots, we will dive deeper into the AWS Services used to build them. The focus will be on Serverless architectural components such as Lambda, API Gateway, Alexa Skills Kit, etc. We will explore different interfaces, voice (eg. Alexa) and text (eg. Slack). We will also discuss about building intelligent Bots.
In the hands on session, the participants will build a Serverless Bot. Participants are free to choose any theme for their Bot, although guidance will be provided on few starter ideas. The participants will be grouped into teams and will have access to starter code, libraries so that they can focus on building their unique bot rather than the underlying undifferentiated heavy lifting. At the end of the hour, the Bots get voted on and the winning Bot is demoed. Through this workshop, the participants will get a deeper understanding of Serverless AWS Services and how to use them to build a Serverless Bot.
Prerequisites:
Participants should have an AWS account established and available for use during the workshop.
Please bring your own laptop.
API Gateways can simplify the work that a developer needs to do to build API based services by helping to standardize authentication and authorization, consumer interfaces, and management needs. With Amazon API Gateway you get all of this and more, including a completely serverless management of your APIs and the ability to host them at almost any scale. You also can get the benefits of the numerous types of APIs that are supported, from pubic to private, REST to Websockets, backed by almost any backend you can think of. In this session we’ll review the powerful capabilities of Amazon API Gateway and how you can get started building awesome APIs.
Speaker: Chris Munns - Principal Developer Advocate, AWS Serverless Applications, AWS
Building ChatBots with Amazon Lex - AWS Summit Tel Aviv 2017Amazon Web Services
Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon 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. Join this session and learn how get started with Amazon Lex, add conversational interface features to your applications and integrate with text-chat and voice based interfaces.
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
Securing Serverless Workloads with Cognito and API Gateway Part I - AWS Secur...Amazon Web Services
The document discusses securing serverless applications using Amazon API Gateway, AWS Lambda, and Amazon Cognito. It describes how to build a basic 3-tier web app that is fully serverless, add authentication with Amazon Cognito by integrating with Cognito user pools, and implement authorization using AWS Identity and Access Management (IAM) by leveraging Cognito. Key benefits mentioned are that AWS Lambda and API Gateway provide automatic scaling with no infrastructure to manage, while security is improved by making use of IAM through Cognito.
Build a Server-less Event-driven Backend with AWS Lambda and Amazon API GatewayDanilo Poccia
The document discusses building a serverless, event-driven backend architecture using AWS Lambda and Amazon API Gateway. It describes how API Gateway can be used to define HTTP endpoints that trigger Lambda functions to execute business logic. This allows building scalable backend services without having to manage servers. The document provides an example media sharing application architecture built with this approach.
This document provides an introduction to building voice driven experiences using Amazon Web Services (AWS) and Alexa Skills Kit (ASK). It discusses how skills work, the ASK architecture which includes configuration data and a hosted service, intent schemas, built-in and custom slot types, requests the Alexa service will post, and techniques for testing skills. It also demonstrates configuring a new skill using AWS Lambda.
The document discusses Amazon Lex, a service for building conversational interfaces using voice and text. It provides an overview of Lex's key features such as text and speech language understanding powered by the same technology as Alexa, connectors to enterprise systems, deployment to chat services like Facebook Messenger, and tools for efficiently building conversations. The document also covers how to get started with Lex by signing up for a free account and building a first bot.
(DEV203) Amazon API Gateway & AWS Lambda to Build Secure APIsAmazon Web Services
Amazon API Gateway is a fully managed service that makes it easy for developers to create, deploy, secure, and monitor APIs at any scale. In this presentation, you’ll find out how to quickly declare an API interface and connect it with code running on AWS Lambda. Amazon API Gateway handles all of the tasks involved in accepting and processing up to hundreds of thousands of concurrent API calls, including traffic management, authorization and access control, monitoring, and API version management. We will demonstrate how to build an API that uses AWS Identity and Access Management (IAM) for authorization and Amazon Cognito to retrieve temporary credentials for your API calls. We will write the AWS Lambda function code in Java and build an iOS sample application in Objective C.
Stephen Liedig: Building Serverless Backends with AWS Lambda and API GatewaySteve Androulakis
Stephen Liedig (Amazon Web Services) is a Public Sector Solutions Architect at AWS working closely with local and state governments, educational institutions, and non-profit organisations across Australia and New Zealand to design, and deliver, highly secure, scalable, reliable and fault-tolerant architectures in the AWS Cloud while sharing best practices and current trends, with a specific focus on DevOps, messaging, and serverless technologies.
This document introduces Amazon Lex, a new service for building conversational interfaces using voice and text. Amazon Lex provides natural language understanding capabilities powered by the same technology as Alexa. It allows developers to build chatbots and deploy them to messaging platforms like Facebook Messenger. Amazon Lex is designed to be efficient and intuitive for developers to build conversations that can integrate with external systems through connectors. Pricing is $0.75 per 1000 text requests and $4.00 per 1000 speech requests.
By leveraging serverless architectures, organisations are building and running modern applications and services with increased agility and simplified scalability—all without managing a single server. Many applications need to manage user identities and support sign-in/sign-up. In this session, we dive deep on how to support millions of user identities, as well as how to integrate with social identity providers and existing corporate directories. We will show the real-world design patterns that AWS customers use to implement authentication and authorisation.
Speaker: Myles Hosford, Security Solutions Architect, Amazon Web Services
Introducing Amazon Lex – A Service for Building Voice or Text Chatbots - Marc...Amazon 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
Chatbots are the new apps. Businesses of all sizes, from startups to enterprises, are looking for new ways to connect with their users through natural, conversational interfaces. Developers have started using chatbots to improve the productivity and efficiency of their operations. In this session, we show how to use AWS Lambda and other serverless offerings from AWS to build chatbots quickly and efficiently. We share examples from our recently concluded AWS Slack Hackathon with a full walkthrough of building a conversational chatbot in an easy, fast, and fun way, along with helpful tools, tips, and techniques.
Serve Your Customers with AI from the Cloud: AWS Developer Workshop - Web Sum...Amazon Web Services
Serve Your Customers with AI from Cloud: AWS Developer Workshop - Web Summit 2018
Conversational interfaces are the latest hot trend in human computer interaction. In this session we will Deep Dive into Amazon Lex, an AWS service that enables developers to embed conversational interfaces within their own applications or deploy intelligent chatbots onto a variety of chat platforms and social networks. You'll also be able to interact with a production chatbot live during this session, so be sure to bring a device with Facebook Messenger along!
Speaker: Ian Massingham - Director, Technical Evangelist, AWS
Introducing Amazon Lex – Service for Building Voice or Text ChatbotsAmazon Web Services
Register for the Chatbot Challenge!
https://awschatbot2017.devpost.com/
- Learn about the features of Amazon Lex
- Learn how to build a chatbot with Amazon Lex
- Learn how to deploy to different messaging platforms with Amazon Lex from the console
- Learn how to get quickly started with Amazon Lex
Conversational interfaces through text with applications like Slack, and through voice with platforms like Amazon Alexa, are rapidly becoming mainstream. Amazon Lex enables you to quickly and easily build sophisticated, natural language conversational chatbots with the same deep learning technologies that power Amazon Alexa. No deep learning experience is required to immediately start creating chatbots that understand voice or text, to ask questions, get answers, and complete sophisticated tasks. This session will go over the features available with Amazon Lex and how they can be used, including how to easily publish your chatbots to mobile devices, web apps, services, and platforms such as Facebook Messenger, Twilio and Slack.
Building Speech Enabled Products with Amazon Polly & Amazon LexAmazon Web Services
This document provides an introduction to Amazon Polly and Amazon Lex. It discusses the features and functionality of Polly, including its wide selection of voices and languages available as well as its quality, pricing and use cases. It then introduces Amazon Lex, discussing its text and speech language understanding capabilities powered by the same technology as Alexa. It covers Lex's features such as enterprise connectors, deployment to chat services, versioning and aliases. The document concludes with examples of Lex bots and a demo of a "DevOps" chatbot integrated with Slack using Lex and AWS Lambda.
This document summarizes a workshop on architecting user authentication and authorization in apps using AWS services. The workshop covers Amazon Cognito for user management, authentication, and data synchronization across devices. It provides an overview of Cognito User Pools and Federated Identities, demonstrates an authentication workflow using the services, and discusses how to get started with a sample Angular app.
AWS re:Invent 2016: Serverless Authentication and Authorization: Identity Man...Amazon Web Services
By leveraging "serverless architectures", startups and enterprises are building and running modern applications and services with increased agility and simplified scalability—all without managing a single server. Many applications need to manage user identities and support sign-in/sign-up. In this session, we dive deep on how to support millions of user identities, as well as how to integrate with social identity providers (such as Google and Facebook) and existing corporate directories. You learn the real-world design patterns that AWS customers use to implement authentication and authorization. By combining Amazon Cognito identity pools and user pools with API Gateway, AWS Lambda, and AWS IAM, you can add security without adding servers.
Building a Chatbot with Amazon Lex and AWS Lambda WorkshopAmazon Web Services
Like coffee? Or just want to build a bot that can take your order? Come learn how to build a chatbot using Amazon Lex and AWS Lambda. And if you’re up for it, bring a cable and a mobile device so you can see how easy it is to make a real app that talks back using AWS Mobile Hub.
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
AWS re:Invent 2016: Workshop: Building Serverless Bots on AWS - Botathon (DCS...Amazon Web Services
In this session we will learn about building Serverless Bots using AWS Services. We will explore contemporary examples of Bots and Serverless architectural building blocks needed to build a Bot. Taking few sample Bots, we will dive deeper into the AWS Services used to build them. The focus will be on Serverless architectural components such as Lambda, API Gateway, Alexa Skills Kit, etc. We will explore different interfaces, voice (eg. Alexa) and text (eg. Slack). We will also discuss about building intelligent Bots.
In the hands on session, the participants will build a Serverless Bot. Participants are free to choose any theme for their Bot, although guidance will be provided on few starter ideas. The participants will be grouped into teams and will have access to starter code, libraries so that they can focus on building their unique bot rather than the underlying undifferentiated heavy lifting. At the end of the hour, the Bots get voted on and the winning Bot is demoed. Through this workshop, the participants will get a deeper understanding of Serverless AWS Services and how to use them to build a Serverless Bot.
Prerequisites:
Participants should have an AWS account established and available for use during the workshop.
Please bring your own laptop.
API Gateways can simplify the work that a developer needs to do to build API based services by helping to standardize authentication and authorization, consumer interfaces, and management needs. With Amazon API Gateway you get all of this and more, including a completely serverless management of your APIs and the ability to host them at almost any scale. You also can get the benefits of the numerous types of APIs that are supported, from pubic to private, REST to Websockets, backed by almost any backend you can think of. In this session we’ll review the powerful capabilities of Amazon API Gateway and how you can get started building awesome APIs.
Speaker: Chris Munns - Principal Developer Advocate, AWS Serverless Applications, AWS
Building ChatBots with Amazon Lex - AWS Summit Tel Aviv 2017Amazon Web Services
Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon 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. Join this session and learn how get started with Amazon Lex, add conversational interface features to your applications and integrate with text-chat and voice based interfaces.
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
Securing Serverless Workloads with Cognito and API Gateway Part I - AWS Secur...Amazon Web Services
The document discusses securing serverless applications using Amazon API Gateway, AWS Lambda, and Amazon Cognito. It describes how to build a basic 3-tier web app that is fully serverless, add authentication with Amazon Cognito by integrating with Cognito user pools, and implement authorization using AWS Identity and Access Management (IAM) by leveraging Cognito. Key benefits mentioned are that AWS Lambda and API Gateway provide automatic scaling with no infrastructure to manage, while security is improved by making use of IAM through Cognito.
Build a Server-less Event-driven Backend with AWS Lambda and Amazon API GatewayDanilo Poccia
The document discusses building a serverless, event-driven backend architecture using AWS Lambda and Amazon API Gateway. It describes how API Gateway can be used to define HTTP endpoints that trigger Lambda functions to execute business logic. This allows building scalable backend services without having to manage servers. The document provides an example media sharing application architecture built with this approach.
This document provides an introduction to building voice driven experiences using Amazon Web Services (AWS) and Alexa Skills Kit (ASK). It discusses how skills work, the ASK architecture which includes configuration data and a hosted service, intent schemas, built-in and custom slot types, requests the Alexa service will post, and techniques for testing skills. It also demonstrates configuring a new skill using AWS Lambda.
The document discusses Amazon Lex, a service for building conversational interfaces using voice and text. It provides an overview of Lex's key features such as text and speech language understanding powered by the same technology as Alexa, connectors to enterprise systems, deployment to chat services like Facebook Messenger, and tools for efficiently building conversations. The document also covers how to get started with Lex by signing up for a free account and building a first bot.
(DEV203) Amazon API Gateway & AWS Lambda to Build Secure APIsAmazon Web Services
Amazon API Gateway is a fully managed service that makes it easy for developers to create, deploy, secure, and monitor APIs at any scale. In this presentation, you’ll find out how to quickly declare an API interface and connect it with code running on AWS Lambda. Amazon API Gateway handles all of the tasks involved in accepting and processing up to hundreds of thousands of concurrent API calls, including traffic management, authorization and access control, monitoring, and API version management. We will demonstrate how to build an API that uses AWS Identity and Access Management (IAM) for authorization and Amazon Cognito to retrieve temporary credentials for your API calls. We will write the AWS Lambda function code in Java and build an iOS sample application in Objective C.
Stephen Liedig: Building Serverless Backends with AWS Lambda and API GatewaySteve Androulakis
Stephen Liedig (Amazon Web Services) is a Public Sector Solutions Architect at AWS working closely with local and state governments, educational institutions, and non-profit organisations across Australia and New Zealand to design, and deliver, highly secure, scalable, reliable and fault-tolerant architectures in the AWS Cloud while sharing best practices and current trends, with a specific focus on DevOps, messaging, and serverless technologies.
This document introduces Amazon Lex, a new service for building conversational interfaces using voice and text. Amazon Lex provides natural language understanding capabilities powered by the same technology as Alexa. It allows developers to build chatbots and deploy them to messaging platforms like Facebook Messenger. Amazon Lex is designed to be efficient and intuitive for developers to build conversations that can integrate with external systems through connectors. Pricing is $0.75 per 1000 text requests and $4.00 per 1000 speech requests.
By leveraging serverless architectures, organisations are building and running modern applications and services with increased agility and simplified scalability—all without managing a single server. Many applications need to manage user identities and support sign-in/sign-up. In this session, we dive deep on how to support millions of user identities, as well as how to integrate with social identity providers and existing corporate directories. We will show the real-world design patterns that AWS customers use to implement authentication and authorisation.
Speaker: Myles Hosford, Security Solutions Architect, Amazon Web Services
Introducing Amazon Lex – A Service for Building Voice or Text Chatbots - Marc...Amazon 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
Chatbots are the new apps. Businesses of all sizes, from startups to enterprises, are looking for new ways to connect with their users through natural, conversational interfaces. Developers have started using chatbots to improve the productivity and efficiency of their operations. In this session, we show how to use AWS Lambda and other serverless offerings from AWS to build chatbots quickly and efficiently. We share examples from our recently concluded AWS Slack Hackathon with a full walkthrough of building a conversational chatbot in an easy, fast, and fun way, along with helpful tools, tips, and techniques.
Serve Your Customers with AI from the Cloud: AWS Developer Workshop - Web Sum...Amazon Web Services
Serve Your Customers with AI from Cloud: AWS Developer Workshop - Web Summit 2018
Conversational interfaces are the latest hot trend in human computer interaction. In this session we will Deep Dive into Amazon Lex, an AWS service that enables developers to embed conversational interfaces within their own applications or deploy intelligent chatbots onto a variety of chat platforms and social networks. You'll also be able to interact with a production chatbot live during this session, so be sure to bring a device with Facebook Messenger along!
Speaker: Ian Massingham - Director, Technical Evangelist, AWS
BDA306 NEW LAUNCH! An Introduction to Amazon Lex, your service for building v...Amazon Web Services
Amazon Lex is a service for building conversational interfaces into any application using voice and text. With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer, enabling you to quickly and easily build sophisticated, natural language conversational chatbots. No deep learning experience is required to immediately start creating chatbots that understand voice or text, to ask questions, get answers, and complete sophisticated tasks. Lex enables you to easily publish your chatbots to mobile devices, web apps, services, and platforms such as Facebook Messenger, Twilio and Slack. This session will go over the features available with Amazon Lex and how they can be used to build and deploy chatbots. Join us for this introductory presentation and learn more about Amazon Lex!
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
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.
Integrate Your Amazon Lex Chatbot with Any Messaging ServiceAmazon Web Services
Amazon Lex offers built-in integrations with Slack, Twilio, Marketo, Salesforce, Quickbooks, Microsoft Dynamics, Zendesk, and Hubspot. But, you can also integrate with any other application by combining the Lex API and AWS API Gateway to extend your chatbots into virtually any use case with minimal effort.
This session will show you how. The design pattern shown will be interesting to folks who want to build a pre-processing layer in front of Lex or want to route messages to multiple specialized bots.
The document summarizes James Beswick's presentation on AWS re:Invent 2020 recaps for the ServerlessToronto meetup group. It highlights several new features from re:Invent including Lambda extensions and container image support, larger Lambda functions with more memory and CPUs, and other service releases. It also lists some on-demand sessions from re:Invent on serverless topics. Beswick thanks the attendees and invites them to join the ServerlessToronto community.
Zombie Apocalypse Workshop by Warren Santer and Kyle Somers, Solutions Archit...Amazon Web Services
The document provides an overview of a workshop on building serverless microservices using AWS Lambda. The workshop will introduce AWS Lambda, Amazon API Gateway, Amazon DynamoDB, and Amazon Cognito. Attendees will work in teams to build a secure, scalable chat service for zombie apocalypse survivors using these AWS serverless technologies. The workshop includes breakout sessions where attendees will add features like typing indicators, SMS integration with Twilio, messaging search with Elasticsearch, integration with Slack, and zombie sensor data integration with Intel Edison.
Integrate Your Amazon Lex Chatbot with Any Messaging Service - AWS Online Tec...Amazon Web Services
Learning Objectives:
- Learn about Amazon Lex and associated concepts such as intents and utterances, Learn how to setup and configure Amazon API Gateway, How to leverage AWS Lambda as the compute layer in front of Amazon Lex
Integrate Your Amazon Lex Chatbot with Any Messaging Service - AWS Online Tec...Amazon Web Services
Learning Objectives:
- Learn about Amazon Lex and associated concepts such as intents and utterances
- Learn how to setup and configure Amazon API Gateway
- How to leverage AWS Lambda as the compute layer in front of Amazon Lex
Reimagining your user experience with Amazon Lex, Amazon Polly and Alexa Ski...Amazon Web Services
AWS offers a family of AI services that provide cloud-native Machine Learning and Deep Learning technologies, allowing developers to build an entirely new generation of apps that can hear, speak, understand, and converse with application users. When creating chat- and voice-enabled applications, developers have the choice of building with Amazon Lex and Amazon Polly, or, with the Alexa Skills Kit, available now in Australia and New Zealand. With the Alexa Skills Kit, you can build engaging skills to reach customers through tens of millions of Alexa-enabled devices, like the Amazon Echo and Echo Dot.
Paul Maddox gave a presentation on deploying containerized microservices applications on Amazon ECS. He demonstrated building a Twitter analyzer application with Go microservices that communicate via RPC and are deployed to a production ECS cluster using AWS CloudFormation templates. Key components included Amazon ECS, ECR, container instances, tasks and containers. Deployments were made repeatable and auditable using infrastructure-as-code.
Building Multichannel Conversational Interfaces Using Amazon Lex - MCL312 - r...Amazon Web Services
In this session, discover how to build a multichannel conversational interface that leverages a preprocessing layer in front of Amazon Lex. This preprocessing layer can enable customers to integrate their conversational interface with external services and use multiple specialized Amazon Lex chatbots as part of an overall solution. As an example of how to integrate with an external service, learn how to integrate with Skype. Watch it in action through a chatbot demonstration with interaction through Skype messaging and voice.
This document provides an overview of a serverless workshop on building microservices for a zombie apocalypse chat application. The workshop will introduce AWS Lambda, Amazon API Gateway, DynamoDB and other AWS serverless services. Attendees will work in teams to implement features like user typing indicators, SMS integration, message search and sensors for the chat app. The goal is to experience building event-driven architectures without having to manage servers. Special challenges will provide extra credit opportunities. The total estimated cost for running the 3 hour workshop on AWS serverless services is less than $1.
Integrate Your Amazon Lex Chatbot with Any Messaging Service - May 2017 AWS O...Amazon Web Services
Learning Objectives:
- Learn how to setup and configure AWS API Gateway
- Learn how to leverage AWS Lambda as the compute layer in front of Amazon Lex
- Learn about Multi-bot architecture
Amazon Lex offers built-in integrations with Slack, Twilio, Marketo, Salesforce, Quickbooks, Microsoft Dynamics, Zendesk, and Hubspot. But, you can also integrate with any other application by combining the Lex API and AWS API Gateway to extend your chatbots into virtually any use case with minimal effort. This session will show you how. The design pattern shown will be interesting to folks who want to build a pre-processing layer in front of Lex or want to route messages to multiple specialized bots.
Deep Dive on Amazon Elastic Container Service (ECS) and FargateAmazon Web Services
This document summarizes a presentation about deploying and managing containerized microservices applications on Amazon ECS. It discusses key components like ECS, ECR, and container instances. It then covers topics like deployment with CloudFormation, cost optimization with reserved instances and spot instances, scaling, security practices like patching and IAM roles, and monitoring with CloudWatch.
Building Chatbots with Amazon Lex I AWS Dev Day 2018AWS Germany
Amazon Lex is a service that allows developers to build conversational interfaces into any application using voice and text. It uses the same deep learning technology as Amazon Alexa to understand user intent and respond conversationally. Developers can build bots using Lex that can be deployed to messaging platforms and mobile apps. Lex provides tools to efficiently create conversations through utterances, intents, slots and fulfillment modeling while automatically scaling.
With AWS Lambda, you can easily build scalable microservices for mobile, web, and IoT applications or respond to events from other AWS services without managing infrastructure. In this session, you’ll see demonstrations and hear more about newly launched features. We’ll show you how to use Lambda to build web, mobile, or IoT backends and voice-enabled apps, and we'll show you how to extend both AWS and third party services by triggering Lambda functions. We’ll also provide productivity and performance tips for getting the most out of your Lambda functions and show how cloud native architectures use Lambda to eliminate “cold servers” and excess capacity without sacrificing scalability or responsiveness.
Similar to Building a Better .NET Bot with AWS Services - WIN205 - re:Invent 2017 (20)
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.
1) The document discusses building a minimum viable product (MVP) using Amazon Web Services (AWS).
2) It provides an example of an MVP for an omni-channel messenger platform that was built from 2017 to connect ecommerce stores to customers via web chat, Facebook Messenger, WhatsApp, and other channels.
3) The founder discusses how they started with an MVP in 2017 with 200 ecommerce stores in Hong Kong and Taiwan, and have since expanded to over 5000 clients across Southeast Asia using AWS for scaling.
This document discusses pitch decks and fundraising materials. It explains that venture capitalists will typically spend only 3 minutes and 44 seconds reviewing a pitch deck. Therefore, the deck needs to tell a compelling story to grab their attention. It also provides tips on tailoring different types of decks for different purposes, such as creating a concise 1-2 page teaser, a presentation deck for pitching in-person, and a more detailed read-only or fundraising deck. The document stresses the importance of including key information like the problem, solution, product, traction, market size, plans, team, and ask.
This document discusses building serverless web applications using AWS services like API Gateway, Lambda, DynamoDB, S3 and Amplify. It provides an overview of each service and how they can work together to create a scalable, secure and cost-effective serverless application stack without having to manage servers or infrastructure. Key services covered include API Gateway for hosting APIs, Lambda for backend logic, DynamoDB for database needs, S3 for static content, and Amplify for frontend hosting and continuous deployment.
This document provides tips for fundraising from startup founders Roland Yau and Sze Lok Chan. It discusses generating competition to create urgency for investors, fundraising in parallel rather than sequentially, having a clear fundraising narrative focused on what you do and why it's compelling, and prioritizing relationships with people over firms. It also notes how the pandemic has changed fundraising, with examples of deals done virtually during this time. The tips emphasize being fully prepared before fundraising and cultivating connections with investors in advance.
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...Amazon Web Services
This document discusses Amazon's machine learning services for building conversational interfaces and extracting insights from unstructured text and audio. It describes Amazon Lex for creating chatbots, Amazon Comprehend for natural language processing tasks like entity extraction and sentiment analysis, and how they can be used together for applications like intelligent call centers and content analysis. Pre-trained APIs simplify adding machine learning to apps without requiring ML expertise.
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. What to expect from the workshop
Learn how to create a Amazon Lex ChatBot from AWS
Management Console
Learn how to create a backend for a Amazon Lex ChatBot with
AWS Lambda
Learn how to add secure credentials to your Amazon Lex ChatBot
with Amazon Cognito
Learn how to create a .NET/ASP.NET Core ChatBot solution using
AWS SDK for NET and Visual Studio
Learn how to deploy a ASP.NET Core ChatBot solution with a
CI/CD pipeline to Amazon EC2 using AWS CodeStar
3. Agenda
• Introduction to Amazon Lex
• Hands-On: Create Your Lex ChatBot
• Introduction to AWS Lambda
• Hands-On: Create Your Lambda function for Lex ChatBot Fulfillment
• Intro to Amazon Cognito
• Hands-On: Create Your Cognito Federated Identity Pool
• Intro to AWS SDK for .NET
• Hands-On: Start Your ASP.NET Core Web ChatBot Solution
• Intro to CI/CD Tools for Deployment: AWS CodeStar
• Hands-On: Use CodeStar to Build & Deploy your ASP.NET ChatBot
4. Prerequisites
• AWS Account
• Visual Studio or Visual Studio Code
• AWS SDK for .NET Toolkit installed
• Basic Linux/Windows Based Environments with .NET
development
6. Text and speech language understanding: powered by the
same technology as Alexa
Enterprise ready: connect to enterprise systems via SaaS
connectors
Versioning and alias support
Build once and deploy to multiple platforms
Designed for builders: efficient and intuitive tools to build
conversations; scales automatically
Amazon Lex - Overview
Continuous learning: monitor and improve your bot
7. Amazon Lex – Multi-platform
Mobile
Messaging
Platforms Web IoT
SDKs: iOS &
Android
Mobile Hub
Facebook, Twilio
SMS and Slack
SDKs: Java, JavaScript,
Python, CLI, .NET, Ruby
on Rails, PHP, Go, & CPP
Integrated with
AWS IoT via AWS
Lambda
Build once and deploy to multiple platforms
8. Amazon Lex – Key Concepts
Utterances
Spoken or typed phrases that
invoke your intent
BookHotel
Intents
An intent performs an action in
response to natural language user input
Slots
Slots are input data required to
fulfill the intent
Fulfillment
Fulfillment mechanism for your
intent
9. Amazon Lex – Example: “Book a hotel”
Book Hotel
NYC
“Book a Hotel in
NYC”
Automatic Speech
Recognition
Hotel Booking
New York City
Natural Language
Understanding
Intent/Slot
Model
UtterancesHotel Booking
City New York City
Check In April 19th
Check Out April 21st
“Your hotel is booked for
April 19th”
Amazon Polly
Confirmation: “Your hotel
is booked for Nov 30th”
“Can I go ahead
with the booking?
a
in
10. Amazon Lex – Slot elicitation
Check In
4/19/2017
City
New York City
I would like to book a hotel
Sure, which city will you
be traveling to?
New York City
What date do you want to
check in?
April 19th
11. Amazon Lex – Dialog management
I would like to book a hotel
Sure, which city will you
be traveling to?
New York City
What date do you want to
check in?
Tomorrow
… And for how many
nights is this for?
City
Simple Declarative Model
Check-In Date
Check-Out Date
Slots
Which city will you be traveling to?
What date do you want to check in?
How many nights is this for?
Prompts
Build Multi-Turn Conversations
Easy Setup in Console
12. Amazon Lex – Customize conversations
I would like to book a hotel
Would you prefer to stay in
Downtown this time as well?
Yes
What date do you want to
check in?
April 19th
Sorry no availability. Would
a different location work?
Personalize conversation
based on user preferences
Validate user input and
re-prompt as necessary
13. Amazon Lex – Error handling
I want to …. {garbled} …..
Sorry can you please
repeat that?
I am having trouble understanding
Can you please say that again?
Sorry I am not able to
assist you at this time
Clarify by requesting user
to repeat
Uses a different
prompt every time
Hang up phrase to end the
conversation
14. Amazon Lex – Conversation context
Slot Values Intents Prompts ConfirmationsSession
Attributes
Slot Value
Slot Value
Conversation
Yes/No
Session
Attributes
Intent
Prompt
Lex maintains context by storing data throughout the conversation
Confirm
15. Amazon Lex – Dynamic conversation flow
Conversation
Session
Attributes
Second
Intent
Switch Intents
First Intent
Session
Attributes
Conversation
Chain Intents
Take out
Dine In
Dine In or
Take out?
Anything
else today?
Book a Car
17. Introduction to
AWS Lambda
A service for serverless compute.
Run code without provisioning
or managing servers..
18. AWS Lambda – Serverless computing
Run code without servers
Pay only for the compute time you consume.
Extend Other AWS Services with Custom Logic:
Triggered by events or called from APIs
• PUT to an Amazon S3 bucket
• Updates to Amazon DynamoDB table
• Call to an Amazon API Gateway endpoint
• Mobile app back-end call
Automated Administration & Automatic Scaling
Makes it easy to:
• Perform real-time data processing
• Build scalable back-end services
• Glue and choreograph systems
19. AWS Lambda – Service Usage
Authoring functions
• Author directly using the console
WYSIWYG editor
• Package code as a .zip and
upload to Lambda or S3
• Plugins for Visual Studio and
Eclipse
• Command line tools
Monitoring and logging
• Built-in metrics for
requests, errors, latency,
and throttles
• Built-in logs in Amazon
CloudWatch Logs
Flexible authorization
• Securely grant access to
resources, including VPCs
• Fine-grained control over
who can call your functions
Flexible use
• Call or send events
• Integrated with other
AWS services
• Build whole serverless
ecosystems
20. AWS Lambda – Programming Model
Bring your own code
• C#, Node.js, Java,
Python
• Bring your own libraries
(even native ones)
Simple resource model
• Select power rating from
128 MB to 1.5 GB
• CPU and network
allocated proportionately
• Reports actual usage
Programming model
• AWS SDK built in
(Python and Node.js)
• Lambda is the
“webserver”
• Use processes, threads,
/tmp, sockets normally
Stateless
• Persist data using Amazon
DynamoDB, S3, or Amazon
ElastiCache
• No affinity to infrastructure
(can’t “log in to the box”)
21. AWS Lambda – Amazon Lex Fulfillment
AWS Lambda
Integration
Return to
Client
User input parsed by Lex to
derive intents and slot values.
Output returned to client
for further processing
Intents and slots passed
to AWS Lambda function
for business logic
implementation
23. Introduction to
Amazon Cognito
A service for adding access control,
authentication, data synchronization, and
user sign-up/sign-in quickly and easily to
your apps like mobile & web apps..
24. Manage authenticated
and guest users’
access to your AWS
resources
Federated
Identities
Synchronize user’s data
across devices and
platforms via the cloud
Data
Synchronization
Add sign-up and
sign-in with a fully
managed user
directory
Your User Pool
GuestYour own
auth
Amazon Cognito Identity Amazon Cognito Sync
Amazon Cognito – Identity and Sync
k/v data
25. Sign in with
Facebook
Or
Username
Password
Sign In
Or
Start as a guest
Authenticate via
3rd party Identity
Providers
Amazon Cognito Identity – User Experience
Guest Access
Your User Pool in
Amazon Cognito
Amazon Cognito
Identity provides
temporary credentials
to securely access
Your resources
DynamoDB
S3
Amazon
Lex
AWS
Lambda
IAM
26. Amazon Cognito – Lex & Federated Identities
Cognito User Identities
(Your User Pool.
Social Media,
SAML, or Unauthenticated )
User
Sign-in or Secure
Guest Access1
Returns Access
and ID Tokens
2
Cognito Federated
Identities
(Identity Pool)Get AWS scoped
credentials
3
Access
to AWS Services
4
Amazon
DynamoDB
Amazon
Lex
AWS
Lambda
IAM
IAM
28. Introduction to
AWS SDK for .NET
Takes the complexity out of building .NET
applications with AWS Services
by providing .NET APIs
29. AWS SDK and tools for .NET architectureEXECUTION
PLATFORM
AWSSDK
LOW-
LEVEL
SERVICE
APIS
AWS
TOOLS
HIGHER-
LEVEL
UTILITY
APIS
.NET 4.5 .NET CORE PHONE STORE
SERVICE CLIENTS
AMAZON S3
TRANSFER UTILITY
AMAZON DYNAMODB
OBJECT PERSISTENCE
VM IMPORT RESOURCE API
AWS TOOLS FOR
WINDOWS
POWERSHELL
AWS TOOLKIT FOR
VISUAL STUDIO
ASP.NET SESSION
PROVIDER
TRACE LISTENER
…
AWS ENDPOINTS: REST API
.NET 3.5
30. AWS SDK for .NET – AWS Toolkit for Visual Studio
Full integration in Visual Studio
32. AWS SDK .NET Comprehensive and powerful tools
MonitoringConfiguration
AWS Config
Amazon EC2
Run Command
AWS Tools for
Windows PowerShell
Develop and Deploy
Amazon
CloudWatch
AWS
CloudTrail
AWS
OpsWorks
AWS Toolkit for
Visual Studio
.NET SDK AWS CodeDeploy AWS
Cloud
Formation
AWS Elastic
Beanstalk
AWS
X-Ray
AWS Lambda
33. Introduction to
AWS CodeStar & AWS Dev Tools
Set up your entire continuous delivery
toolchain in minutes, allowing you to start
releasing code faster
34. AWS CodeStar
Develop on AWS in minutes:
Set up your entire CI/CD development environment and
programming tools for coding, testing, and deploying
Collaborate securely with your entire team:
Manage team access and membership to projects
Integrated issue tracking and project management:
Integrates Atlassian JIRA Software to easily manage and
monitor issues & activity from CodeStar dashboard
Support for popular programming languages:
Develop applications using language of choice including
C#, Java, JavaScript, PHP, Ruby, and Python
Release code faster:
Set up your entire continuous delivery toolchain in minutes
35. AWS CodeStar – Features
Project Templates
Team Access Management
with AWS IAM
Managed Build Service with
AWS Code Build
Unified Project Dashboard
using Amazon CloudWatch
monitoring service
Issue tracking and project
management via integrated
Atlassian JIRA Software
AWS CodeCommit and
GitHub integration for
Secure Hosted Git
Repository
Automated App
Deployments with AWS
CodeDeploy and AWS
CloudFormation
Integration of AWS
CodePipeline for
Automated Continuous
Delivery Pipeline
36. AWS CodeStar – Automated Continuous Delivery
Each CodeStar project creates and configures a
continuous delivery pipeline
Source Build Test Production
Third Party
Tooling
Software Release Steps:
AWS CodeCommit AWS CodeBuild AWS CodeDeploy
AWS CodePipeline
37. AWS CodePipeline
Continuous delivery service for fast and reliable
application updates
Model and visualize your software release process
Builds, tests, and deploys your code every time there is a
code change
Integrates with third-party tools and AWS
38. AWS CodeCommit
Secure, scalable, and managed Git source control
Automatic encryption at rest and in transit
Supports existing tooling
Highly available
39. AWS CodeBuild
Fully managed build service with pay-as-you-
go pricing
Support for compiling source code, running
tests, and building packages
Enables continuous integration and delivery
EC2
40. AWS CodeDeploy
Automates code deployments to any instance
Handles the complexity of updating your applications
Avoid downtime during application deployment
Deploy to Amazon EC2 or on-premises servers, in any
language and on any operating system
Integrates with third-party tools and AWS
41. AWS CloudFormation
Create templates of your infrastructure
CloudFormation provisions AWS resources based on
dependency needs
Version control/replicate/update templates like code
Integrates with development, CI/CD, management tools
43. Best practices while building a bot
• Understand the conversation flow
• What information do you need from the conversation
• What is the intent/goal of the conversation
• Validate your input
• Handle errors gracefully
• Add clarification prompts if required
• Test, test and more testing
• Understand Metrics after your Bot is deployed in
production
44. Challenge 1 – Create a basic chat bot
• Be creative
• Think of real world problems that you want to solve
with this Chat Bot
• The sample below shows how you can create a basic
chat bot to launch EC2 instances based on the OS and
Instance type
• https://s3.amazonaws.com/wildrydes-
nickil/ChatOps+using+Amazon+Lex.docx
• The Slack part of the sample is not required. Feel free
to transpose the Lambda function from Python to .NET
45. Challenge 2 – Build a CI/CD pipeline using the
ChatBot you created
This .NET sample given below should give you a good
idea on how you can integrate all the pieces together.
https://github.com/awslabs/aws-lex-net-chatbot
47. Amazon Lex – A Complete solution
End to End
Speech to Intent
ASR+NLU
integrated into
one API
Dialog Management
Native support &
maintains context
Text to Speech
Amazon Polly
integrated into API
Business Logic
Native integration
with AWS Lambda
Deployment
One click
deployment
Security
Encrypted data in
transit & at rest
Scale
Completely
managed service
Analytics
Monitor and
improve