by Amit Narayanan, Solutions Architect, AWS
Amazon Lex is a service for building conversational interfaces into any application using voice and text, and Amazon Polly is a service that turns text into lifelike speech. This session combines both of these AWS services, the presenter will demonstrate how to build DevOps and Help Desk chatbots that feature spoken-voice interfaces, and explore the potential of bringing characters to life through interactive chatbots that improves customer engagement. Attendees will be provided with the foundational skills for those looking to enrich their applications with natural, conversational interfaces. Level 300
by Keith Steward, Solutions Architect, AWS
Amazon Lex is a service for building conversational interfaces into any application using voice and text, and Amazon Polly is a service that turns text into lifelike speech. This session combines both of these AWS services, the presenter will demonstrate how to build DevOps and Help Desk chatbots that feature spoken-voice interfaces, and explore the potential of bringing characters to life through interactive chatbots that improves customer engagement. Attendees will be provided with the foundational skills for those looking to enrich their applications with natural, conversational interfaces. Level 300
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.
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
AWS User Group Singapore / Amazon Lex -- JAWSDAYS 2017Alex Smith
In this presentation, we cover the growth and experience of the AWS User Group Singapore. The second half covers the use of Amazon Lex to augment User Group activities
This was originally delivered at JAWSDAYS 2017 Tokyo:- http://jawsdays2017.jaws-ug.jp/session/1337/
Engage your users with a natural language conversational interface using voice and text.
You will learn how to:
– Create a chat bot to understand your users’ intentions and fulfil their requests.
– Engage in a conversation to extract key pieces of data from the user
– Fulfil the users’ intentions with AWS Lambda functions
– Integrate with Facebook Messenger
Exploring the Business Use Cases for Amazon Lex - June 2017 AWS Online Tech T...Amazon Web Services
Learning Objectives:
- Learn about applying conversational interfaces in applications through Amazon Lex
- Learn about popular use cases for Amazon Lex
- Learn how specific AWS customers have implemented Amazon Lex in different workflows
Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex is now generally available, making it easy for developers to access the same deep learning technologies that power Amazon Alexa. In this tech talk, we will introduce Lex and walk through use cases for retail, travel and hospitality, and internal help desks, where Amazon Lex's automation engine creates the potential to reduce costs, improve service quality, and create new ways to access corporate information.
by Keith Steward, Solutions Architect, AWS
Amazon Lex is a service for building conversational interfaces into any application using voice and text, and Amazon Polly is a service that turns text into lifelike speech. This session combines both of these AWS services, the presenter will demonstrate how to build DevOps and Help Desk chatbots that feature spoken-voice interfaces, and explore the potential of bringing characters to life through interactive chatbots that improves customer engagement. Attendees will be provided with the foundational skills for those looking to enrich their applications with natural, conversational interfaces. Level 300
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.
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
AWS User Group Singapore / Amazon Lex -- JAWSDAYS 2017Alex Smith
In this presentation, we cover the growth and experience of the AWS User Group Singapore. The second half covers the use of Amazon Lex to augment User Group activities
This was originally delivered at JAWSDAYS 2017 Tokyo:- http://jawsdays2017.jaws-ug.jp/session/1337/
Engage your users with a natural language conversational interface using voice and text.
You will learn how to:
– Create a chat bot to understand your users’ intentions and fulfil their requests.
– Engage in a conversation to extract key pieces of data from the user
– Fulfil the users’ intentions with AWS Lambda functions
– Integrate with Facebook Messenger
Exploring the Business Use Cases for Amazon Lex - June 2017 AWS Online Tech T...Amazon Web Services
Learning Objectives:
- Learn about applying conversational interfaces in applications through Amazon Lex
- Learn about popular use cases for Amazon Lex
- Learn how specific AWS customers have implemented Amazon Lex in different workflows
Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex is now generally available, making it easy for developers to access the same deep learning technologies that power Amazon Alexa. In this tech talk, we will introduce Lex and walk through use cases for retail, travel and hospitality, and internal help desks, where Amazon Lex's automation engine creates the potential to reduce costs, improve service quality, and create new ways to access corporate information.
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.
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.
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.
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!
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. Join this session to learn more and find out how you get can started with Amazon Polly, today!
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
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
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.
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.
Hands-on with Rekognition, Polly & Lex - Pop-up Loft TLV 2017Amazon Web Services
The AWS Cloud now provides a range of AI services based on Deep Learning technology and automatic learning. These services bring natural language understanding (Amazon Lex), image recognition (Amazon Rekognition) and voice synthesis (Amazon Polly) to your applications. Come discover them during this session through a number of live demos.
AWS Summit Singapore - Get to Know Your Customers - Modern Data ArchitectureAmazon Web Services
Craig Stires, Business Development Manager - Big Data & Analytics, APAC, AWS
Your customers probably want a better experience with your brand. Your different business teams want and need better insights in their decision making. Almost certainly, your finance and operations teams require this to happen at a fraction of the cost of traditional on-premises options. Modern data architectures on AWS help many of our best customers realise all of those goals. Your business data contains critical information about customer behaviours, operational decisions, and many factors that have financial impact on your organisation. Increasingly, this data sits beyond your transactional systems, and is too big, too fast, and too complex for existing systems to handle. AWS Data and Analytics services are designed from our customers' requirements to ingest, store, analyse, and consume information at record-breaking scale. In this session you will learn how these services work together to deliver business automation, enhance customer engagement and intelligence.
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
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.
Learn How to Build a Bot for Voice and Text with Amazon Lex and Amazon Polly ...Amazon Web Services
Learn How to Build a Bot for Voice and Text with Amazon Lex and Amazon Polly.
- Amazon Polly - life-like speech service
- Amazon Lex - enables developer to build conversational chatbots quickly and easily.
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.
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.
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.
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!
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. Join this session to learn more and find out how you get can started with Amazon Polly, today!
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
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
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.
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.
Hands-on with Rekognition, Polly & Lex - Pop-up Loft TLV 2017Amazon Web Services
The AWS Cloud now provides a range of AI services based on Deep Learning technology and automatic learning. These services bring natural language understanding (Amazon Lex), image recognition (Amazon Rekognition) and voice synthesis (Amazon Polly) to your applications. Come discover them during this session through a number of live demos.
AWS Summit Singapore - Get to Know Your Customers - Modern Data ArchitectureAmazon Web Services
Craig Stires, Business Development Manager - Big Data & Analytics, APAC, AWS
Your customers probably want a better experience with your brand. Your different business teams want and need better insights in their decision making. Almost certainly, your finance and operations teams require this to happen at a fraction of the cost of traditional on-premises options. Modern data architectures on AWS help many of our best customers realise all of those goals. Your business data contains critical information about customer behaviours, operational decisions, and many factors that have financial impact on your organisation. Increasingly, this data sits beyond your transactional systems, and is too big, too fast, and too complex for existing systems to handle. AWS Data and Analytics services are designed from our customers' requirements to ingest, store, analyse, and consume information at record-breaking scale. In this session you will learn how these services work together to deliver business automation, enhance customer engagement and intelligence.
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
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.
Learn How to Build a Bot for Voice and Text with Amazon Lex and Amazon Polly ...Amazon Web Services
Learn How to Build a Bot for Voice and Text with Amazon Lex and Amazon Polly.
- Amazon Polly - life-like speech service
- Amazon Lex - enables developer to build conversational chatbots quickly and easily.
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 quick overview, 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.
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!
Improving Customer Experience: Enhanced Customer Insights Using Natural Langu...Amazon Web Services
In this session, we’ll discuss how to utilize natural language processing (NLP) to analyze data sources, such as user sentiments, conversational intent, and social media. Machine learning solutions help us bring deeper insights and relationships in texts to reduce the analysis time from weeks to days. We will highlight how quickly a machine learning-based solution can be deployed. We will dive deep into AWS services, such as AWS Lambda, Amazon SageMaker, Amazon Comprehend (Classification), Topic Modeling, and Amazon Transcribe, to rapidly develop a natural language search and analysis application to meet such requirements. We will also demonstrate how to ingest social media Tweets to generate a sentiment score to engage with the customer more effectively.
MCL331_Building a Virtual Assistant with Amazon Polly and Amazon Lex PollexyAmazon Web Services
Technology advances have enabled people with disabilities to communicate more meaningfully and participate more fully in their daily lives. In this session, we discuss the many challenges for those with special needs and how AWS voice technologies empower this population. In this workshop, participants learn how to build Pollexy (Polly + Lex), a Raspberry Pi, and a mobile-based special needs verbal assistant that lets caretakers schedule audio task prompts and messages both on a recurring schedule and on-demand.
BDA302 Building Intelligent Apps with AWS Machine Learning Language ServicesAmazon Web Services
Amazon brings natural language processing (NLP), automatic speech recognition (ASR), text-to-speech (TTS), and neural machine translation (NMT) technologies within reach of every developer. In this session, learn how you can easily add intelligence to any application with solution-oriented machine learning (ML) services that provide speech, language, and chatbot functionalities. We also share real-world examples of ML in action. See how others are defining and building the next generation of apps that can hear, speak, understand, and interact with the world around us.
Building Chatbots with Amazon Lex I AWS Dev Day 2018AWS Germany
Through Amazon AI services, we learn how to add powerful features like natural language understanding(NLU), automatic speech recognition (ASR), visual search and image recognition, text to speech (TTS), and machine learning (ML) technologies to applications. https://aws.amazon.com/machine-learning/
Amazon brings natural language processing, automatic speech recognition, text-to-speech, and neural machine translation technologies within reach of every developer. In this session, learn how you can easily add intelligence to any application with solution-oriented machine learning (ML) services that provide speech, language, and chatbot functionalities. We also share real-world examples of ML in action. See how others are defining and building the next generation of apps that can hear, speak, understand, and interact with the world around us.
BDA306 An Introduction to Amazon Lex, your Service for Building Voice and Tex...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!
Steve Shirkey, Solutions Architect, ASEAN, AWS
With the launch of several new Machine Learning (ML) services on AWS, now is your chance to learn how to quickly apply ML to solve real-world business problems, no prior ML experience necessary. During this session, you will learn about vision services to analyze your images and video for facial comparison, object detection and detecting text (Amazon Rekognition and Amazon Rekognition Video), building conversational interfaces for chatbots (Amazon Lex), and core language services for converting audio to text (Amazon Transcribe), converting text to speech (Amazon Polly), identifying topics and themes in text (Amazon Comprehend) and translating between two languages (Amazon Translate).
Make your solution see, hear and talk, leveraging artificial intelligence services based on deep learning and neural networks. We will discover three new AI tools from AWS - Lex, Polly and Rekognition; integrated with a physical world device for human interaction and environmental awareness
Speaker: Sunil Mallya, Solutions Architect, AWS Deep Learning
This presentation is focused on building solutions and strategy to solve business or customer engagement challenges. It tells the Amazon Machine Learning story and describes core AWS Artificial Intelligence services such as Polly, Lex and Rekognition can be applied to business problems.
Build Intelligent Apps with Amazon ML - Language Services - BDA302 - Chicago ...Amazon Web Services
Amazon brings natural language processing, automatic speech recognition, text-to-speech, and neural machine translation technologies within reach of every developer. In this session, learn how you can easily add intelligence to any application with solution-oriented machine learning (ML) services that provide speech, language, and chatbot functionalities. We also share real-world examples of ML in action. See how others are defining and building the next generation of apps that can hear, speak, understand, and interact with the world around us.
Building your own chat bot with Amazon Lex - Hebrew WebinarBoaz Ziniman
Amazon Lex is a service for building conversational interfaces into any application using voice and text. The service 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.
During this webinar, we will demonstrate how to get started with Amazon Lex, add conversational interface features to your applications and integrate with text-chat and voice-based interfaces.
Similar to Building a Better Chatbot with Amazon Lex and Polly (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.
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. Converts text
to life-like speech
48 voices 24 languages Low latency,
real time
Fully managed
Amazon Polly: Text-to-Speech
Voice Quality & Pronunciation
1. Automatic, Accurate Text Processing
2. Intelligible and Easy to Understand
3. Add Semantic Meaning to Text
4. Customized Pronunciation
Articles and Blogs
Training Material
Chatbots (Lex)
Public Announcements
3. Amazon Lex
Utterances
Spoken or typed phrases that invoke
your intent
BookHotel
Intents
A goal that the user intends to perform.
Identifies an action in response to
natural language user input
Slot Types and Slots
Represents input data from the user to
fulfill the intent. Can be optional.
Fulfillment
The backend business logic that
needs to run to fulfil the user’s intent
4. How does it Work
Spot
Memory Optimized
Virginia
“I want spot prices for
Memory Optimized
instances in Virginia”
Automatic Speech
Recognition
FindSpotPrices
Memory Optimized
Natural Language
Understanding
Intent/Slot
Model
Utterances
Devops Bot: Jared B
InstanceType Memory Optimized
Region Virginia
“OK, Spot price for Memory
Optimized instances in
Virginia is $0.98”
Polly
Lambda returns: “OK, Spot price
for Memory Optimized instances
in Virginia is $0.98”
Prices
Optional Confirmation
Prompt
Virginia
5. AWS Mobile Hub Integration
Authenticate users
Analyze user behavior
Store and share media
Synchronize data
More ….
Track retention
Conversational Bots
AWS Mobile SDKs
AWS Mobile Hub
6. Time to Build a DevOps Bot
http://bit.ly/2qUkw7h
• Intents, Slots, Utterances
• Lambda
• Mobile Hub Integration
• CloudWatch Metrics