Important note
The most scalable and cost-effective way to generate S3 PJUT events for asynchronously invocating downstream AI workflows via Lambda is to generate an AWS pre-signed URL, and then provide it to your mobile or web application users. Many users can be served at the same time via this approach, and it may increase performance and throughput.
Considering the same region for your AWS AI services and S3 bucket may improve performance and reduce network latency. AWS VPC endpoints can leverage enhanced security without using the public internet. You can store the AWS AI results in an AWS S3 bucket and encrypt the rest to attain better security.
In this section, you learned how to extract text from a scanned document and print the form data out of it. Unlike the other sections, you used the testing feature of a Lambda function by creating a test configuration that includes an event template. In the next section, you will learn about creating a chatbot for organizations and learn how to use it.
Most of the features that are available in Alexa are powered by Amazon Lex. You can easily build a chatbot using Amazon Lex. It uses natural language understanding and automatic speech recognition behind the scenes. An Amazon Lex bot can be created either from the console or via APIs. Its basic requirements are shown in the upcoming diagram.
Some common uses of Amazon Lex include the following:
Next, you will explore the benefits of Amazon Lex.
Some reasons for using Lex include the following:
Next, you’ll get hands-on with Amazon Lex.