Amazon Boosts Code Whisperer, AI, And ML

(CTN News) – On Tuesday, Amazon announced updates and additions to its Amazon AI services suite, including a machine learning-based coding platform called Code Whisperer that’s easier to use.

In spite of the fact that Amazon Code Whisperer is still in preview, RPA2AI Research analyst Kashyap Kompella believes this system and AI coding assistants like it will increase productivity for software developers and make coding more accessible to non-technical and semi-technical enterprise users.

It’s likely that Code Whisperer will face the same challenges as Github’s Copilot, and the contentious issue of using open source code as training data for machine learning models must be resolved,” Kompella said.

Security, bugs, obtaining support when an enterprise can’t fix a problem on its own, and abandoning support for some open source products are among the challenges of using open source code for AI models.

As part of its re:Invent user conference this week, AWS announced various features and product upgrades.

Mortgage lending automation

Amazon Textract Analyze Lending is a new loan processing tool for its Textract document text extraction system.

With the lending tool, mortgage companies can automate the classification and extraction of mortgage loan data, which can include W2 forms, pay stubs, and bank and tax statements.

PennyMac, a national home mortgage lender, is one of the early users of Amazon Textract Analyze Lending and it is said to have been able to process a 5,000-word mortgage application in minutes instead of hours, according to AWS.

Similar technologies have become available for other markets to fill in labor gaps and move people out of repetitive tasks, said Matt Mullen, an analyst at Deep Analysis.

In Mullen’s opinion, Texttract Analyze Lending looks particularly interesting because it recognizes the need for specific industry solutions that are vertically focused, which is a unique feature.

Updates to Amazon Code Whisperer AI

As part of Amazon Code Whisperer, originally introduced in June, there is now support for the AWS Builder ID authentication system. This enables AI developers to securely sign on with their email address for their integrated development environment with the AWS Toolkit.

In addition to the TypeScript and C# programming languages, Code Whisperer now supports Python as well, which accelerates the development of code, according to AWS. As of now, Code Whisperer doesn’t support Python, Java, or JavaScript anymore.

Additionally, the platform will now provide code recommendations for some of the most widely used AWS services, including Amazon Elastic Compute, Lambda, and  Simple Storage System (S3).

It has been announced that Amazon has made the administration of  Code Whisperer easier by adding the system to the AWS Management Console. This means that any authorized AWS administrator can enable the system for their organization using the AWS Management Console.

Features of Amazon’s artificial intelligence (AI)

As part of another evolution of one of its existing systems, Amazon Web Services has added a new capability to its Amazon Kendra enterprise search service. This capability allows tabular searches in HTML documents.

It is now possible to find and extract precise answers from HTML tables using natural language by using natural language processing.

According to Amazon Web Services, this capability addresses the widespread problem of finding information and revealing insights from unstructured datasets, such as HTML tables, that require pulling information from two-dimensional formats such as rows and columns in order to help identify relevant insights.

Meanwhile, with its call center system updates, the vendor also introduced Amazon Transcribe Call Analytics, an addition to Amazon Transcribe, the tech giant’s automatic speech recognition service.

AWS said the new tool would enhance the customer’s experience by providing real-time conversation insights, identifying call sentiment, and automatically generating call summaries that will eliminate the need for call center agents to take notes during conversations.

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