AWS customers and partners convened in New York City on Wednesday, June 10, 2024 for the star of the AWS Summit tour. It’s on the big stage at Javits Center that AWS announced exciting GA and preview capabilities for its cloud products that will allow companies working on AWS environments to build applications faster and with fewer distractions.
This year’s keynote, led by Dr. Matt Wood, VP of AI Products AWS, revealed the cloud giant’s plans to make generative AI more useful and accessible to a wider set of technical users and developer workflows.
AWS announced the addition of its Amazon Q Developer into two new locations to help developers remain in a single environment throughout the development lifecycle, lowering the amount of time spent switching between tools for research, fact checking, and guidance.
The speed of innovation provided by these tools can only be accessed within the AWS cloud environment, and can be used alongside or in addition to business tools like SAP.
Amazon Q Developer is now available in SageMaker Studio, an addition that seeks to speed ML development lifecycles. Within SageMaker Studio JupyterLab, developers will be able to access natural language tools that guide developers through the complicated process of choosing, learning, and troubleshooting ML tools.
The generative AI-based Amazon Q solution, when activated, sits next to the JupyterLab notebook, giving developers direct access to vital ML guidance and suggestions without opening multiple research tabs or switching between applications.
Developers can now also access the Amazon Q tool within their IDE and privately connect company git or S3 repositories for coding suggestions tailored to existing company code and infrastructures.
Amazon Q can analyze company assets for coding, API, or tooling suggestions that best meet the needs of the developer. Private access to company code means that Amazon will not use the company data to train their models, and admins have access to periodically update Amazon Q with the most recent company code.
Two features were announced in preview for Amazon Bedrock: administrators can now turn on memory retention for Anthropic’s Claude 3 Sonnet or Haiku and code interpretation.
When memory retention is enabled, agents will remember context from one interaction to another, allowing developers to use fewer prompts and build upon previous work without replication.
Code interpretation allows agents to build visualizations or analyses based on the data compiled by the agent, meaning that developers don’t need to export, switch tools, and import data to make agent-generated information fit for business consumption.
AI assistants within Amazon tools are meant to make work easier for all business users. The apps announced at AWS Summit NYC reduce development time for engineering teams by lowering the barrier to access from writing code to writing natural language prompts. This effectively moves much of the app-building work out of the hands of developers and into those of business and technical users without direct coding knowledge.
Amazon Q Apps was released under general availability to Amazon Q Business Pro users. These companies can use the information in their Amazon Q Business Pro accounts to build customized apps to speed processes across the organization and by users who are less technical but can provide detailed prompts. These apps can be saved and published within the App Library for general use.
Similarly, AWS App Studio was released in preview. The App Studio is a low-code environment that technical business users can leverage to build applications that draw from business data and code. Meant for business users like project managers, data analysts, and enterprise architects, App Studio provides a platform for these users to make applications without requiring more out of already-overleveraged development teams.
For those thinking about moving from ECC to AWS cloud services, EPI-USE can provide previews of the AWS services listed above and many more within the EPI-USE SHIP program. As part of your SHIP package, you can test AI tools within AWS cloud production-like environments, expand and test modern SAP services in sandboxes, and see how your company can benefit from modernization built on the AWS cloud. Click below to find out more.