Top 3 Announcements from AWS re:Invent 2023

Top 3 Announcements from AWS re:Invent 2023

I once again had the privilege to travel to AWS re:Invent, the annual conference in Las Vegas, together with Buzzcloud! 

This year’s re:Invent was heavily focused on generative AI and machine learning, and I couldn’t be happier about it. Together with tens of thousands of cloud computing experts and fans we got the opportunity to take part in and experience tons of interesting sessions, discussions, keynotes, workshops, demos and much more.

Every year during the conference, AWS announces a bunch of new awesome tools and services, and this year was no different. In this article, I will share my top 3 news from AWS re:Invent.

1. Powerful New Capabilities for Amazon Bedrock

Amazon Bedrock is a fully managed service that offers foundational models that can be used and customized to easily build and deploy generative AI applications. The foundation models are offered via a single API, and since it is a managed service, there is no need to manage any infrastructure on your own.

Along with announcing expanded choices for models, AWS also announced the possibility to put guardrails around your models. The guardrails assess user inputs and model responses based on the policies that you provide to ensure that your AI-powered apps adhere to data privacy and responsible AI standards based on your specific use case. For example, you can use the guardrails to safeguard the context of your application, restrict undesirable topics or filter harmful content for a relevant and safe user experience.

Additionally, model evaluation for Bedrock is now available in preview. It offers a choice of human evaluation or automatic evaluation based on predefined or custom metrics to evaluate, compare and choose the best models for your use cases.

2. New AWS Trainium Chip for AI Models

During the conference, a second generation of the custom-built Trainium chip was announced. Trainium is a family of processors built by AWS for training models, designed to enhance performance and efficiency. The new Trianinum2 has three times the memory as the first chip, and can train models four times faster than its predecessor.

Together with the other announcements, AWS demonstrates a deep understanding of the advancements and needs in the field of GenAI and ML, and they showcase a commitment to provide the best tools possible for the users to accelerate the training of models as well as building and managing their AI applications.

3. Amazon Q

The big highlight of this year was Amazon Q: the generative AI-powered assistant designed for work that can be tailored to your business, built with privacy and security in mind. It was announced by Adam Selipsky, CEO of AWS, during his keynote speech. Amazon Q can be accessed while on the AWS management console, in developer environments and other third-party apps like Slack. It comes with connectivity to over 40 enterprise systems, and you can even create an application with Amazon Q crawling the Internet itself – imagine the possibilities!

Amazon Q is similar to Microsoft’s Copilot, Google’s Duet AI and Dropbox’s Dash. It uses Amazon Bedrock and integrates multiple AI systems, apart from some of the competing tools that are built on a singular large language model. The possibilities and potential of using Amazon Q within your applications are virtually endless – it can connect to your business systems and identify documentation or features that needs updating, add tasks to the backlog, generate test cases for your code, answer general questions about your business, users and applications, troubleshoot lambda functions, be used to filter and search in AWS Quicksight or give expert assistance when coding inside your IDE. Q also integrates to Amazon Connect, the customer service platform that helps agents solve support requests.

You can try Amazon Q for yourself by simply logging into an AWS account in your organization and clicking on the icon in the far right sidebar, or test it in your IDE by installing the toolkit.

Amazon Q is priced at $20/month per user using the Business plan, and $25/month per user using the Builders plan. Some capabilities are free during the preview period. Read more about the pricing here.

I am eager to explore what’s possible with Q and compare it to its competitors.

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