On the second day of AWS re:Invent 2024, Dr. Swami Sivasubramanian, vice president of AI and Data at AWS, announced an array of new advancements for Amazon Bedrock, the company’s platform that allows businesses to build generative AI applications. On day one, we saw AWS CEO Matt Garman and Amazon CEO Andy Jassy introduce some new models and capabilities. On Thursday, December 5, Sivasubramanian demonstrated new model capabilities in which AWS is impacting change in their respective industries through generative AI.
The new upgrades aim to provide more flexibility and control to build and deploy generative AI applications faster and more efficiently. All announcements demonstrate AWS’s commitment to model selection and optimization of how estimates are measured. In his insightful keynote, Sivasubramanian emphasized that AWS, with its groundbreaking technology, is not only shaping the present but also laying the groundwork for future innovations to take flight.
Here’s a look at key moments from the keynote:
What’s new on Amazon Bedrock?
Dr. during his keynote speech. Sivasubramanian introduced some new features for Amazon Bedrock. The latest updates include expanded model options, access to over 100 exclusive models through the Amazon Bedrock Marketplace, enhanced prompt management tools, and some new features for knowledge bases (a self-serve online library of information) and data automation. Dr. Sivasubramanian said these features aim to provide flexibility, scalability, and maximum use of data. While other capabilities are in preview, the Amazon Bedrock Marketplace is live. An AWS executive said models from Luma AI, Poolside and Stability AI will soon be added to Amazon Bedrock.
New Amazon SageMaker AI Capabilities
AWS’s service for building and deploying AI models — Amazon SageMaker — got four innovations aimed at making generative AI and machine learning development cost-efficient, fast, and easy to scale. The new innovations focus on helping companies get started quickly with popular models, optimize their training processes and seamlessly integrate with partner AI tools. Features are curated training recipes, flexible training plans, task governance, and integrated partner AI apps.
What these advances mean for customers is that they will get faster and more affordable AI solutions. Businesses can now expect more personalized, efficient and innovative experiences such as smarter chatbots, faster recommendations, and improved automation of daily tasks.
Amazon Bedrock Marketplace
One of the important announcements on Day 2 was the new Amazon Bedrock Marketplace. It is a place that provides access to over 100 popular and exclusive AI models including Mistral Nemo, Falcon RW, etc. Users can choose models that suit their needs, deploy them across scalable AWS infrastructure through fully managed endpoints, and integrate them securely. Using Bedrock’s APIs. It also includes guardrails, agents, and strong security and privacy protections. According to AWS, this marketplace simplifies model discovery, deployment, and integration.
SageMaker HyperPod gets new features
To address the growing demand for AI, AWS has announced some new features for SageMaker HyperPod. These included flexible training plans that allowed for streamlining capacity reservations, saving training weeks and working within budgets and deadlines. On the other hand, Task Governance in SageMaker HyperPod automates the management and prioritization of compute resources, completing high-priority tasks with maximum utility and efficiency. SageMaker also integrates AI apps from partners like Comet and Fiddler, essentially reducing the time spent configuring third-party tools and accelerating the model development lifecycle. These innovations are intended to enhance resource efficiency, reduce development complexity and improve AI deployment speed for customers.
Advanced Gen AI enhancements to Bedrock
Dr. In his keynote speech, Sivasubramanian also presented a suite of innovations that simplify and optimize generative AI development. While prompt caching in API calls helps reuse context, intelligent prompt routing improves response quality and cost-efficiency by directing queries to the best-suited AI model. To address the challenges associated with Retrieval Augmented Generation (RAG), AWS introduced the Kendra Gen AI Index, which integrates with over 40 enterprise data sources for accurate and compelling outputs.
On the other hand, Bedrock Knowledge Base now enables structured data retrieval and use of knowledge graphs through GraphRAG support, allowing for better, more accurate responses to Gen AI applications. AWS also introduced Bedrock Data Automation, which processes unstructured multimodal data to enhance Gen AI insights.
For security and to ensure ethical usage, AWS introduced Bedrock Guardrails that offer customizable security and automated logic checks. Meanwhile, the new multimodal toxicity detection filters out harmful image content.
The author is invited by AWS at AWS re:Invent 2024 in Las Vegas.