AWS re:Invent 2024, our biggest cloud event of the year, in Las Vegas, Nevada, featured keynotes, innovation talks, builder labs, workshops, and tech demos.
Generative artificial intelligence (Gen AI) was again a major focus, with Amazon Web Services (AWS) CEO Matt Garman, AWS Vice President of Data and AI Swami Sivasubramanian, and special guest Amazon CEO Andy Jassy announcing a range of innovations, as well as sharing behind-the-scenes-insights.
Here are some of the key announcements from the event:
1. Amazon Nova foundation models
New Amazon Nova models, available in Amazon Bedrock, can process text, image, and video as prompts. Customers can use Amazon Nova-powered Gen AI applications to understand videos, charts, and documents, or generate multimedia content. Using Amazon Bedrock, customers can easily experiment with and evaluate Amazon Nova models, as well as other foundation models (FMs), to determine the best model for an application.
2. Now available: AWS Trainium2 instances
AWS Trainium2-powered Amazon Elastic Compute Cloud (Amazon EC2)instances, powered by AWS Trainium2 chips, are purpose-built for high-performance deep learning (DL) training of Gen AI models, including large language models (LLMs) and latent diffusion models. A single Trn2 instance combines 16 Trainium2 chips interconnected with ultrafast NeuronLink high-bandwidth.
Trn2 UltraServers—a completely new EC2 offering—use NeuronLink interconnect to connect four Trn2 servers together into one giant server. With new Trn2 UltraServers, customers can scale up their generative AI workloads across 64 Trainium2 chips.
3. Trainium3 chips: designed for high-performance needs of Gen AI workloads
Trainium3, AWS’s next-generation AI chip, will allow customers to build bigger models faster, and deliver superior real-time performance. Trainium3-powered UltraServers are expected to be four times more performant than Trn2 UltraServers. The first Trainium3-based instances will be available in late 2025.
4. New capabilities for Amazon Bedrock and the biggest expansion of models to date
New innovations for Amazon Bedrock will give customers greater flexibility and control to build and deploy production-ready Gen AI faster. These include:
- The broadest selection of fully managed models from leading AI companies
- Access to more than 100 popular, emerging, and specialized models with Amazon Bedrock Marketplace
- New Amazon Bedrock capabilities to help customers more effectively manage prompts at scale
- Two new capabilities for Amazon Bedrock Knowledge Bases
- New Amazon Bedrock Data Automation
5. Amazon Bedrock strengthened with industry-first AI safeguard, new agent capability, and model customization
New capabilities for Amazon Bedrock will help customers prevent factual errors due to hallucinations, orchestrate multiple AI-powered agents for complex tasks, and create smaller, task-specific models that can perform similarly to a large model at a fraction of the cost and latency:
- Automated reasoning checks. The first and only Gen AI safeguard that helps prevent factual errors due to hallucinations using logically accurate and verifiable reasoning.
- Expansion of Amazon Bedrock Agents. Supports multi-agent collaboration, empowering customers to easily build and coordinate specialized agents to execute complex workflows.
- Amazon Bedrock Model Distillation. Model distillation is a technique that transfers the knowledge from a large model to a small model, while retaining the latter’s performance characteristics. This usually requires specialized machine learning (ML) expertise, but with Amazon Bedrock Model Distillation, any customer can now distill their own model with no ML expertise required.
6. New Amazon SageMaker AI capabilities
New innovations for Amazon SageMaker AI can help customers get started faster with popular publicly available models, maximize training efficiency, lower costs, and use their preferred tools to accelerate Gen AI model development. These include three innovations for Amazon SageMaker HyperPod, which helps customers efficiently scale Gen AI model development across thousands of AI accelerators, reducing time to train foundation models by up to 40%.
7. Next generation of Amazon SageMaker to deliver unified platform for data, analytics, and AI
The next generation of Amazon Sagemaker now showcases four new features and capabilities: SageMaker Unified Studio, SageMaker Catalog, SageMaker Lakehouse, and Zero-ETL integrations with SaaS applications. This brings together the capabilities customers need for fast Structured Query Language (SQL) analytics, petabyte-scale big data processing, data exploration and integration, machine learning (ML) model development and training, and Gen AI in one integrated platform.
8. New capabilities and continued momentum for Amazon Q Business
Amazon Q Business is the most capable Gen AI-powered assistant for finding information, gaining insight, and taking action at work. The new capabilities offer customers better insights across Amazon Q Business and Amazon Q in QuickSight, enhance cross-app Gen AI experiences, provide more than 50 actions for popular business applications, and make it easy to automate complex workflows—enabling employees to complete tedious, time-consuming work faster.
9. New enhancements to Amazon Q Developer, the most capable Gen AI assistant for software development
These enhancements to Amazon Q Developer include agents that accelerate unit testing, documentation, and code reviews, and an operational capability that helps operators and developers of all experience levels investigate and resolve operational issues across their AWS environment in a fraction of the time. Amazon Q Developer can speed up software development tasks by up to 80%, already providing the highest reported code acceptance rate of any coding assistant that suggests multi-line code; code security scanning that outperforms leading publicly benchmarkable tools; and high-performing AI agents that autonomously reason and iterate to achieve complex goals.
10. New database capabilities including Amazon Aurora DSQL, the fastest distributed SQL database
New capabilities for Amazon Aurora and Amazon DynamoDB will support customers’ most demanding workloads that need to operate across multiple Regions with strong consistency, low latency, and the highest availability:
- Amazon Aurora DSQL. his new serverless, distributed SQL database enables customers to build applications with 99.999% multi-Region availability, strong consistency, PostgreSQL compatibility, four times faster reads and writes compared to other popular distributed SQL databases, virtually unlimited scalability, and zero infrastructure management.
- Enhancements to Amazon DynamoDB global tables. AWS is now using the same underlying technology leveraged by Aurora DSQL to enhance DynamoDB global tables, adding the option of strong consistency to the highest availability, virtually unlimited scalability, and zero infrastructure management already available in DynamoDB global tables, ensuring customers' multi-Region applications are always reading the latest data without having to change any application code.
11. New data center components to support AI, improve energy efficiency, and boost innovation
AWS expects to begin construction on new data centers with the full set of new components—which combine advances in power, cooling, and hardware—in early 2025 in the U.S. Watch this video and learn more about AWS's new data center components.
Watch the re:Invent 2024 keynotes:
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