Buy with AWS enables you to seamlessly discover and purchase products available in AWS Marketplace from AWS Partner websites using your AWS account.
Amazon SageMaker HyperPod recipes help customers get started with training and fine-tuning popular publicly available foundation models, like Llama 3.1 405B, in just minutes with state-of-the-art performance.
Amazon commits $100M to empower education equity initiatives, enabling socially-minded organizations to create AI-powered digital learning solutions. This aims to reach underserved students globally through innovative platforms, apps, and assistants.
Q Developer empowers non-ML experts to build ML models using natural language, enabling organizations to innovate faster with reduced time to market.
Build responsible AI applications - Safeguard them against harmful text and image content with configurable filters and thresholds.
Amazon Bedrock enhances generative AI data analysis with multimodal processing, graph modeling, and structured querying, accelerating AI application development.
Route requests and cache frequently used context in prompts to reduce latency and balance performance with cost efficiency.
Discover, test, and use over 100 emerging, and specialized foundation models with the tooling, security, and governance provided by Amazon Bedrock.
Unlock efficient large model training with SageMaker HyperPod flexible training plans - find optimal compute resources and complete training within timelines and budgets.
Enable priority-based resource allocation, fair-share utilization, and automated task preemption for optimal compute utilization across teams.
Unifying data silos, Amazon SageMaker Lakehouse seamlessly integrates S3 data lakes and Redshift warehouses, enabling unified analytics and AI/ML on a single data copy through open Apache Iceberg APIs and fine-grained access controls.
Effortlessly analyze operational data in Amazon SageMaker Lakehouse, freeing developers from building custom pipelines and enabling seamless insights extraction.
Manage data and AI assets through a unified catalog, granular access controls, and a consistent policy enforcement. Establish trust via automation - boost productivity and innovation for data teams.
Realize visual traceability of data origins, transformations, and usage - bolstering trust, governance, and discoverability for strategic data-driven decisions.
Unify data engineering, analytics, and generative AI in a streamlined studio with enhanced capabilities of Amazon SageMaker.
Amazon Q Business extends productivity with generative AI-powered workflow automation capability and 50+ actions for enterprise efficiency, enabling seamless task execution across tools like ServiceNow, PagerDuty, and Asana.
New Amazon Q Business capabilities help ISVs integrate with the Amazon Q index to retrieve data from multiple sources through a single API and customize the design of their Amazon Q embedded assistant.