AWS News Blog
Category: Artificial Intelligence
Use Amazon Q Developer to build ML models in Amazon SageMaker Canvas
Q Developer empowers non-ML experts to build ML models using natural language, enabling organizations to innovate faster with reduced time to market.
Amazon Bedrock Guardrails now supports multimodal toxicity detection with image support (preview)
Build responsible AI applications – Safeguard them against harmful text and image content with configurable filters and thresholds.
New Amazon Bedrock capabilities enhance data processing and retrieval
Amazon Bedrock enhances generative AI data analysis with multimodal processing, graph modeling, and structured querying, accelerating AI application development.
Reduce costs and latency with Amazon Bedrock Intelligent Prompt Routing and prompt caching (preview)
Route requests and cache frequently used context in prompts to reduce latency and balance performance with cost efficiency.
Amazon Bedrock Marketplace: Access over 100 foundation models in one place
Discover, test, and use over 100 emerging, and specialized foundation models with the tooling, security, and governance provided by Amazon Bedrock.
Meet your training timelines and budgets with new Amazon SageMaker HyperPod flexible training plans
Unlock efficient large model training with SageMaker HyperPod flexible training plans – find optimal compute resources and complete training within timelines and budgets.
Maximize accelerator utilization for model development with new Amazon SageMaker HyperPod task governance
Enable priority-based resource allocation, fair-share utilization, and automated task preemption for optimal compute utilization across teams.
Amazon SageMaker Lakehouse and Amazon Redshift supports zero-ETL integrations from applications
Simplify data replication and ingestion from applications such as Salesforce, SAP, ServiceNow, and Zendesk, to Amazon SageMaker Lakehouse and Amazon Redshift.