control

In: Artificial Intelligence

Managing access control in enterprise machine learning (ML) environments presents significant challenges, particularly when multiple teams share Amazon SageMaker AI resources within a single Amazon Web Services (AWS) account. Although Amazon SageMaker Studio provides user-level execution roles, this approach becomes unwieldy as organizations scale and team sizes grow. Refer toContinue Reading

In: Artificial Intelligence

In the context of distributed systems and microservices architecture, orchestrating communication between diverse components presents significant challenges. However, with the launch of Amazon Bedrock Agents, the landscape is evolving, offering a simplified approach to agent creation and seamless integration of the return of control capability. In this post, we exploreContinue Reading

In: Technology

Researchers at the Advanced Science Research Center at the CUNY Graduate Center (CUNY ASRC) and at Florida International University report in the journal Science their insights on the emerging field of complex frequencies excitations, a recently introduced scheme to control light, sound and other wave phenomena beyond conventional limits. BasedContinue Reading

In: Artificial Intelligence

Amazon SageMaker Studio provides a single web-based visual interface where different personas like data scientists, machine learning (ML) engineers, and developers can build, train, debug, deploy, and monitor their ML models. These personas rely on access to data in Amazon Simple Storage Service (Amazon S3) for tasks such as extractingContinue Reading

In: Artificial Intelligence

Several factors can make remediating security findings challenging. First, the sheer volume and complexity of findings can overwhelm security teams, leading to delays in addressing critical issues. Findings often require a deep understanding of AWS services and configurations and require many cycles for validation, making it more difficult for lessContinue Reading

In: Artificial Intelligence

Knowledge Bases for Amazon Bedrock is a fully managed service that helps you implement the entire Retrieval Augmented Generation (RAG) workflow from ingestion to retrieval and prompt augmentation without having to build custom integrations to data sources and manage data flows, pushing the boundaries for what you can do inContinue Reading

In: Artificial Intelligence

In November 2023, we announced Knowledge Bases for Amazon Bedrock as generally available. Knowledge bases allow Amazon Bedrock users to unlock the full potential of Retrieval Augmented Generation (RAG) by seamlessly integrating their company data into the language model’s generation process. This feature allows organizations to harness the power ofContinue Reading