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Amazon Bedrock Flows is now generally available with enhanced safety and traceability

AWS Machine Learning - AI

Seamless integration of latest foundation models (FMs), Prompts, Agents, Knowledge Bases, Guardrails, and other AWS services. Flexibility to define the workflow based on your business logic. Reduced time and effort in testing and deploying AI workflows with SDK APIs and serverless infrastructure.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

When users pose questions through the natural language interface, the chat agent determines whether to query the structured data in Amazon Athena through the Amazon Bedrock IDE function, search the Amazon Bedrock knowledge base, or combine both sources for comprehensive insights.

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Boost productivity by using AI in cloud operational health management

AWS Machine Learning - AI

The assistant can filter out irrelevant events (based on your organization’s policies), recommend actions, create and manage issue tickets in integrated IT service management (ITSM) tools to track actions, and query knowledge bases for insights related to operational events. It has several key components.

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Empowering everyone with GenAI to rapidly build, customize, and deploy apps securely: Highlights from the AWS New York Summit

AWS Machine Learning - AI

Amazon Q can also help employees do more with the vast troves of data and information contained in their company’s documents, systems, and applications by answering questions, providing summaries, generating business intelligence (BI) dashboards and reports, and even generating applications that automate key tasks.

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Asure’s approach to enhancing their call center experience using generative AI and Amazon Q in Quicksight

AWS Machine Learning - AI

Furthermore, by integrating a knowledge base containing organizational data, policies, and domain-specific information, the generative AI models can deliver more contextual, accurate, and relevant insights from the call transcripts.

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The Good and the Bad of Databricks Lakehouse Platform

Altexsoft

Here are four main applications of the platform across industries: data warehousing — SQL queries and business intelligence (BI) at scale; data engineering — building and maintaining data pipelines , running ETL and ELT workloads; data streaming and real-time analytics , and data science and machine learning projects.

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Transforming credit decisions using generative AI with Rich Data Co and AWS

AWS Machine Learning - AI

It aims to boost team efficiency by answering complex technical queries across the machine learning operations (MLOps) lifecycle, drawing from a comprehensive knowledge base that includes environment documentation, AI and data science expertise, and Python code generation.