Remove Reference Remove Serverless Remove Software Review
article thumbnail

Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. This time efficiency translates to significant cost savings and optimized resource allocation in the review process.

article thumbnail

Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

Ground truth data in AI refers to data that is known to be factual, representing the expected use case outcome for the system being modeled. Document Section Targeting - Reference specific sections when the information location is relevant - Example: "In Section [X] of [Document Name], what are the steps for [specific process]?"

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Integrating Key Vault Secrets with Azure Synapse Analytics

Apiumhub

We may also review security advantages, key use instances, and high-quality practices to comply with. This integration not only improves security by ensuring that secrets in code or configuration files are never exposed but also improves compliance with regulatory standards. What is Azure Synapse Analytics? notebooks, pipelines).

Azure 89
article thumbnail

Orchestrate generative AI workflows with Amazon Bedrock and AWS Step Functions

AWS Machine Learning - AI

Since Amazon Bedrock is serverless, you don’t have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. We're more than happy to provide further references upon request. We must also include.$

article thumbnail

Serverless and Edge Runtime Part 2

Apiumhub

This is the second post in a two-part series exploring the world of Serverless and Edge Runtime. In the previous post, we got familiar with serverless; the main focus of this post will be the Edge Runtime, where it can be useful, and what its caveats are. Edge, the Location: the concept of running servers closer to our users.

article thumbnail

Deploy DeepSeek-R1 Distilled Llama models in Amazon Bedrock

AWS Machine Learning - AI

Their DeepSeek-R1 models represent a family of large language models (LLMs) designed to handle a wide range of tasks, from code generation to general reasoning, while maintaining competitive performance and efficiency. Review the model response and metrics provided. For more information, refer to the Amazon Bedrock User Guide.

article thumbnail

Serverless and Edge Runtime

Apiumhub

This is the introductory post in a two-part series, exploring the world of Serverless and Edge Runtime. The main focus of this post will be Serverless, while the second one will focus on an alternative, newer approach in the form of Edge Computing. Scalability Of course, going serverless is not only for small projects.