Remove Analysis Remove APIs Remove Metrics
article thumbnail

Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. API Gateway also provides a WebSocket API. Incoming requests to the gateway go through this point.

article thumbnail

Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning

All of this data is centralized and can be used to improve metrics in scenarios such as sales or call centers. For integration between services, we use API Gateway as an event trigger for our Lambda function, and DynamoDB as a highly scalable database to store our customer details.

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

LLM-as-a-judge on Amazon Bedrock Model Evaluation

AWS Machine Learning

This approach allows organizations to assess their AI models effectiveness using pre-defined metrics, making sure that the technology aligns with their specific needs and objectives. Expert analysis : Data scientists or machine learning engineers analyze the generated reports to derive actionable insights and make informed decisions.

Metrics 88
article thumbnail

Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning

How do Amazon Nova Micro and Amazon Nova Lite perform against GPT-4o mini in these same metrics? Amazon Bedrock APIs make it straightforward to use Amazon Titan Text Embeddings V2 for embedding data. Vector database FloTorch selected Amazon OpenSearch Service as a vector database for its high-performance metrics.

article thumbnail

Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning

Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics. Evaluation, on the other hand, involves assessing the quality and relevance of the generated outputs, enabling continual improvement.

article thumbnail

How Formula 1® uses generative AI to accelerate race-day issue resolution

AWS Machine Learning

During these live events, F1 IT engineers must triage critical issues across its services, such as network degradation to one of its APIs. This impacts downstream services that consume data from the API, including products such as F1 TV, which offer live and on-demand coverage of every race as well as real-time telemetry.

APIs 69
article thumbnail

Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing FMs from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

APIs 114