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Anthropic Claude 3.5 Sonnet ranks number 1 for business and finance in S&P AI Benchmarks by Kensho

AWS Machine Learning

Sonnet currently ranks at the top of S&P AI Benchmarks by Kensho , which assesses large language models (LLMs) for finance and business. For example, there could be leakage of benchmark datasets’ questions and answers into training data. Anthropic Claude 3.5 Kensho is the AI Innovation Hub for S&P Global. Anthropic Claude 3.5

Finance 123
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LLM-as-a-judge on Amazon Bedrock Model Evaluation

AWS Machine Learning

Amazon Bedrock , a fully managed service offering high-performing foundation models from leading AI companies through a single API, has recently introduced two significant evaluation capabilities: LLM-as-a-judge under Amazon Bedrock Model Evaluation and RAG evaluation for Amazon Bedrock Knowledge Bases. 0]}-{evaluator_model.split('.')[0]}-{datetime.now().strftime('%Y-%m-%d-%H-%M-%S')}"

Metrics 104
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From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 2

AWS Machine Learning

Analyst Notes Database Knowledge base containing reports from Analysts on their interpretation and analyis of economic events. Analyst Notes Database This is asking for interpretation of an event, I will look in Analyst Notes. Refer to this documentation for a detailed example of tool use with the Bedrock Converse API.

APIs 117
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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning

The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. Explore examples to estimate the severity and likelihood of potential events that could be harmful.

APIs 107
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Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions

AWS Machine Learning

The solution uses the following services: Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale. Purina’s solution is deployed as an API Gateway HTTP endpoint, which routes the requests to obtain pet attributes.

APIs 127
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Optimize your machine learning deployments with auto scaling on Amazon SageMaker

AWS Machine Learning

Although you can integrate the model directly into an application, the approach that works well for production-grade applications is to deploy the model behind an endpoint and then invoke the endpoint via a RESTful API call to obtain the inference. However, you can use any other benchmarking tool. large two-core machine.

Benchmark 103
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Enhance performance of generative language models with self-consistency prompting on Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies and Amazon via a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI. A limitation of the approach is its larger computational cost.

APIs 135