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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning

Using its enterprise software, FloTorch conducted an extensive comparison between Amazon Nova models and OpenAIs GPT-4o models with the Comprehensive Retrieval Augmented Generation (CRAG) benchmark dataset. FloTorch used these queries and their ground truth answers to create a subset benchmark dataset.

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GraphStorm 0.3: Scalable, multi-task learning on graphs with user-friendly APIs

AWS Machine Learning

With GraphStorm, you can build solutions that directly take into account the structure of relationships or interactions between billions of entities, which are inherently embedded in most real-world data, including fraud detection scenarios, recommendations, community detection, and search/retrieval problems. Specifically, GraphStorm 0.3

APIs 113
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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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Pixtral-12B-2409 is now available on Amazon Bedrock Marketplace

AWS Machine Learning

Overview of Pixtral 12B Pixtral 12B, Mistrals inaugural VLM, delivers robust performance across a range of benchmarks, surpassing other open models and rivaling larger counterparts, according to Mistrals evaluation. Performance metrics and benchmarks Pixtral 12B is trained to understand both natural images and documents, achieving 52.5%

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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 90
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Benchmark and optimize endpoint deployment in Amazon SageMaker JumpStart 

AWS Machine Learning

This post explores these relationships via a comprehensive benchmarking of LLMs available in Amazon SageMaker JumpStart, including Llama 2, Falcon, and Mistral variants. We provide theoretical principles on how accelerator specifications impact LLM benchmarking. Additionally, models are fully sharded on the supported instance.

Benchmark 119
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Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning

These include metrics such as ROUGE or cosine similarity for text similarity, and specific benchmarks for assessing toxicity (Detoxify), prompt stereotyping (cross-entropy loss), or factual knowledge (HELM, LAMA). Refer to Getting started with the API to set up your environment to make Amazon Bedrock requests through the AWS API.