APIs Benchmark Document 
AWS Machine Learning
AUGUST 2, 2024
adds new APIs to customize GraphStorm pipelines: you now only need 12 lines of code to implement a custom node classification training loop. For more details about how to run graph multi-task learning with GraphStorm, refer to Multi-task Learning in GraphStorm in our documentation. introduces refactored graph ML pipeline APIs.
AWS Machine Learning
JUNE 12, 2024
In today’s data-driven business landscape, the ability to efficiently extract and process information from a wide range of documents is crucial for informed decision-making and maintaining a competitive edge. The Anthropic Claude 3 Haiku model then processes the documents and returns the desired information, streamlining the entire workflow.
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AWS Machine Learning
AUGUST 13, 2024
The healthcare industry generates and collects a significant amount of unstructured textual data, including clinical documentation such as patient information, medical history, and test results, as well as non-clinical documentation like administrative records. Lastly, the Lambda function stores the question list in Amazon S3.
AWS Machine Learning
MAY 2, 2024
In September of 2023, we announced the launch of Amazon Titan Text Embeddings V1, a multilingual text embeddings model that converts text inputs like single words, phrases, or large documents into high-dimensional numerical vector representations. In this benchmark, 33 different text embedding models were evaluated on the MTEB tasks.
AWS Machine Learning
JUNE 25, 2024
Jamba-Instruct is built by AI21 Labs, and most notably supports a 256,000-token context window, making it especially useful for processing large documents and complex Retrieval Augmented Generation (RAG) applications. Prompt guidance for Jamba-Instruct can be found in the AI21 model documentation.
AWS Machine Learning
SEPTEMBER 12, 2024
You can use the BGE embedding model to retrieve relevant documents and then use the BGE reranker to obtain final results. On Hugging Face, the Massive Text Embedding Benchmark (MTEB) is provided as a leaderboard for diverse text embedding tasks. It currently provides 129 benchmarking datasets across 8 different tasks on 113 languages.
AWS Machine Learning
NOVEMBER 22, 2023
When a customer has a production-ready intelligent document processing (IDP) workload, we often receive requests for a Well-Architected review. To follow along with this post, you should be familiar with the previous posts in this series ( Part 1 and Part 2 ) and the guidelines in Guidance for Intelligent Document Processing on AWS.
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