Knowledge Bases for #AmazonBedrock now supports advanced RAG capabilities. ☁️🤖🚀 https://go.aws/3W465NQ With Knowledge Bases for Amazon Bedrock you can now write your own chunking code & choose from built-in chunking options such as semantic & hierarchical chunking. With advanced parsing, you can now leverage foundation models provided by Amazon Bedrock to translate complex PDF documents to simple text formats, improving accuracy #AWS #generativeAI
Knowledge Bases for Amazon Bedrock
Great news .... Amazon Bedrock's Knowledge Bases will benefit users by enabling the integration of proprietary information into generative-AI applications. With advanced RAG capabilities, users will be able to write their own chunking code or choose from built-in options, improving data parsing and accuracy. This will facilitate the translation of complex documents to simple text formats, enhancing the overall performance of AI applications. Advanced RAG capabilities in Knowledge Bases enhance accuracy and relevance by integrating real-time data retrieval with generative models. e.g. advanced parsing significantly improves the translation of PDF documents by enabling the extraction of complex data, such as embedded objects, tables, and figures, with higher accuracy and efficiency.
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Senior Data Scientist at Deloitte| Gen AI & RAG Specialist | NVIDIA Supercomputer Certified | Machine Learning | Deep Learning | NLP | Conversational AI
2moI am trying to use a S3 bucket with more than 100 pdf documents with Knowledge base , and getting an error. Does it mean it cannot parse more than 100 documents ? Can we change this limit ? This is not scalable at all.