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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning

Knowledge Bases for Amazon Bedrock automates synchronization of your data with your vector store, including diffing the data when it’s updated, document loading, and chunking, as well as semantic embedding. It then employs a language model to generate a response by considering both the retrieved documents and the original query.

APIs 112
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Top 10 Auto Dialer Software in 2024 for Efficient Sales Teams

JustCall

Automation features and open API: An auto dialer offers open APIs so your developers can- – Build automation workflows for call logging, – Build workflows for notes logging – Help with reporting and analytics tasks (i.e., Open API for custom integrations and workflows. Reporting and analytics tools.

Sales 52
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Testing times: testingRTC is the smart, synchronized, real-world scenario WebRTC testing solution for the times we live in.

Spearline

Consequently, no other testing solution can provide the range and depth of testing metrics and analytics. And testingRTC offers multiple ways to export these metrics, from direct collection from webhooks, to downloading results in CSV format using the REST API. Happy days! You can check framerate information for video here too.

Scripts 98
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Build an image search engine with Amazon Kendra and Amazon Rekognition

AWS Machine Learning

Using architecture diagrams as an example, the solution needs to search through reference links and technical documents for architecture diagrams and identify the services present. Therefore, users without ML expertise can enjoy the benefits of a custom labels model through an API call, because a significant amount of overhead is reduced.

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Build a powerful question answering bot with Amazon SageMaker, Amazon OpenSearch Service, Streamlit, and LangChain

AWS Machine Learning

A small number of similar documents (typically three) is added as context along with the user question to the “prompt” provided to another LLM and then that LLM generates an answer to the user question using information provided as context in the prompt. Chunking of knowledge base documents. Implementing the question answering task.

APIs 77
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­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

Apache Iceberg is an open table format for very large analytic datasets. It manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. put_record API to ingest individual records or to handle streaming sources.

Scripts 73
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Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

AWS Machine Learning

Homomorphic encryption is a new approach to encryption that allows computations and analytical functions to be run on encrypted data, without first having to decrypt it, in order to preserve privacy in cases where you have a policy that states data should never be decrypted. The following figure shows both versions of these patterns.

Scripts 95