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Protect sensitive data in RAG applications with Amazon Bedrock

AWS Machine Learning

For more information, see Redacting PII entities with asynchronous jobs (API). The query is then forwarded using a REST API call to an Amazon API Gateway endpoint along with the access tokens in the header. The user query is sent using an API call along with the authentication token through Amazon API Gateway.

APIs 90
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How healthcare payers and plans can empower members with generative AI

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a unified API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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Build a contextual chatbot application using Knowledge Bases for Amazon Bedrock

AWS Machine Learning

For example, a chatbot could suggest products that match a shopper’s preferences and past purchases, explain details in language adapted to the user’s level of expertise, or provide account support by accessing the customer’s specific records. It also supports source attribution and short-term memory needed for RAG applications. Choose Next.

Chatbots 127
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2022H2 Amazon Textract launch summary

AWS Machine Learning

This is why we launched Amazon Textract in 2019 to help you automate your tedious document processing workflows powered by AI. The Analyze Lending feature in Amazon Textract is a managed API that helps you automate mortgage document processing to drive business efficiency, reduce costs, and scale quickly.

APIs 117
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How to Handle Handset Input (DTMF) From a Phone Call in ASP.NET Core

Nexmo

In this tutorial, we’re going to be using the Vonage Voice API to learn how to quickly snap the former (DTMF) into our ASP.NET core applications. Collecting DTMF from a user over a PSTN call will involve the following: Setting up a Vonage API Account if you don’t have one. A Vonage API account.

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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

In the following example, for an LLM to answer the question correctly, it needs to understand the table row represents location and the column represents year, and then extract the correct quantity (total amount) from the table based on the asked location and year: Question : What was the Total Americas amount in 2019? He received his Ph.D.

Finance 123
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Detect fraud in mobile-oriented businesses using GrabDefence device intelligence and Amazon Fraud Detector

AWS Machine Learning

From the combined industry experience, the solution team believes that many of the modus operandi in a mobile environment is driven by fraudsters having tools and methods to create fake accounts at scale and bypass a platform’s security checks on the device, thereby enabling them to exploit the platform for large returns.

APIs 94