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Build a Conference Call with the Nexmo Voice API and ASP.NET Core

Nexmo

This is the sixth tutorial on how to use Voice APIs with ASP.NET series. In today’s tutorial, we will learn how to setup a conference call so multiple people can join the same call. A Nexmo account, which you can sign up for here. To use The Nexmo Voice API , we need to create a voice application. Configuration.

APIs 91
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Build a Conference Call with the Nexmo Voice API and ASP.NET Core

Nexmo

This is the sixth tutorial on how to use Voice APIs with ASP.NET series. In today’s tutorial, we will learn how to setup a conference call so multiple people can join the same call. A Nexmo account, which you can sign up for here. To use The Nexmo Voice API , we need to create a voice application. Configuration.

APIs 91
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Build a Conference Call with the Nexmo Voice API and Ruby on Rails

Nexmo

In this walkthrough, we are going to create a Ruby on Rails conference call application that utilizes the Nexmo Voice API. Within the Nexmo documentation, a conference call is also referred to as a conversation , and we will be using these terms interchangeably. To work through this tutorial, you will need a Nexmo account.

APIs 81
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Build a Conference Call with the Nexmo Voice API and Ruby on Rails

Nexmo

In this walkthrough, we are going to create a Ruby on Rails conference call application that utilizes the Nexmo Voice API. Within the Nexmo documentation, a conference call is also referred to as a conversation , and we will be using these terms interchangeably. To work through this tutorial, you will need a Nexmo account.

APIs 81
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Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Solution overview Our solution implements a verified semantic cache using the Amazon Bedrock Knowledge Bases Retrieve API to reduce hallucinations in LLM responses while simultaneously improving latency and reducing costs. The function checks the semantic cache (Amazon Bedrock Knowledge Bases) using the Retrieve API.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning

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

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Streamline RAG applications with intelligent metadata filtering using Amazon Bedrock

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, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.