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Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets

AWS Machine Learning

The steps involved are as follows: The financial analyst poses questions via a platform such as chatbots. Large language models – The large language models (LLMs) are available via Amazon Bedrock, SageMaker JumpStart, or an API. The agent answers the question “ What is Amazon’s net loss for fiscal year ending in December 2022?

Marketing 110
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Chatbot: Complete Guide

JivoChat

Chatbots have become a success around the world, and nowadays are used by 58% of B2B companies and 42% of B2C companies. In 2022 at least 88% of users had one conversation with chatbots. There are many reasons for that, a chatbot is able to simulate human interaction and provide customer service 24h a day.

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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning

medium instance to demonstrate deploying LLMs via SageMaker JumpStart, which can be accessed through a SageMaker-generated API endpoint. You can request service quota increases through the console, AWS Command Line Interface (AWS CLI), or API to allow access to those additional resources. We use an ml.t3.medium