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Provide live agent assistance for your chatbot users with Amazon Lex and Talkdesk cloud contact center

AWS Machine Learning

The integration of Amazon Lex with Talkdesk cloud contact center is inspired by WaFd Bank (WaFd)’s digital innovation journey to enhance customer experience. For example, the following figure shows screenshots of a chatbot transitioning a customer to a live agent chat (courtesy of WaFd Bank).

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Create powerful self-service experiences with Amazon Lex on Talkdesk CX Cloud contact center

AWS Machine Learning

In the second part of this series, we describe how to use the Amazon Lex chatbot UI with Talkdesk CX Cloud to allow customers to transition from a chatbot conversation to a live agent within the same chat window. The bank has invested in a digital transformation of its contact center to provide exceptional service to its clients.

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Build generative AI chatbots using prompt engineering with Amazon Redshift and Amazon Bedrock

AWS Machine Learning

Amazon Bedrock offers a choice of high-performing foundation models from leading AI companies, including AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon, via a single API. Prompt engineering makes generative AI applications more efficient and effective.

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ChatGPT, GPT-3, and Your Conversational AI Solution

Creative Virtual

In some cases, one might be willing to accept a certain risk in exchange for very efficiently making large chunks of information available to a chatbot. However its knowledge is not limitless and so on its own it will not have large parts of the information needed for specific chatbot use cases.

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Zero-shot and few-shot prompting for the BloomZ 176B foundation model with the simplified Amazon SageMaker JumpStart SDK

AWS Machine Learning

Prompt engineering for zero-shot and few-shot NLP tasks on BLOOM models Prompt engineering deals with creating high-quality prompts to guide the model towards the desired responses. Prompt engineering can greatly improve the performance of zero-shot and few-shot learning models. He is currently a Senior Adviser of CITIC CLSA.

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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

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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. What Is a Chatbot?