Remove Big data Remove Chatbots Remove Entertainment
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AI: 4 Key Benefits for the Customer Experience

VocalCom

When you think of how artificial intelligence is being used in customer service these days, chatbots may come to mind. Indeed, chatbots have redefined the way in which customers interact with brands, helping consumers find answers more quickly and make purchases more seamlessly. AI may be used to essentially predict human behavior.

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Revolutionizing Communication: Unleashing the Power of the Best Artificial Intelligence Chatbots

SmartKarrot

Understanding the basics of AI chatbots An artificial intelligence chatbot is a computer program designed to converse with users through text-based or voice-based interfaces, using Artificial Intelligence (AI) technologies such as Natural Language Processing (NLP) and Machine Learning (ML).

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Personalize your generative AI applications with Amazon SageMaker Feature Store

AWS Machine Learning

The applications also extend into retail, where they can enhance customer experiences through dynamic chatbots and AI assistants, and into digital marketing, where they can organize customer feedback and recommend products based on descriptions and purchase behaviors.

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Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

AWS Machine Learning

He has over 11 years of experience in developing and leading data science, machine learning, and big data initiatives. Prior to joining AWS, he was consulting customers in various industries such as Automotive, Manufacturing, Telecommunications, Media & Entertainment, Retail and Financial Services.

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Technology is the Enabler not the Disruptor (So Stop Using it as an Excuse)

C3Centricity

Beverage manufacturers are getting into entertainment in a big way. As a great example, think about Red Bull which today is seen more as an entertainment company that just happens to make a drink! Chatbots are providing additional resources to the already overworked customer services departments.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

He is passionate about building secure and scalable AI/ML and big data solutions to help enterprise customers with their cloud adoption and optimization journey to improve their business outcomes. About the authors Ram Vittal is a Principal ML Solutions Architect at AWS.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

In this sample architecture of a chatbot application, there are five trust boundaries where controls are demonstrated, based on how AWS customers commonly build their LLM applications. Your LLM application may have more or fewer definable trust boundaries. Ram Vittal is a Principal ML Solutions Architect at AWS.