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Conversational AI use cases for enterprises

IBM Journey to AI blog

Beyond the simplistic chat bubble of conversational AI lies a complex blend of technologies, with natural language processing (NLP) taking center stage. This sophisticated foundation propels conversational AI from a futuristic concept to a practical solution. billion by 2030.

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Conversation AI: What it is and top use cases

AssemblyAI

Ninety percent of contact centers handle calls faster and more efficiently after implementing a conversation AI tool. And, with recent advances in AI technology, the quality of conversation AI tools is rapidly increasing, making their impact even more significant. What is Conversation AI?

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Top AI models for conversation intelligence

AssemblyAI

Many teams are turning to conversation intelligence to help them achieve these goals.    In this article, we cover what exactly conversation intelligence is and why conversation intelligence is important before exploring the top use cases for AI models in conversation intelligence.

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AI courses to boost your skills and stay ahead

AI News

The course covers the requirements elicitation process for AI applications and teaches participants how to work closely with data scientists and machine learning engineers to ensure that AI projects meet business goals. For business analysts, the course provides essential skills to guide AI initiatives that deliver real business value.

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GitLab Introduces Duo Chat: A Conversational AI Tool for Productivity

Marktechpost

To address this, GitLab has introduced a new tool called Duo Chat, which aims to simplify the developer experience by integrating conversational AI into the existing workflow. The post GitLab Introduces Duo Chat: A Conversational AI Tool for Productivity appeared first on MarkTechPost.

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The Comparison: Perplexity AI vs ChatGPT

Analytics Vidhya

While ChatGPT, developed by OpenAI, stands as a titan in conversational AI, “Perplexity” pertains more to a performance metric used in evaluating language models. Introduction In artificial intelligence, particularly in natural language processing, two terms often come up: Perplexity and ChatGPT.

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Generative AI use cases for the enterprise

IBM Journey to AI blog

The quality of outputs depends heavily on training data, adjusting the model’s parameters and prompt engineering, so responsible data sourcing and bias mitigation are crucial. Imagine training a generative AI model on a dataset of only romance novels. Existing content can be reimagined and edited using AI tools.