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Natural Language Processing (NLP): Unlocking Inclusivity and Equitable Futures in Capital Infrastructure Planning

Unite.AI

Natural Language Processing (NLP) and Artificial Intelligence (AI) emerge as a powerful tools to revolutionize capital infrastructure planning, foster inclusivity, and drive an equitable future by engaging communities in decision-making.

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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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Synthflow AI: The Ultimate Tool for Automating Your Business Calls

Analytics Vidhya

Introduction Conversational AI has emerged as a transformative technology in recent years, fundamentally changing how businesses interact with customers.

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The Comparison: Perplexity AI vs ChatGPT

Analytics Vidhya

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

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Ernie Bot vs. ChatGPT: A Comparative Analysis of AI-Language Models

Analytics Vidhya

The world of artificial intelligence and natural language processing is continuously evolving, with innovative language models being developed to better understand and interact with human language. Two such language models are Baidu’s Ernie Bot and OpenAI’s ChatGPT.

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How conversational AI can transform IT support

IBM Journey to AI blog

That was, until the introduction of AI chatbots for business emerged on the IT landscape. How Watson Assistant can help IBM Watson Assistant is a holistic SaaS solution for creating AI-enabled conversational experiences.

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Amazon trains 980M parameter LLM with ’emergent abilities’

AI News

The researchers trained models of various sizes on up to 100,000 hours of public domain speech data to see if they would observe the same performance leaps that occur in natural language processing models once they grow past a certain scale. The researchers plan further work to identify optimal model size for emergent abilities.

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