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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. NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately.

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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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Accelerate deep learning model training up to 35% with Amazon SageMaker smart sifting

AWS Machine Learning Blog

In today’s rapidly evolving landscape of artificial intelligence, deep learning models have found themselves at the forefront of innovation, with applications spanning computer vision (CV), natural language processing (NLP), and recommendation systems. K Lokesh Kumar Reddy is a Senior engineer in the Amazon Applied AI team.

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Machine Learning and Language (ML²) at CDS: Moving NLP Forward

NYU Center for Data Science

It’s a pivotal time in Natural Language Processing (NLP) research, marked by the emergence of large language models (LLMs) that are reshaping what it means to work with human language technologies. Building on this momentum is a dynamic research group at the heart of CDS called the Machine Learning and Language (ML²) group.

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Top 6 NLP Language Models Transforming AI In 2023

Topbots

BERT by Google Summary In 2018, the Google AI team introduced a new cutting-edge model for Natural Language Processing (NLP) – BERT , or B idirectional E ncoder R epresentations from T ransformers. This model marked a new era in NLP with pre-training of language models becoming a new standard. What is the goal?

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The Rise of ChatGPT: A New Era of Artificial Intelligence

Becoming Human

Machine Learning and Deep Learning One of the key components of the development of ChatGPT is machine learning. Machine learning is a process that involves training artificial neural networks with large amounts of data so that they can learn to recognize patterns and make predictions based on that data.

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Using AI-Mechanized Hyperautomation for Organizational Decision Making

Unite.AI

In the modern business context, hyperautomation is a technological extrapolation to amplify the enterprise digital journey by accelerating crucial innovation initiatives, AI adoption, and driving digital decision-making. Simply put, it is a superior iteration of intelligent automation. This shift is expected to become the norm by 2024.