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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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Alan Ranger, VP of Marketing at Cognigy – Interview Series

Unite.AI

Cognigy provides AI-driven solutions to enhance customer service experiences across industries. Cognigy's AI Agents leverage a leading Conversational AI platform, offering features such as intelligent IVR, smart self-service, and agent assist functionalities. Key technological breakthroughs behind the Cognigy.AI

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AI Decoded: Demystifying Large Language Models, the Brains Behind Chatbots

NVIDIA

Editor’s note: This post is part of our AI Decoded series , which aims to demystify AI by making the technology more accessible, while showcasing new hardware, software, tools and accelerations for RTX PC and workstation users. If AI is having its iPhone moment, then chatbots are one of its first popular apps. and online.

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This AI Paper Reviews the Evolution of Large Language Model Training Techniques and Inference Deployment Technologies Aligned with this Emerging Trend

Marktechpost

In Large Language Models (LLMs), models like ChatGPT represent a significant shift towards more cost-efficient training and deployment methods, evolving considerably from traditional statistical language models to sophisticated neural network-based models. Check out the Paper.

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NVIDIA Releases NIM Microservices to Safeguard Applications for Agentic AI

NVIDIA

Central to the orchestration of the microservices is NeMo Guardrails, part of the NVIDIA NeMo platform for curating, customizing and guardrailing AI. NeMo Guardrails helps developers integrate and manage AI guardrails in large language model (LLM) applications.

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How AI Chatbots Mimic Human Behavior: Insights from Multi-Turn Evaluations of LLMs

Marktechpost

In summary, the framework employed a better multi-turn assessment technique than a single-turn approach to evaluating anthropomorphic behaviors in conversational AI. The results identified relationship-building behaviors that evolved with dialogue. Also,feel free to follow us on Twitter and dont forget to join our 75k+ ML SubReddit.

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Enterprise LLM APIs: Top Choices for Powering LLM Applications in 2024

Unite.AI

This move places Anthropic in the crosshairs of Fortune 500 companies looking for advanced AI capabilities with robust security and privacy features. In this evolving market, companies now have more options than ever for integrating large language models into their infrastructure.

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