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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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Google DeepMind Researchers Propose Matryoshka Quantization: A Technique to Enhance Deep Learning Efficiency by Optimizing Multi-Precision Models without Sacrificing Accuracy

Marktechpost

Quantization is a crucial technique in deep learning for reducing computational costs and improving model efficiency. Large-scale language models demand significant processing power, which makes quantization essential for minimizing memory usage and enhancing inference speed.

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The CX Power Duo: How Humans and AI Are Revolutionizing the Customer Experience

Unite.AI

AI is no longer just a tool used alongside agentswe're now seeing a true symbiosis. From enhancing customer experience with conversational AI to accelerating speed-to-value and scale through AI-powered multilingual translation, the adoption of AI is a force multiplier. Lost in Translation?

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Meta AI Introduces Brain2Qwerty: A New Deep Learning Model for Decoding Sentences from Brain Activity with EEG or MEG while Participants Typed Briefly Memorized Sentences on a QWERTY Keyboard

Marktechpost

Dont Forget to join our 75k+ ML SubReddit.

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Achieve multi-Region resiliency for your conversational AI chatbots with Amazon Lex

AWS Machine Learning Blog

Integrations with Amazon Connect Amazon Lex Global Resiliency seamlessly complements Amazon Connect Global Resiliency , providing you with a comprehensive solution for maintaining business continuity and resilience across your conversational AI and contact center infrastructure.

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Building a Multi-Agent System with CAMEL AI

Analytics Vidhya

Deep learning intelligent agents are revolutionizing the concept of machine and technology around us. Cognitive systems are able to reason, decide, operate and even solve problems without human interferences.

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Reduce conversational AI response time through inference at the edge with AWS Local Zones

AWS Machine Learning Blog

Recent advances in generative AI have led to the proliferation of new generation of conversational AI assistants powered by foundation models (FMs). These latency-sensitive applications enable real-time text and voice interactions, responding naturally to human conversations. Amazon Linux 2). model=meta-llama/Llama-3.2-3B