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Transforming customer service: How generative AI is changing the game

IBM Journey to AI blog

Generative AI has the potential to significantly disrupt customer care, leveraging large language models (LLMs) and deep learning techniques designed to understand complex inquiries and offer to generate more human-like conversational responses. Watsonx.data allows scaling of AI workloads using customer data. Watsonx.ai

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4 Key Risks of Implementing AI: Real-Life Examples & Solutions

Dlabs.ai

It’s essential to keep humans involved in AI decision-making processes, especially when these decisions can significantly impact people’s lives. While AI systems can automate many tasks, they should not completely replace human judgment and intuition.

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Breaking Down AutoGPT: What It Is, Its Features, Limitations, Artificial General Intelligence (AGI) And Impact of Autonomous Agents on Generative AI

Marktechpost

LLMs, the Artificial Intelligence models that are designed to process natural language and generate human-like responses, are trending. The best example is OpenAI’s ChatGPT, the well-known chatbot that does everything from content generation and code completion to question answering, just like a human. What is AutoGPT?

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Model versioning, lineage, and packaging : Can you version and reproduce models and experiments? Can you see the complete model lineage with data/models/experiments used downstream? The platform’s labeling capabilities include flexible label function creation, auto-labeling, active learning, and so on.