Tag: Concept
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Customer Experience Automation: Boosting Engagement & Efficiency – 2025-05-12
Channel: IBM Date Published: 2025-05-12 Summary Customer Experience Automation (CXA) leverages technology to automate and enhance customer interactions across the entire customer lifecycle, spanning various channels like web, mobile, social media, chat, email, and call centers. It aims to deliver consistent, high-quality, and personalized experiences. CXA depends on four interconnected processes: orchestration (mapping the customer…
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Business Automation Strategy: 7 Key Steps for Success – 2025-05-16
Channel: IBM Date Published: 2025-05-16 Summary This video outlines seven key steps for creating an effective automation strategy. The strategy should streamline operations, enhance decision-making, and drive digital transformation, augmenting human capabilities rather than replacing employees. Step one involves assessing and identifying opportunities by analyzing current processes and identifying pain points. Step two focuses on…
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The Era of an AI Augmented Workforce: How AI Enhances Human Efforts – 2024-01-26
Channel: IBM Date Published: 2024-01-26 Summary This video discusses how AI is augmenting human efforts in the workplace, using three use cases to illustrate the point. It emphasizes that while AI can automate manual tasks and enhance data processing, human input remains crucial for context, strategy, and empathy. The first example features Susan, an administrative…
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How business leaders budget for generative AI – 2024-12-19
Channel: IBM Date Published: 2024-12-19 Summary This episode of AI Academy, hosted by Anthony Marshall from IBM’s Institute for Business Value, discusses how business leaders should approach budgeting for Generative AI (GenAI). It highlights that traditional budgeting methods often fall short when applied to GenAI due to its unique characteristics and potential for both efficiency…
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Building a data strategy for AI – 2024-05-02
Channel: IBM Date Published: 2024-05-02 Summary This AI Academy video emphasizes the critical role of high-quality data in achieving successful AI implementations. It highlights that many organizations struggle to derive significant business value from AI due to inadequate data strategies. A modern data strategy is essential for managing unstructured data, which constitutes a large portion…
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5 Types of AI Agents: Autonomous Functions & Real-World Applications – 2024-05-02
Channel: IBM Technology Date Published: 2024-05-02 Summary This video explains the five main types of AI agents, differentiating them based on their intelligence, decision-making processes, and interaction with their environments. It begins with the simple reflex agent, which follows predefined rules like a thermostat, reacting to immediate conditions without memory. Next, the model-based reflex agent…
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Context Engineering vs. Prompt Engineering: Smarter AI with RAG & Agents – 2025-08-18
Channel: IBM Technology Date Published: 2025-08-18 Summary The video differentiates between prompt engineering and context engineering in the realm of large language models (LLMs) and agentic AI. Prompt engineering involves crafting the input text (prompts) to steer the LLM’s behavior, while context engineering is a broader discipline that encompasses programmatically assembling everything the LLM sees…
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MCP in Action: Revolutionizing AI Agent Integration – 2025-07-29
Channel: IBM Technology Date Published: 2025-07-29 Summary The Model Context Protocol (MCP) is presented as a transformative technology that standardizes the way AI models interact with various tools and APIs, likening it to a universal interface (USB-C) for AI agents. It eliminates the need for custom integrations, simplifying the connection of AI models to repositories,…
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🦸🏻#14: What Is MCP, and Why Is Everyone – Suddenly!– Talking About It? – 2025-03-17
Author: Ksenia Se Date: 2025-03-17 Summary The article introduces the Model Context Protocol (MCP), an open standard developed by Anthropic to bridge AI systems with external tools and data sources. MCP emerged as a solution to the longstanding challenge of integrating language models with real-world systems in scalable, flexible ways. Although MCP was initially announced…