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AI Applications: From Experimental Pilots to Business-Critical Systems
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Artificial Intelligence Applications
Implementing AI to Transform Products and Operations
Practical applications of AI technologies across business functions. Covers implementing generative AI, natural language processing, computer vision, recommendation systems, conversational interfaces, autonomous agents, and knowledge-enhanced AI systems like retrieval-augmented generation. Maturity advances from experimental pilots to scaled, business-critical AI capabilities embedded in products and operations.
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AI Agents Survival Guide: Most Will Fail by Repeating the Telephone Operator Mistake
Examines autonomous AI agents that can plan, execute, and adapt with minimal human oversight. Provides frameworks for identifying appropriate use cases, designing guardrails and oversight mechanisms, managing the risks of increased autonomy, and evolving from copilots to agents as trust and capability mature.
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Knowledge Graphs vs Language Models: Why You Need Both
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Why Your Next AI System Will Be a Team, Not a Model
Examines architectures that combine multiple AI models, retrieval systems, tools, and traditional logic to solve complex problems no single model can handle. Covers design patterns, orchestration frameworks, testing and debugging strategies, reliability engineering, and when compound systems justify the added complexity.
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Your AI Will Soon Be “Dumber” Than ChatGPT – By Design
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