Reframing GenAI as Not AI - Generative Search, Auto-Complete and Pattern Matching

Overview

Uncover the reality behind the AI hype:

what we often refer to as "AI" is, in actuality, generative search and pattern matching, devoid of true intelligence. This event offers insight into why redefining these technologies as practical IT tools rather than mysterious solutions leads to more effective implementation.

Syllabus

• Introduction to Generative AI
Overview of generative AI technologies
Common misconceptions about AI
Importance of accurate terminology and understanding
• The Reality of AI Capabilities
Differentiating between AI and IT tools
Case studies: Where generative AI is used
Limitations of current AI technologies
• Generative Search
Mechanisms of generative search
Applications and examples
Advantages and pitfalls
• Auto-Complete Technologies
How auto-complete works
Key algorithms in pattern recognition
Impact on user experience and productivity
• Pattern Matching
Understanding pattern recognition
Techniques and methods
Real-world implementations and challenges
• Reframing AI as IT Tools
Benefits of reframing AI technologies
Strategic implementation in organizations
Managing expectations and aligning goals
• Ethical and Practical Considerations
Ethical concerns and responsible use
Data privacy and security issues
Future directions and responsible innovation
• Conclusion
Recap of key learnings
Implications for businesses and technology development
Final thoughts on the evolution of generative AI technologies

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Subjects

Computer Science