Lessons Learned Building a GenAI Powered App

Overview

Join us for an enlightening session on building GenAI-powered applications. Dive into practical tips and insights derived from real-world experiences and learn about the best practices in the dynamic field of artificial intelligence.

This presentation will offer valuable knowledge for anyone interested in the convergence of AI technology and application development. Whether you're a seasoned developer or new to AI, this talk promises to enhance your understanding and skills in building applications powered by generative AI.

Syllabus

• Introduction to GenAI Applications
Overview of Generative AI
Examples of GenAI-powered apps
Key differences from traditional AI applications
• Understanding GenAI Algorithms
Basics of Generative Adversarial Networks (GANs)
Introduction to Transformer models (e.g., GPT, BERT)
Selecting the right model for your application
• Designing a GenAI-powered App
Defining the problem and use case
User experience and interface considerations
Ethical considerations in GenAI
• Development Best Practices
Data collection and preprocessing
Training and fine-tuning models
Evaluating GenAI models
• Engineering and Infrastructure
Choosing the right cloud and computational resources
Optimizing for scalability and performance
Managing deployments and updates
• Real-world Challenges and Solutions
Handling bias and ensuring fairness
Addressing security and privacy concerns
Mitigating hallucinations and error correction
• Case Studies
Detailed analysis of successful GenAI apps
Lessons learned from failed projects
• Future Trends and Opportunities
Emerging technologies in GenAI
Potential applications and new use cases
• Wrap-up and Course Review
Summary of key insights
Discussion of takeaways and implementation strategies

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Subjects

Conference Talks