Lessons Learned Building a GenAI Powered App

Overview

Join us for an enlightening session on building GenAI-powered applications. Delve into the lessons learned from real-world experiences and equip yourself with practical tips and best practices.

Whether you're an AI enthusiast or a seasoned developer, this presentation offers a wealth of knowledge to enhance your skills in artificial intelligence development.

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