2-GenAI.pptx

Certified GenAI Business Prompt Engineer (CGBPE) – Session 2 Copyright © 2024 Ivan Del Valle. All rights reserved. https://www.linkedin.com/in/enterprise-solutions Data Sources and Management for LLMs The role of data in training LLMs Training data shapes LLM capabilities Quality data enhances LLM p...

Certified GenAI Business Prompt Engineer (CGBPE) – Session 2 Copyright © 2024 Ivan Del Valle. All rights reserved. https://www.linkedin.com/in/enterprise-solutions Data Sources and Management for LLMs The role of data in training LLMs Training data shapes LLM capabilities Quality data enhances LLM performance Effective data management practices Organize data for efficient LLM training Regularly update and clean training datasets Data sources: Considerations and challenges Verify data accuracy and relevance Address data privacy and security concerns 2 / Unlocking the Power of Generative AI Building AI Models with LLMs Foundation models vs. custom-built models Pretrained vs. tailored for specific needs Ready-made vs. personalized approach The process of building LLM-based AI models Data selection, model training, evaluation Fine-tuning, testing, deployment steps Success stories of AI models with LLMs Improved translations, enhanced search results Increased sentiment analysis accuracy 3 / Unlocking the Power of Generative AI Data Platform Considerations for Generative AI Choosing the right data platform for AI projects Evaluate data security Ensure scalability and governance Consider GPU allocation and scaling Key features of effective data platforms for LLMs Scalable infrastructure Near-zero maintenance Supports pretrained language models Comparative analysis of popular data platforms Scalability comparison Maintenance complexity overview Feature comparison 4 / Unlocking the Power of Generative AI NLP: Teaching Machines to Understand Us NLP (Natural Language Processing): A branch of AI that helps computers understand, interpret, and use human language in a way that is both valuable and meaningful. Think of it as teaching a computer to understand our conversations, read our stories, and even catch our jokes. The Role of NLP in LLMs: LLMs (Large Language Models) like GPT-3 use advanced NLP to grasp the intricacies of human language. It's the difference between just hearing words and truly understanding them. How NLP Powers LLMs Communication: Enables LLMs to chat with us, answer questions, or offer customer support. Content Creation: Powers LLMs to write articles, generate creative stories, or even compose music. Understanding: Allows LLMs to read and summarize information, making sense of vast amounts of text data. Unlocking the Power of Generative AI / Deployment of LLM Applications Steps in deploying LLM applications Select suitable LLM Customize model for specific tasks Integrate with external applications Ensuring scalability and performance Optimize model efficiency Implement parallel processing Monitor system performance Best practices for LLM application deployment Regular model updates Security protocols implementation Testing in varied scenarios 6 / Unlocking the Power of Generative AI The Role of Domain-specific LLMs in AI Projects What are domain-specific LLMs? Focused on specific subjects or industries Trained for specialized knowledge extraction Advantages in AI project implementation Enhanced performance in targeted areas Efficient data extraction and analysis Examples of domain-specific LLM applications BioBERT for biomedical text analysis CodeBERT for cybersecurity solutions 7 / Unlocking the Power of Generative AI Customization and Selection of Language Models Customization techniques for LLMs Prompt-based fine-tuning Domain-specific data integration Custom prompt generation Criteria for selecting the right language model Task alignment Training data relevance Model size and complexity Adapting and tuning capabilities Ecosystem and support availability Success stories: Customized LLM implementations Improved chatbot interactions Enhanced text summarization accuracy Optimized language translation services 8 / Unlocking the Power of Generative AI Funding and Supporting GenAI Projects Sources of funding Governmental agencies Private corporations Academic institutions Crowdfunding platforms Supporting frameworks for responsible innovation Ethical guidelines Integration of ethical considerations Safety and robustness methodologies Development of reasoning capabilities 9 / Unlocking the Power of Generative AI Project Lifecycle and Deployment Strategies Lifecycle strategies for seamless AI deployment Selecting appropriate models Adapting models to specific tasks Guiding model customization for projects Tackling challenges in the deployment phase Overcoming data limitations Ensuring model compatibility Addressing performance issues Blueprints for successful AI project rollouts Utilizing orchestration libraries Implementing retrieval-augmented generation Scaling to multiple LLMs 10 / Unlocking the Power of Generative AI Monitoring and Compliance in Cloud Data Platforms Best practices for monitoring cloud platforms Regular audits Real-time alerts User activity tracking Compliance challenges and solutions Data encryption Access control policies Intrusion detection systems Case studies: Effective monitoring and compliance Company X implementation Regulatory compliance success 11 / Unlocking the Power of Generative AI Data breach prevention