AI GOVERNANCE
As AI and data technologies advance, organizations face complex risks, regulations, and ethical challenges. "Manage AI & Data Risk: Effective Strategies for Governing Information, Data & Artificial Intelligence" serves as a comprehensive guide for leaders, professionals, and policymakers to navigate AI's challenges while maintaining ethical and compliant data governance.
The book starts by explaining the fundamentals of AI, from machine learning to the evolving AI tech stack, offering readers insights into the development of AI and data science. It then explores the risks posed by AI systems and compares various global ethical frameworks for trustworthy AI use.
With a focus on regulatory landscapes like the EU's GDPR and the emerging EU AI Act, the guide provides an in-depth look at AI risk management frameworks to ensure compliance with current and future laws. It also breaks down the AI life cycle, offering practical insights on structuring, testing, and validating AI projects.
Actionable strategies are provided for responsible AI governance, including integrating AI risk management with operational risk strategies, establishing governance infrastructure, managing post-deployment systems, and addressing legal and auditing challenges.
"Manage AI & Data Risk" equips organizations to govern AI and data systems effectively, mitigate risks, ensure compliance, and build stakeholder trust—making it essential for business leaders, data scientists, risk managers, and policymakers.
LARGE LANGUAGE MODELS
Beyond Words a comprehensive exploration of Large Language Models (LLMs), delving into their development, architecture, applications, and the broader implications of their use. This book is designed for both newcomers and seasoned professionals interested in understanding the transformative impact of LLMs on various fields.
Key Features:
Introduction to LLMs
Core Principles and Architectures
Performance and Capabilities
Training and Fine-tuning
Key Challenges and Limitations
Future Directions and Trends
Beyond Words is a must-read for anyone looking to understand the nuances of Large Language Models and their profound implications for the future of artificial intelligence and its applications.
CONVERSATIONAL E-COMMERCE
AI-Powered Commerce: Revolutionizing Product Recommendations with LLMs and RAG provides executives with the blueprint to harness the transformative power of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to revolutionize how products are recommended to customers in real-time, leading to substantial growth in revenue, customer satisfaction, and operational efficiency.
Key takeaways include:
Understanding how LLMs and RAG can revolutionize product recommendations.
Building AI-powered conversational systems that scale across platforms.
Real-world case studies demonstrating successful AI implementation in e-commerce.
Strategies for overcoming technical, operational, and compliance challenges.
How to maximize business growth through AI-driven customer engagement and personalization.
CONVERSATIONAL E-COMMERCE
Ethical Data Harvesting for Customer Data Platforms: Unlocking the Power of Bidirectional Conversational AI, explores the intersection of AI technology, ethical data practices, and regulatory compliance. It emphasizes the importance of designing secure, scalable, and compliant AI-driven interactions that enhance real-time insights and personalization while prioritizing user trust and transparency.
Key takeaways include:
Importance of Ethical Practices: Organizations must prioritize ethical data harvesting practices to build trust and ensure compliance with regulations while leveraging AI technologies in customer interactions.
Understanding Regulatory Compliance: Familiarity with regulations such as GDPR, CCPA, and COPPA is crucial for organizations to navigate legal obligations and protect user data rights.
Transparency and Trust: Clear communication regarding data collection, AI capabilities, and the nature of interactions with virtual avatars is essential for fostering customer trust.
User Empowerment: Providing customers with control over their data, including consent management and the right to access and delete information, enhances their confidence in engaging with AI systems.