The session on AI-as-a-Service (AIaaS) with Cross-Industry Applications can have the following key outcomes:
1. Understanding AI-as-a-Service (AIaaS)
Definition and components of AIaaS
Cloud-based AI solutions and their advantages
How AIaaS democratizes AI for businesses
2. Cross-Industry Applications of AIaaS
Healthcare: AI-driven diagnostics, personalized medicine, and predictive analytics
Finance: Fraud detection, risk assessment, and algorithmic trading
Retail & E-commerce: Personalized recommendations, chatbots, and inventory management
Manufacturing: Predictive maintenance, quality control, and automation
Education: AI tutors, automated grading, and personalized learning
Cybersecurity: AI-driven threat detection and automated response systems
3. Understanding TRIZ and Inventive Thinking
Introduction to TRIZ (Theory of Inventive Problem Solving)
How TRIZ differs from traditional problem-solving approaches
The role of systematic innovation in defining future strategies
4. TRIZ Principles for Problem-Solving and Innovation
TRIZ Inventive Principles and their real-world applications
Identifying and resolving contradictions in problem-solving
Using TRIZ to anticipate technological evolution (Trends of Engineering System Evolution - TESE)
KPRIET – An AI Integrated Campus
Preparing future-ready engineers with AI-integrated teaching and learning. KPRIET integrates Artificial Intelligence across teaching, learning, research and innovation to create a smarter, future-ready campus experience for students and faculty.
