Report on the Two-Day Workshop on Artificial Intelligence and Generative AI
Organised at IIT Roorkee

Introduction

The twenty-first century is defined by rapid technological advances, among which Artificial Intelligence (AI) and Generative Artificial Intelligence (Gen AI) stand at the forefront. AI is no longer just a futuristic concept but an integral part of industries, economies, and societies worldwide. Generative AI, a subset of AI, has recently captured global attention with its ability to create new text, images, music, and even scientific insights, marking a significant leap forward in human-computer collaboration.

In this context, I had the privilege of attending a two-day offline workshop on Artificial Intelligence and Generative AI at the Indian Institute of Technology (IIT) Roorkee, one of India’s most prestigious institutions. The workshop provided a unique blend of theoretical foundations, practical demonstrations, and discussions on real-world applications.

The report that follows provides a comprehensive overview of my experience at IIT Roorkee, the knowledge imparted during the sessions, and my personal reflections. It is written with an educational purpose to highlight the importance of such learning opportunities and to share the core concepts of AI and Gen AI with a wider academic audience.


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About IIT Roorkee and the Workshop

Founded in 1847, IIT Roorkee is one of the oldest technical institutions in Asia and has consistently been a leader in engineering and scientific research. Its legacy in innovation and knowledge dissemination made it an ideal venue for a workshop on frontier technologies like Artificial Intelligence and Generative AI.

The workshop was designed as an intensive two-day programme aimed at introducing participants to both the fundamentals of AI and the emerging world of Gen AI. It was structured to cater to beginners while also offering valuable insights into practical applications. Faculty experts, research scholars, and trainers led the sessions, creating an engaging environment where concepts were explained, demonstrated, and discussed in depth.

The event was not merely about classroom learning but also about experiencing the intellectual atmosphere of IIT Roorkee, networking with like-minded peers, and gaining exposure to the institution’s cutting-edge research facilities.


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Workshop Overview

Day 1: Artificial Intelligence – Foundations and Applications

The first day was dedicated to understanding the foundations of Artificial Intelligence. The sessions started with definitions, historical context, and the evolution of AI. From early symbolic AI to machine learning and modern deep learning, the speakers traced the journey of AI as both a scientific field and a driver of industrial innovation.

The focus was on core principles of AI:

Problem-solving and search techniques.

Knowledge representation and reasoning.

Supervised and unsupervised learning.

Neural networks and deep learning basics.

Applications in robotics, healthcare, finance, agriculture, and education.


Hands-on exercises included simple machine learning demonstrations using Python-based libraries, where participants could see how an algorithm learns from data and makes predictions.

Day 2: Generative AI – The New Frontier

The second day shifted focus to Generative AI, a field that has risen to prominence with breakthroughs like GPT (Generative Pretrained Transformer) models, DALL·E, Stable Diffusion, and others. The sessions began with the fundamentals of generative modelling, including probabilistic models, autoencoders, GANs (Generative Adversarial Networks), and transformers.

Key learning points included:

How Gen AI differs from traditional AI.

The role of deep learning architectures in enabling generative models.

Applications in content creation, design, drug discovery, coding assistance, and personalised education.

Ethical considerations, including bias, authenticity, and responsible AI use.


Live demonstrations showcased how Gen AI tools generate human-like text, create images from prompts, and assist in creative problem-solving. Participants also interacted with these systems to better understand their capabilities and limitations.


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Basics of Artificial Intelligence

What is AI?

Artificial Intelligence refers to the simulation of human intelligence processes by machines, especially computer systems. It involves creating algorithms that can perform tasks traditionally requiring human intelligence, such as learning, reasoning, problem-solving, perception, and natural language understanding.

Core Components of AI

1. Machine Learning (ML): Algorithms that allow systems to learn from data and improve performance over time without being explicitly programmed.


2. Neural Networks: Computing systems inspired by the human brain, consisting of layers of interconnected nodes that process data and identify patterns.


3. Natural Language Processing (NLP): Enables machines to understand, interpret, and respond in human language.


4. Computer Vision: Teaching machines to interpret and analyse visual data like images and videos.


5. Robotics: Integrating AI with mechanical systems to perform physical tasks autonomously.



Applications of AI

Healthcare: Disease diagnosis, personalised medicine, and drug discovery.

Finance: Fraud detection, algorithmic trading, and risk management.

Agriculture: Precision farming, crop yield prediction, and pest control.

Education: Adaptive learning platforms and automated grading.

Smart Cities: Traffic management, energy optimisation, and surveillance.



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Basics of Generative AI

What is Generative AI?

Generative AI is a branch of AI focused on creating new data that resembles existing data. Unlike traditional AI, which analyses or classifies data, Gen AI is capable of producing original outputs, such as text, images, audio, and even scientific designs.

Foundations of Generative AI

1. Generative Models: Models that learn the probability distribution of data and generate new samples.


2. Generative Adversarial Networks (GANs): A framework where two neural networks (generator and discriminator) compete to create increasingly realistic data.


3. Transformers: Neural architectures that use attention mechanisms to process large sequences of data, crucial for modern language models.


4. Diffusion Models: Models that generate images by reversing the process of adding noise, leading to high-quality outputs.



Applications of Generative AI

Creative Industries: Content generation, art, and music composition.

Education: Automated tutoring, personalised content creation.

Healthcare: Designing molecules for new drugs.

Software Development: AI-assisted coding and debugging.

Media: Deepfakes and virtual environments.


Ethical Considerations

While Gen AI offers vast potential, it also raises questions of authenticity, intellectual property, bias, and misuse. The workshop stressed the importance of responsible development and deployment of these technologies.


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Workshop Activities and Learning Environment

The interactive nature of the workshop made the learning experience highly enriching. Activities included:

Lectures and presentations on AI and Gen AI fundamentals.

Hands-on sessions using coding platforms for building small machine learning models.

Demonstrations of cutting-edge Gen AI applications.

Group discussions on ethical and social implications.

Q&A sessions with faculty to clarify concepts and explore advanced topics.


The atmosphere at IIT Roorkee, with its blend of academic rigour and collaborative spirit, created an ideal environment for immersive learning.


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Reflections and Personal Learning

Attending this workshop was an invaluable opportunity to expand my knowledge base in one of the most critical areas of technology today. Key takeaways for me included:

A solid grasp of AI fundamentals, which will serve as a foundation for advanced learning.

An appreciation of how Gen AI is revolutionising creativity and industry.

Practical insights into the working of machine learning and generative models.

A deeper understanding of the ethical dimensions of AI, an area often overlooked but increasingly important.


The experience also inspired me to explore further academic and professional pathways in AI, potentially contributing to research and innovation in this field.


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Conclusion

The two-day workshop on Artificial Intelligence and Generative AI at IIT Roorkee was not merely an academic exercise but an eye-opening experience into the future of technology. By covering both the foundational aspects of AI and the cutting-edge developments in Generative AI, the workshop equipped participants with knowledge that is both broad and deep.

In today’s digital era, where AI is transforming industries and human experiences alike, gaining such exposure is invaluable. IIT Roorkee provided the perfect platform, combining expertise, infrastructure, and a culture of innovation.

The knowledge and inspiration gained from this workshop will undoubtedly influence my academic pursuits and professional aspirations. More importantly, it reinforced the idea that AI and Gen AI are not just tools of the future but are shaping the present, making it essential for every learner, innovator, and policymaker to engage with these technologies responsibly.