Workshop

Pre-Conference Workshops

Workshop

Generative Models- Methods, Tools and Applications

Date

02.04.2025

Audience

Research scholars, Faculty and PG students

Generative models are crucial in modern artificial intelligence due to their ability to create new data that resembles existing datasets. Their importance can be seen in various fields, including image generation, text generation for automated reports, music composition, and data augmentation to avoid overfitting and improve performance. They are particularly valuable in healthcare, anomaly detection, gaming, simulations, and architectural design. Generative models continue to evolve, enabling AI to become more creative and impactful across industries. The objective of the one-day workshop is to introduce the concepts, tools, and applications of generative models.

Time Slot Name Affiliation Topic Email Mobile No.
9:00 - 10:30 am Rahil Tiwari Software Engineer, Microsoft Transforming from LLMs to AI Agents Rahil_tiwari@live.com 9742016803
11:00 - 12:30 pm Mr. Balagangadhara Thilak Adiboina Verizon Data Services India Private Limited Large Language Models - -
2:00 - 3:30 pm S. Bhaskara Reddy Senior Project Manager, Infosys Data Augmentation Sbreddy1@rocketmail.com 8008551283

Overview

The pre-conference workshops are designed to provide an in-depth exploration of emerging topics, hands-on learning opportunities, and collaborative discussions within the field of Artificial Intelligence. These workshops offer participants the opportunity to delve into specific themes, methodologies, or challenges that complement the main conference program. Participants will engage in interactive sessions with experts in the field, gain practical skills, and foster connections with peers. Whether you're an academic, industry professional, or student, these workshops provide valuable knowledge applicable to research and real-world challenges.

Workshops Offered

Application of AI in Edge-Enabled Cloud

The Application of AI in Edge-Enabled Cloud workshop explores the integration of Artificial Intelligence (AI) with edge computing in cloud environments, a transformative approach that combines the power of centralized cloud computing with the low-latency, real-time processing capabilities of edge devices. This workshop is designed to delve into how AI algorithms can be deployed efficiently at the edge, and how edge-enabled cloud infrastructures can enhance AI's performance in areas such as industrial IoT, smart cities, autonomous vehicles, and real-time data analytics.

Participants will gain insight into the following key topics:

  • AI model deployment at the edge and in hybrid edge-cloud environments.
  • Data processing techniques that optimize real-time AI operations on edge devices.
  • Use of AI in edge computing to enhance decision-making, latency reduction, and resource management.
  • Case studies highlighting real-world applications, such as predictive maintenance, anomaly detection, and automation in Industry 4.0.
  • Challenges and solutions for scaling AI across distributed edge and cloud infrastructures.

This workshop is ideal for researchers, developers, and industry professionals interested in leveraging edge-enabled cloud for AI applications, focusing on both the theoretical underpinnings and practical implementations.

Workshop Format

The workshop will feature:

  • Interactive tutorials on deploying AI models in edge-enabled cloud environments.
  • Hands-on sessions using real-time data to simulate edge-AI applications.
  • Panel discussions on the future of AI in edge computing, addressing current challenges and advancements in technology.
  • Case study presentations by industry experts showcasing successful AI applications at the edge.
Requirements
  • Basic understanding of cloud computing, edge devices, and AI principles.
  • Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) is recommended.
  • Participants are encouraged to bring laptops for hands-on activities.
Learning Outcomes

By the end of the workshop, participants will:

  • Understand the role of AI in edge computing and cloud environments.
  • Learn how to deploy and manage AI models at the edge for low-latency applications.
  • Explore real-world use cases where AI at the edge has driven efficiency and innovation.
  • Gain practical experience through hands-on sessions and tools for developing edge-AI solutions.