Sixteenth Alumni Talk on Generative AI and Use Cases

Introduction to Generative AI

        A seminar on “Generative Artificial Intelligence (Gen AI)” was delivered by Dr. Sanjay Kumar Panda from A.B.A., Balasore, Odisha, at Fakir Mohan University, Balasore. Dr. Panda began his talk by introducing the concept of Generative AI as an advanced branch of Artificial Intelligence capable of creating new data such as text, images, audio, and videos based on existing information. Unlike conventional AI, which focuses on analyzing and predicting outcomes, Generative AI emphasizes creativity and innovation by generating original outputs that resemble human-created content. He highlighted the growing importance of Gen AI in transforming industries and driving automation through intelligent data-driven generation.

Uses in Different Fields

During the seminar, Dr. Panda discussed the diverse applications of Generative AI across various sectors. In healthcare, Gen AI is being used for drug discovery, image-based diagnosis, and treatment personalization. In the education sector, it helps in generating interactive study materials, question papers, and AI-based tutoring systems. The media and entertainment industry uses it to create realistic visuals, scripts, and music compositions. In business and marketing, AI assists in producing advertisements, market analysis, and customer engagement tools. Furthermore, in engineering, architecture, and design, it helps create prototypes and simulations that save time and resources, showcasing the vast potential of generative technology.

Different Tools for Generative AI

Dr. Panda also highlighted several important tools and platforms used in the development and implementation of Generative AI. He mentioned ChatGPT and DALL·E by OpenAI as leading tools for text and image generation respectively. Other tools like Google Bard (Gemini), Midjourney, and Stable Diffusion were also discussed for their roles in creative content generation. For researchers and developers, frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers are essential for building and training generative models. These tools have democratized AI by enabling students, professionals, and industries to experiment and innovate using intelligent content creation systems.

Challenges of Generative AI

In the concluding part of his seminar, Dr. Panda emphasized the ethical and technical challenges associated with Generative AI. He pointed out issues such as data privacy, copyright violations, and misuse through deepfakes that threaten trust and authenticity. Moreover, he addressed concerns about bias in AI models, as they can replicate unfair patterns present in the training data. He also mentioned the high computational cost and energy consumption involved in training these models, which raises questions about sustainability. Dr. Panda concluded his talk by stressing the need for responsible AI use, proper regulatory measures, and continuous research to ensure that Generative AI serves humanity positively and ethically.