Generative AI is reshaping how data is processed, interpreted, and utilized across domains—from synthetic data generation to automated insights. This session offers a critical, technically grounded look at both the advantages and the risks of GenAI, emphasizing its implications for data-driven work. Whether you’re building models, analyzing patterns, or deploying systems, this discussion will help you better evaluate the role of GenAI in your practice.
Join this session and get to know more about:
- How generative models like GPT and diffusion networks function under the hood
- Practical applications of GenAI in data generation, cleaning, and model acceleration
- Challenges around bias, hallucination, and validation in generative outputs
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