Thanks to recent progress in deep learning architectures, current AI is typically data intensive (needs a lot of data to train a good model) and infrastructure intensive (needs powerful machines to crunch the data). The last, and perhaps the most important, component to execute AI projects successfully is a well trained AI team that understands theory, has practical problem solving skills and is exposed to end-to-end system thinking. When compared to conventional large established companies to whom some of the above resources are available with ease and may be in abundance, in a typical startup company the emphasis is on doing more with less 'data, computation and number of hands' but without compromising on the quality and speed of execution. This talk is about how we devised our AI strategy at Swiggy and what are the lessons we can share from our journey. In the talk, I will also be discussing some practical use cases we have solved using generative AI models and their business impact on the Swiggy ecosystem.

Dr. Hemant Misra is an active researcher in the areas of text and signal processing, speech/speaker recognition, machine learning, healthcare applications and education. He did his MS (1999) from IIT, Madras, and PhD from EPFL (2006). Then he held post-doc positions at Telecom ParisTech, University of Glasgow, and Xerox Research Centre Europe. After having successful stints at Philips (Healthcare) Research, IBM's India Research Lab and Citicorp Services India, currently Hemant is 'VP - Head of Applied Research' at Swiggy.