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For Shrivash the exciting part of AI is witnessing the tectonic shifts and improvements happening frequently.

Deloitte AI Institute is proud to introduce a series profiling AI warriors who are pushing the boundaries of what’s possible in the search for new and innovative uses of AI.

"The exciting part is witnessing the tectonic shifts and improvements happening frequently in the field of data and AI."

Can you share the most interesting part of your career journey?

The interesting part of my professional journey is the learning and experience, which have always been in sync with the developments happening in the field of AI. I am working with cutting-edge technology and delivering on the most sought-after projects for big organisations/governments. The projects are independent of domain or scale. Given the fact that data is everywhere, we can work everywhere, which gives a very wide viewpoint of several businesses and processes.

What excites you the most about working with data and AI?

The exciting part is witnessing the tectonic shifts and improvements happening frequently in the field of data and AI. Data is increasingly transpiercing into our everyday tasks which can influence geopolitical decisions. The exciting part is that data gives us visibility and makes us far-sighted. This tool (for far sightedness) has the potential to change the course of individuals or businesses at a massive scale by studying historical patterns and projecting a future course.

Describe an interesting project that you have worked on.

We studied the GPS patterns of trucks which did not follow the prescribed route and accepted the delivery of a second consignment over and above the assignment. The trucks were supposed to deliver chemicals, which were installed with high-quality equipment, such as temperature and vibration controls, and we paid two times the price to forbid the usage of trucks for any other delivery. Our task was identifying trucks that had wandered away from the prescribed route despite using the GPS coordinates and timestamps. We identified the halt timings, found the nearby locations, flagged any chemical warehouses/cold storages nearby, and raised a signal to alert the transporter if anything likely was found.