Popular consensus states that the advances that have taken place in deep learning over the last couple of decades are as fundamental as the advent of electricity. What we've seen so far is only the first wave of AI, and we're only starting to scratch the surface of what's possible. We wanted to understand what is happening in India and how it's being used.
On a balmy Wednesday evening in March, we hosted 'Recoding Business', to explore AI from specific vantage points. Lightbox partners Sandeep, Prashant and Sid spoke one-on-one with three experts knee-deep in solving India-specific problems in areas such as hyperlocal delivery, conversational interfaces and fashion.
Dale Vaz, Head of Data Science & Engineering at Swiggy
"We want to be able to understand what the customer needs even before they state that need."
Aakrit Vaish, Co-founder & CEO at Haptik
"If I was to start another company, one of the first three people I would hire would be a data scientist."
Ganesh Subramanian, Founder & CEO at Stylumia
"The approach to solving the problem [of waste in fashion] has been 'Let's use recycled materials', but nobody looks at how to make less... Sustainability is improving the prediction accuracy and making the industry more effective."
Highlights from the event
– AI helps us understand consumers, their context and better predict their needs. Which is then used to create products that they actually want.
– AI recognises patterns that we wouldn't expect.
– More than a consumer-facing tech play, this needs a data-driven culture wherein every employee feels that they're contributing to a business' intelligence. Data is a raw material currently being overlooked.
– Faster insights and capturing trends as they emerge enables companies to be more sustainable. By effectively forecasting demand, we can limit supply and reduce wastage of resources.
– AI is critical to achieve scale. The volume of data being produced and moving parts cannot be tackled by humans alone.
– The data scientist has become an integral role for startups as well as established companies, to collect, catalogue and make sense of all the data coming in.