In 2018 alone, AI-related startups and ventures have secured $9.3 billion in VC funding, according to a report from PwC and CB Insights. The Indian unicorns PayTm, Swiggy, and Oyo have been investing resources to gain AI capabilities and have acquired at least one AI company.
In 2018, VCs have funded Indian AI startups with USD 478.38 million in 111 funding rounds. One of the reasons why AI & machine learning-based technologies on the rise are that the competitive advantages one can develop using them, especially with the customer experience and cost optimization. In e-commerce, for example, understanding consumer behaviour and product demand and making the right offer at the right time can be the difference between winning or losing over the competition.
Change in Working
AI in the early stages was mostly based on rule-based systems, whose ability to deliver value is limited by how well the rules are defined, which requires human expertise. In machine learning (ML) — a subset of AI — once a model is trained, the ML model can learn further through inferencing — where the ML model is put to work on real-time data.
The ability of ML models to self-learn with minimal to no human interventions has been the key in gaining interest from entrepreneurs and innovators. Whether it’s shopping on Flipkart or watching movies on Netflix, the customers’ experiences are vastly touched my machine learning and its subset deep learning. Curating vast amount of content and making purchase recommendations has been one of the commercially well-recognized use cases that saw huge interest from tech giants as well as well-established startups. UBS estimates that AI as a standalone industry has the potential to reach a market cap of USD 120-180 billion by 2020.
Health Care and AI
Healthcare is another field where AI and machine learning systems are expected to make a big impact. For example, a Bangalore based startup delivers precision medicine using AI and machine learning. Another Bangalore based startup analyzes medical data and generates reports using deep learning systems, which can make a huge difference in delivering timely patient-care.
Machine learning is the turnkey technology that impacts many industry sectors: robotics, retail, banking, finance, self-driving, fraud-detection, weather forecasting, finding medicine for HIV, examining extraterrestrial objects, and so on. That is, AI & ML provide massive opportunities for entrepreneurs to explore, experiment, and build new businesses.
AI and machine learning applications need the power of massively parallel processing capabilities provided by GPUs. However, owning GPU hardware doesn’t justify 3-year amortization costs, especially for entrepreneurs who are starting out in the AI & ML space. Also, there aren’t many cost-effective GPU solutions available in the Indian market. Getting started with machine learning has become less difficult with the development and production-grade availability of Open Source frameworks.
AI & ML space is still young and entrepreneurs have a massive opportunity to innovate and disrupt. There have been concerns that AI might replace our jobs on a massive scale. However, according to a study by UBS, in most areas, AI is poised to replace tasks, not jobs.