AI, deep learning and algorithms such as Convolutional Neural Networks are outperforming other techniques in object detection in images or image streams. When we look at the detection of soccer balls in our soccer robots2, traditional machine vision techniques (including color segmentation and contour detection) are expensive in terms of computing power and not very robust to changes like different illumination. The Robocup initiative is struggling to move its soccer games outdoors, one of the reasons being poor sensing performance in outdoor daylight conditions. Driver assist systems for cars deal with outdoor conditions much better. When we use an off-the-shelf, less traditional neural network like YOLO3 in our lab, we can reliably and robustly detect all the balls in our field independently of their color, paint pattern, distance and illumination.

At first blush, creating better leads for companies that sell things to other companies may not seem like a big deal in a social sense, but I think it really is. They are really people, people trying to do things. In a lot of cases, they have built really great products, really great services, and yet they fail. I think one of the big reasons they fail is they just have not been able to connect with the market. It could be that they failed to get product market fit right, that they built the wrong solution. I think a lot of times, they've built a great solution, but they just don't have sales capabilities, or marketing capabilities. They don't have that little bit of luck to find those first important customers who are going to pay the bills and help them prove that what they have really works in the marketplace.

Artificial Intelligence (AI) is a term out of the books that has come to life in the last decade or so and is now widely used in businesses. Machine Learning (ML) is an integral part of AI that is redefining how businesses works in 2019. Almost 97% of the mobile phone subscribers use machine learning applications in one way or another both knowingly and unknowingly. Hence, applying ML to your businesses will open up wide opportunities to connect with new customers and business prospects equally. Against a traditional thought process, ML is not only applicable to large businesses with big names but to small and mid-sized businesses (SMBs) as well.

A central task force on Artificial Intelligence (AI) has suggested creating a National Artificial Intelligence Mission (N-AIM) that will serve as a nodal agency for coordinating AI related activities in the country. The report of the task force, set up by the Union Commerce Ministry in August last, has also said "AI should be seen as a scalable problem solver in India rather than only as a booster of economic growth." Professor V Kamakoti, Chairman of the task force and a Professor of IIT, Madras, said the report was a "practical" one and that "all our recommendations have been very pointed and it has been seen to it that they are very much implementable in a short time." According to the report, Artificial Intelligence "is the science and engineering of making intelligent machines, especially intelligent computer programmes." The task force, whose members include those from government and the private sector, besides the academia, has identified 10 domains in India, including Manufacturing, FinTech, Agriculture/Food Processing and Education for implementation of AI.