ADCOM 2018 provided a fascinating ensemble of keynotes by the subject matter experts. Dr. P. Anandan, currently the CEO of Wadhwani Institute for Artificial Intelligence and formerly the Managing Director at Microsoft Research India talked about how artificial intelligence can be used for societal causes with particular emphasis on extending healthcare benefits to the deprived. Dr. Manish Gupta, CEO of VideoKen and Infosys Foundation Chair Professor at IIIT-B presented his work on fast cataloguing of a given video stream using artificial intelligence. Mr C. Mohan Ram, CEO, Kaizenvoiz, explained the use of artificial intelligence and behavioural analytics for user authentication obviating the need for password. Dr. Sriram Rajamani, Managing Director of Microsoft Research India, expounded on the path breaking research happening at Microsoft in the area of artificial intelligence (AI), machine learning (ML) and internet of things (IoT). The talk covered theory of data Science, low resource Natural Language Processing (NLP) and low resource ML together with AI/MI solutions for societal scale problems.
Dr. Shailesh Kumar, Reliance Jio, traced the evolution of product strategy, decision approach and AI thinking, and then elaborated how AI can be used in eCommerce to optimize the inventory and delivery, personalize the pricing, and accelerate the mutual discovery of products and customers.
From a large number of submissions, about 15% of papers were accepted for presentation in multiple parallel tracks. The track on “Machine Learning for Healthcare” had interesting papers on analysis of ECG, EEG and hearing through bone conduction, using machine learning and neural networks. The track on “Image Understanding and AI” dealt with papers on compression of images obtained from satellite and detection of headgear for compliance with traffic laws, etc. Yet another track had papers suggesting use of neural network and fuzzy logic for text recognition with applications in language translation and automated query interpretation. There was a track on Deep Learning featuring papers that explored applications as diverse as robotic grasping, relation extraction and Smartphone CPU usage prediction.