How are artificial neural networks and intelligent systems changing industries and our everyday lives? How do complex systems and algorithms and systems translate into consumer products? And how do we make sure that artificial intelligence doesn’t cross the line and becomes dangerous? These issues and more will be explored at IntelSys 2017, EAI International Conference on Emerging Trends in Intelligent Systems (October 14-15, Coimbatore, India) together with the keynote speaker Dr. D. Jude Hemanth (Department of Electronics and Communications Engineering, Karunya University), whose brains we were thrilled to pick.
Could you summarize the scope of your current work and what you are coming to share with everyone at IntelSys 2017?
Currently, I am developing novel soft computing (intelligent) techniques such as Artificial Neural Networks and fuzzy systems. The novelty in these systems is seen with the architectures and training algorithms. The significant aspect of these novels systems is that they work more efficiently than the conventional systems.
The applicability of the algorithms is explored in the context of medical image analysis (classification and segmentation of medical images). In this conference, I am going to focus on two aspects: to share the technical details of algorithms and systems developed by me in the context of retinal image analysis, and to initiate a spark among the budding engineers among participants to develop intelligent systems to solve societal problems.
What do you see as the biggest challenges that intelligent systems are currently facing?
For one thing, it is the lack of practical feasibility of the intelligent algorithms since most of them are iteration-dependent. Another one is the difficulty of converting these algorithms/systems into products. Furthermore, though we say “intelligent systems”, a “complete intelligence” has not been achieved yet. One must also keep an eye on the possible negative impacts of such Artificial Intelligence (AI) systems.
How do you see research and industry moving forward and tackling these challenges?
The pace of the work of the R&D industries in tackling these challenges is very high. However, there are still miles to go.
R&D industries give more emphasis on developing innovative intelligent algorithms, which is the need of the hour. More emphasis is put on developing product development to fill the gap of practical non-feasibility, and in intelligent robotic systems, most of the companies are incorporating a “Plan B” in the case of failure.
What would you say are the main trends in this area that are showing promise?
There are plenty but here a few of them are deep learning approaches, virtual reality mixed with intelligent systems, anomaly detection, scene understanding, graphics and animation, and nature-inspired computing algorithms.
Learn more and register for IntelSys 2017 here.