Breakfast Meeting on Artificial Intelligence

AMCHAM’s Tamil Nadu Chapter held a breakfast meeting on artificial intelligence entitled ‘Why the recent excitement in artificial intelligence? An introduction to deep reinforcement learning’ on 8th November at the Hotel Westin in Chennai. The guest speaker was Professor Dr. B. Ravindran, Head – Robert Bosch Centre for Data Science and Artificial Intelligence (RBC-DSAI) & Associate Professor, Department of Computer Science and Engineering, IIT Madras. The meeting was chaired by Mr. Rajan Aiyer, Country Head, Trimble Information Technologies, India.

 

The meeting began with a welcome by Mr. Rajan Aiyer, Vice Chairman – Tamil Nadu Chapter, AMCHAM, who introduced the guest speaker Professor B. Ravindran.

 

Prof. Ravindran began by saying that humans excel at solving a wide variety of challenging problems, from low-level motor control through to high-level cognitive tasks. The goal of deepmind he said, is to create artificial agents that can achieve a similar level of performance and generality. Like a human, our agents learn for themselves to achieve successful strategies that lead to the greatest long-term rewards. This paradigm of learning by trial-and-error, solely from rewards or punishments, is known as reinforcement learning (RL). Also like a human, AI agents construct and learn their own knowledge directly from raw inputs, such as vision, without any hand-engineered features or domain heuristics. This is achieved by deep learning of neural networks. Deepmind has pioneered the combination of these approaches – deep reinforcement learning – to create the first artificial agents to achieve human-level performance across many challenging domains. Reinforcement learning (RL) methods have achieved significant successes recently by marrying the representation learning power of deep networks and the control learning abilities of RL. This has resulted in some of the most significant recent breakthroughs in artificial intelligence such as the Atari game player and the Alpha Go engine from Deepmind. This success has opened up new lines of research and revived old ones in the RL community.

 

In his presentation Dr. B. Ravindran introduced the reinforcement learning paradigm and briefly review the progress made in deep RL. His presentation in an easy to understand format to an AI ignorant audience to motivate the concepts through practical examples using the digital gaming platform.

 

Prof. Ravindran said that Artificial Intelligence (AI) is the branch of computer science which deals with the intelligence of machines, where an intelligent agent is a system that takes actions which maximize its chances of success. He added that the central principles of AI include reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects. AI is the science of making intelligent machines, especially intelligent computer programs.

 

AI has many varied applications such as in finance – all banking operations; pharmaceuticals and medicine – cardiology, neurology, embryology, development of new drugs, clinical studies, remote surgical procedures, etc.; gaming – computerised video games; information management and retrieval; AI expert systems embedded in products; help desk assistance; HR – employee performance evaluation; supply chain and logistics; marketing: satellite controls; network developments; military activity controls – smart bombs, unmanned drones, decoding of enemy secret codes; nuclear power station management; climate change – advanced weather modelling, doppler radar; industrial applications – machine vision inspection systems, robotic systems; telecommunications; music; cybersecurity; etc. This list is not exhaustive. Most consumer products and automobiles available today have some level of AI embedded in the operating system.

 

Prof. Ravindran also said that robotics is a major field related to AI. Robotics require intelligence to handle tasks such as object manipulation and navigation, along with localization, motion planning and mapping.

 

Speaking on machine learning, the Professor said that this is another core part of AI. Machine perception deals with the capability to use sensory inputs to deduce the different aspects of the world, while computer vision is the power to analyse visual inputs such as facial, object and gesture recognition.

 

During the interactive session Prof. Ravindran responded to some of the questions such as: Will there come a point when computers become too intelligent? Should robots have the same legal rights as humans? How would we get around the question of ownership? To what extent should we trust or predict the behaviour of robots? Would it be wrong to deliberately install mechanisms that gave humans an immediate physical advantage, such as an on/off switch?

 

The meeting concluded with Mr. Rajan Aiyer thanking Professor Ravindran for the very enlightening presentation on artificial intelligence. Prof. Ravindran welcomed members to visit IIT – Madras for further discussions or collaborative projects on artificial intelligence.