Machine Intelligence Research Labs (MIR Labs)

Machine Intelligence Research Labs (MIR Labs) was established in 2008 as a global non-profit academic consortium focused on innovation and research excellence. MIR Labs network comprises of several leading academicians and scientists from the Univers ading academicians and scientists from the Universities and Industry from different continents. The main objectives of Machine Intelligence Research Labs (MIR Labs) are as follows. To initiate new innovative research directions by networking together the critical mass of resources To strengthen scientific and technological excellence on a particular research area, which is important to a particular geographical region / area / country etc. To integrate the various research efforts of the scientific team to be a source of innovation on possible scientific, technological and socio-economic trajectories to mould the future of Machine Intelligence To promote and sponsor scientific activities (conferences and workshops) in developing and under represented countries by offering mentoring, technical assistance etc. The idea of Machine Intelligence refers back to 1936, when Alan Turing proposed the idea of universal mathematics machine, a theoretical concept in the mathematical theory of computability. In the MIR Labs framework, machine intelligence refers to building adaptive intelligence (network intelligence) in a network of machines (networks) to solve a problem. Computational intelligence techniques have found their way in solving some real world problems in science, business, technology and commerce. Today we have methodologies that could translate languages, identify objects in images and video, advanced automation in manufacturing processes, control cars etc., just to name a few. Inspite of the evolution of current techniques, sometimes we realize that the so-called computational intelligence is many a times very artificial in nature. It can be argued with some conviction that a computationally intelligent algorithm that cannot solve new problems in new ways is emphasizing the artificial and not intelligence.Defining machine intelligence is not an easy task. It is a consortium of various technologies involving non-linear dynamics, computational intelligence, ideas from physics, physcology and several other computational frameworks. We are blessed with sophisticated technological artifacts that are enriching our daily lives and the society. It is believed that the cyber infrastrcuture is going to provide us the framework to integrate, control or operate virtually any device, appliance, monitoring systems, infrastructures etc. An Internet enabled cyber-ecosystem is not far away. Such a complex system has to be autonomous and able to continuously adapt, providing the required quality of service levels according to different service level agreements, without requiring the need of much human intervention. This is an interesting problem. The challenge is to design intelligent machines and networks that could communicate and adapt according to critic or error information, self organize and resilient in case of a system, service or component failure due to natural cause or a malicious attack. Currently a lot of focused research works is going in different areas and most of these results are confined to the institutions and laboratories. We believe that an academic initiative is required to integrate the various research efforts to build complex intelligent machines and networks that can tackle our complex problems of the future. The goal of our society is to develop an efficient and highly productive research group with the least over-head costs focusing on machine intelligence research. This requires a concerted team effort from a diverse group of individuals and institutions. Our work culture is based on extensive collaboration with international scientific networks including universities, research centers, regulatory authorities and industry from all over the world. Our research teams work toward a common goal of generating scientifically validated innovations, including methods of research, technologies, that benefit the society. Gender equity, youth, and resilience play a significant role in our research portfolio and how to engage young research at all levels of the research process. We also support graduate student training, which is critical to improving the research capacity of scientists in developing countries that positively impacts people and communities. Over the years, we got involved in several funded research projects from the Government and the Industry.