Artificial Intelligence, Machine Learning and Big Data

Natural Language Processing (NLP) is a topic of computer science, Computational Linguistics and Artificial Intelligence which is concerned with the ability of a computer program to understand human languages. The steps which are used in Natural Language Processing include Lexical Analysis, Syntactic Analysis, Semantic Analysis, Discourse Integration, Pragmatic Analysis, etc. This topic will help participants to understand how Artificial Intelligence and Natural Language Processing can be utilized to perform the useful task using various human languages

The future Artificial Intelligence (AI) has the potential to transform the world. Time since the Turing Test was proposed, computers have become so intelligent. Artificial Intelligence is fast becoming a major economic force. For sure It will be an integral part of the human life in future. However, an important question remains is that what will happen if the pursuit of strong AI succeeds and an Artificial Intelligence system becomes better than humans. We believe this session will help us to discuss, prepare and prevent such potential outcomes in the future.

Big Data Analytics studies large volumes of data to uncover hidden patterns, correlations, and other visions. Decades before anyone pronounced the term “big data,” even in the 1950s, businesses were using basic analytics to be aware of the trends.  However, the advancement that big data analytics brings to the industry includes efficiency and speed. This progress in Big Data Analysis leads to smarter business models, more efficient operations and happier customers. This session will help especially organizations and industry people to gather knowledge on how to utilize their data and use it to spot new opportunities.

Modern Artificial Intelligence (AI), is the ability of a computer-controlled robot to perform tasks commonly associated with intelligent beings. Integration of various systems is necessary for a promising Artificial Intelligence. The pillars of Modern AI include computational intelligence, Neural Networks, Genetic Algorithms, Swarm Algorithms and Fuzzy Logic. Modern AI uses tools and data from the fields like computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, operations research, economics, control theory etc. The above session will put a clear picture about various facets of Modern Artificial Intelligence.

Intelligent Automation can be used in industry to enhance productivity and efficiency, reduce operational risks, and improve customer experiences. This plays a vital role in any industry’s next-generation innovation. In Intelligence Automation, we use a software or hardware which has the ability to perform things automatically. This session helps to analyse the widespread integration of Automation and Artificial Intelligence and how it is helping the human lives.

The ability of the Autonomous Systems to make decisions for themselves, with little to no input from humans greatly increases the utility of robots and similar devices. However, due to this autonomous function, some experts and academics have questioned the use of AI in various jobs. Writers like Isaac Asimov considered the issue in many of his works. This session aims to provide an agenda within which researchers can anticipate the current and future ethical issues and to provide insights about what is, and is not, regarded as ethical behaviour.

Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop a conventional algorithm for effectively performing the task. This focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is also referred to as predictive analytics.

Although the science of robotics only came about in the 20th century, for thousands of year’s man has been imagining Intelligent Mechanized Systems which can perform human-like works. In the modern era, the term ‘Robot’ has been introduced for the first time by Karel Capek in 1921. Today, one can visualize human-sized robots with the ability of near-human thoughts and works, which are being launched into space to complete the next stages of extra-terrestrial and extra solar research. This session is meant to go through the entire journey and go through the process of creating the human invented automation system.

Just like any human being robots are also assimilation of many parts. All robot consists of some Mechanical, Electrical Components along with some computer programming. As more and more robots are designed for specific tasks components are also designed likewise. Robots can be created in many ways, using all manner of materials, however, most robots share a great deal in common. This session will help a lot of researchers, students to analyse the process of creation of robot and what are the future trend in this area.

We are now living in the smart machine era. Robots are playing an extensive and vital role in our routine life. It feels like science fiction is starting to become reality. Starting from home to workplace they are now in every sector. Robots are increasingly coming closer to us as smart technology allows people to control the functions of their home. As technology becomes more forward-thinking, it's clear that the world is changing and there's a good possibility that robots will be functioning in ordinary people's homes within the next decade or so.The main discussion point of the session will be how robots grow into an essential partner in our journey and how they are helping us to simplify our life.

Professionals are unanimous in predicting that long-term sustainability of healthcare systems could be met by automation driven by digital health technologies, such as artificial intelligence, 3D-printing or robotics. Robots can support, assist and extend the service health workers are offering.This session will highlight the role of these RoboticTechnology in our health care system and issues arising out of it.

The Internet has revolutionized the world and communications like nothing before. The inception of internet begins with the development of the computer. Foundation with the early research in packet switching, the government, industry, and researchers has been partners in evolving and implementing this new technology. The history of the internet is complex and involves many technological, organizational aspects. Its influence reaches throughout society.The aim of the session will be to revisit the whole journey which led us to today’s digital world.

The Internet of Things (IoT) refers to the networked interconnection of objects equipped with ubiquitous intelligence, or simply “smart objects”. Several endeavours have been made in the last decade to bring together standard modelling languages with generic simulation frameworks. Modelling allows description of aspects at a higher level of abstraction independent from the target platform and simulation helps to simulate such description in large-scale scenarios. The session will help to learn about the nitty-gritty of the importance of modelling and simulation in the Internet of Things.

Technology’s ability to create wonderful things in the future stretches from fiction to fact: self-driving cars, virtual reality, and smart devices. The applications for internet connected devices are widespread. A growing number of Internet of Things (IoT) devices are designed for human use. Starting from agriculture to defense and space, it is affecting our lives in many ways.

This session will discuss how the IoT has been now an inseparable part of our lifestyle and the issues and technologies related to it.

Evolutionary Robotics is a computer-simulated technique of creating Intelligent and Autonomous Robots. The initial idea of encoding a robot control system into a genome and have artificial evolution dates back to the late 80s. Evolutionary computation can be used to design the physical structure of the robot. Neural Network is the most common type of controller used in evolutionary robotics. This session is designed to understand and discuss how to create a useful controller to complete many robotic tasks.