Future Trends in Computing

1) Man machine Coexistence?
The development of ICT should be sustainable that machine shall not take the place of the man. Machines shall always be a tool for man, not other way. 

2) Artificial intelligence? (5th Gen. Computers)
Artificial intelligence (AI) studies and develops intelligent machines and software. It develops intelligents agents which perceives its environment and takes actions that maximize its chances of success.

3) Ubiquitous computing? 
Ubiquitous computing is a  model of human-computer interaction in which information processing has been thoroughly integrated into everyday objects and activities.  Someone using ubiquitous computing uses devices and systems, and may not even be aware of it. The machines that fit the human environment instead of forcing humans to enter theirs. 

4) Kansei systems/Engneering? 
The development ICT products and services that operates on users emotions  feelings and needs, The devices responds users's emotional responses

5) Augmented reality
AR is a live, direct or indirect, view of a physical, real-world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics or GPS data. As a result, the technology functions by enhancing one’s current perception of reality.By contrast, virtual reality replaces the real world with a simulated one. Augmentation is conventionally in real-time and in semantic context with environmental elements, such as sports scores on TV during a match. With the help of advanced technology the information about the surrounding real world of the user becomes interactive and digitally manipulable. Artificial information about the environment and its objects can be overlaid on the real world.

6.) Context Aware Computing
Context awareness is a property of mobile devices that is defined complementary to location awareness. Whereas location may determine how certain processes in a device operate, context may be applied more flexibly with mobile users, especially with users of smart phones. Context awareness originated as a term from ubiquitous computing or as so-called pervasive computing which sought to deal with linking changes in the environment with computer systems, which are otherwise static. The term has also been applied to business theory in relation to business process management issues.

7.) Quantum computing
QC developed on quantum physics where atoms are used as memory and processors. They are called quantum bits (qubits). Qubits can perform certain calculations exponentially faster than conventional computers. While traditional computers encode information into bits using binary numbers, either a 0 or 1. They can do calculations on one set of numbers at once, quantum computers encode information as a series of quantum-mechanical states can represent 1 , 4 or 16 states. It can do computations on many different numbers at once. Quantum computers are more powerful than a classical computers. Quantum computing is used in cryptography and modeling and indexing very large databases.

8). Evolutionary computing
This is a subfield of artificial intelligence that involves continuous optimization and combinational optimization problems. Evolutionary computation uses iterative progress, such as growth or development in a population. This population is then selected in a guided random search using parallel processing to achieve the desired end. Such processes are often inspired by biological mechanisms of evolution. As evolution can produce highly optimised processes and networks, it has many applications in computer science.

9). Biology Systems
is ICT applied to biomedical and biological scientific research. It focuses on complex interactions within biological systems to discover emergent properties, properties of cells, tissues and organisms functioning as a system. These typically involve metabolic networks or cell signaling networks. Genetic algorithms
A genetic algorithm (GA) is a search heuristic that follows natural evolution. It is used to generate useful solutions to search problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. Genetic algorithms find application in bioinformatics, phylogenetics, computational science, engineering, economics, chemistry, manufacturing, mathematics, physics and other fields.

11). Nature Inspired Computing (NIC) 
NIC aims to develop new computing techniques after getting ideas by observing how nature behaves in various situations to solve complex problems. Nano technologies are best examples of NIC. Nature Inspired Computing techniques are so flexible that they can be applied to wide range of problems, so adaptable that they can deal with unseen data and capable of learning, so robust that they can handle incomplete data. They have decentralized control of computational activities.