Postgraduate Courses in Artificial Intelligence (AI)
'AI' or Artificial Intelligence represents a subject area born from the primitive computing machines of WWII, and which has started to invisibly permeate many aspects of modern life. Washing machines with fuzzy logic controllers that learn their owners washing patterns, timetabling software, speech recognition systems and sophisticated design packages for the latest chip designers all use inference rules or ways of analysing a problem which cannot be solved using traditional mathematical analysis. AIl systems basically either try to mimic some aspect of human behaviour (mistakes included!) or attempt to make sensible, best case, (or least worst) decisions or actions when faced with confusing or imprecise information. For example, developing intelligent machines that can beat Grand Masters at Chess has been an AI challenge that has only just been realised (http://www.research.ibm.com/deepblue/). Studying a postgraduate course in Artificial Intelligence is guaranteed to put you at the forefront of this growing industry. Read on to discover what a postgraduate course in AI is all about.
As computing power has so rapidly expanded over the last few decades, there has been a similarly rapid rise in the performance of AI systems, which can now handle problems thought impossible only a few decades ago. But it is not just computing power – it is the enhanced understanding of human nature and the way that WE solve problems that has moved this knowledge forward. This is one of the compelling aspects of AI – it represents a blend of computing, analysis and psychology that many find irresistible.
In the UK, there is a growing AI industrial sector, that uses AI knowledge in the development of intelligent products (http://www.neuralnetworksolutions.com/, http://www.neurodynamics.com/, http://www.neusciences.com/, http://www.omniperception.com/). These use an exciting range of newly developed AI techniques as well as more established technology such as neural networks, a type of AI that is designed to mimic the way the brain works, and typically learns by examples. Neural networks are particularly useful in areas such as pattern recognition, generalisation and trend prediction, and have found uses in everything from market forecasting, image understanding to medical diagnosis and quality control.
Specialists involved in developing AI applications will often utilise a mix of computing, core AI knowledge and application-specific knowledge gained from a human expert. It is often the capture and modelling of this latter knowledge component that can make or break the performance of an AI system. A relevant MSc or PhD can be a good route into those companies developing these kinds of products.
Career opportunities using AI also include those undertaking pure and applied research in Universities (e.g. http://www.ee.surrey.ac.uk/CVSSP/) and industry (e.g. http://research.microsoft.com/). This requires a good understanding of the state-of-the-art in AI, and a vision of what is possible in the future. The core AI expertise can often be acquired as part of an undergraduate Computing or Electronic Engineering degree, or at postgraduate level, specialising in AI at Masters or PhD level. Students opting to study AI typically have interest in a wide range of subjects, and like to view topics from different perspectives.
Entry to university research is often via PhD research, perhaps preceded by an MSc (e.g. machine intelligence http://www.surrey.ac.uk/postgraduate/eps/electroniceng/taught/index.htm). One example of where the next generation of AI systems is headed is in the natural interface between man and machine, in which vision, speech, perception, learning are integrated into a system that enables machines and humans to communicate effortlessly. If this kind of vision interests you, then a postgraduate course in this area is a challenging and exciting way of entering the world of AI. Studying a postgraduate course in Artificial Intelligence will open up new opportunities for an interesting and dynamic career whether in industry or research.
Article by:
Kevin Wells, PhD
Terry Windeatt, PhD
University of Surrey
