Developments in Artificial Intelligence
Artificial intelligence (AI) has been one of the most controversial newest technology in computer science since it was first proposed in the 1950s. Defined as the part of computer science that exhibit the characteristics associated with human intelligence—understanding language, learning, reasoning, solving problems, and so on. Artificial intelligence (AI) is intelligence exhibited by machines.
In computer science, an ideal “intelligent” machine is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal. The field has been controversial because of its social, ethical, and philosophical implications. Such controversy has affected the funding environment for AI and the objectives of many research programs.
Artificial intelligence is on the rise and has already become a buzzword in the legal industry. So far, the discussion around the use of technology in the legal industry focuses on the battle between humans and machines – and the possibility of the latter taking over the jobs of lawyers. This short article focuses on the underlying technologies behind the structure.
Artificial intelligence (AI) is intelligence exhibited by machines. In computer science, an ideal “intelligent” machine is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal.
Artificial Intelligence (AI) was famously defined by John McCarthy as “the science and engineering of making intelligent machines.” AI could also be defined as “cognitive technologies.” However labelled, the field has many branches, with many significant connections and commonalities among them. The most important fields are currently machine learning including deep learning and predictive analytics, Natural Language Processing (NLP), comprising translation, classification & clustering and information extraction.
AI research is developed and implemented by a range of scientists and technologists with varying perspectives, interests, and motivations.Engineering-oriented researchers, by contrast, are interested in building systems that behave intelligently. Some attempt to build systems using techniques analogous to those used by humans, whereas others apply a range of techniques adopted from fields such as information theory, electrical engineering, statistics, and pattern recognition. Those in the latter category often do not necessarily consider themselves AI researchers, but rather fall into a broader category of researchers interested in machine intelligence.
This is a broad research area and the UK is a strong international contributor, evidenced by the existence of world-leading UK research groups and increasingly high levels of academic impact attained by the UK relative to the world. A significant proportion of EPSRC funding is concentrated in a small number of institutions, with the remainder spread across a large number of other universities. AI is an enabler for
many technologies, underpinning or linking with a number of other research areas, both within ICT (for example, Image and vision computing and Information systems) and beyond (for example, Robotics. The most visible users of AI research are often large companies, although there are also a number of smaller spin-outs that are starting to grow and become successful.