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Current Applications of AI

The world of Artificial Intelligence (AI) is developing at a fast pace with significant advances and investments being made in computer-based AI and associated systems Let’s look at seven current applications of AI:
© Torrens University

The world of Artificial Intelligence (AI) is developing at a fast pace with significant advances and investments being made in computer-based AI and associated systems Let’s look at seven current applications of AI:

1. AI and Machine Learning

Machine Learning

When we talk about ML (Machine Learning) we are discussing an AI that can automatically learn from experience on its own. ML focuses on the development of programs that mine collected data to learn from. We usually categorise this process into unsupervised and supervised, with supervised meaning that the AI can apply ML only with the input of new parameters and controls, but the unsupervised AI can apply ML in a creative fashion, mutating and developing its boundaries to learn in new and sometimes unexpected ways. This sounds dangerous in a ‘killer robots’ kind of way, but is currently limited to very narrow scopes of work. For example, solving maths equations.

2. AI and Natural Language Processing

Natural Language Processing

NLP (Natural Language Processing) is another category of AI, bearing in mind that all these categories somewhat overlap, wherein the focus is on helping computers and systems to take in and understand human speech in a similar way to humans. This technology is not yet fully realised, as anyone who has attempted to ask Siri to do something simple can attest, but progress is being made, and each new version brings capabilities that many said wouldn’t be possible for many years.

3. AI and Expert Systems

Expert Systems

ES (Expert Systems) is the term given to a computer that has been developed to interact and express itself in as human a fashion as possible. For example, to drive a car, serve a customer, or produce financial forecasts in the same way a human expert would. ES usually achieves this through the core components of Knowledge Base (data, facts, rules of a key area. For example, driving) and Interference Engine (the utilisation of the Knowledge Base to find new patterns and learn new things).

4. AI and Computer Vision

Computer Vision

Simply put, this is the ability for AI to see. Put in a more technical sense, this is the research and development relating to AI use of vision to gain information from images and visual stimulation. This becomes very useful for any robot that needs to move around in its environment or any AI that needs to observe and process visual data to perform a task. AI Computer Vision includes areas like vision sensors, pattern recognition, and learning techniques. For example, what makes a chair a chair? It seems like a simple question that most humans can answer, but think of all the many variations of a chair. How would you teach a computer to instinctively differentiate a bench from a coffee table? Not an easy challenge (Krüger et al., 2007).

5. AI and Speech

Speech This, again put quite simply, is the ability for an AI to speak to us in a way that is familiar and understandable and for the AI to hear and understand when we speak to it. Progress has been rapid in this area, but perfect understanding still eludes us. Once this has been achieved, the reward of instantaneous international language translation awaits.

6. AI and Planning

Planning

AI Planning is one of the earliest and most utilised sub-categories of AI research. It is the application of AI to achieve goals in a more efficient and effective manner and can apply to any industry that utilises cyber security, cognitive assistants, robots and autonomous systems, and service composition.

7. AI Based Robotics

Based Robotics

When most people think of AI they think of a smart robot that can interact with a human in a way that is recognisable as some ‘personality’. For a robot to work on a factory production line, performing the same movement doesn’t require much ‘intelligence’. However, for a robot to have a sense of personality and character (presence) requires a complex representation of intelligence. The study and development of this is the field of AI based Robotics.

“There is no reason and no way that a human mind can keep up with an artificial intelligence machine by 2035.”
Gray Scott – Futurist, Techno-Philosopher, Speaker, and Writer.
© Torrens University
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