In spite of being around for quite some time, the term ‘Artificial Intelligence’ has recently emerged as a hot-topic of conversation amongst researchers and technologists in the field of Computer Science.
But what is it?
Simply put, Artificial Intelligence is that branch of Computer Science concerned with making machines (specifically computers) behave like human beings, giving them the capacity to perform tasks that normally require human (natural) intelligence.
Already there are a series of activities that computers with Artificial Intelligence have been designed to perform:
- Speech Recognition
- Visual Perception
- Translation between Languages
- Learning and Reasoning
- Problem Solving
The term was first coined in 1956 by John McCarthy at the Massachusetts Institute of Technology and has become an essential part of the technology industry.
Research associated with Artificial Intelligence is highly technical and specialised and there are four core elements associated with AI: Knowledge Engineering, Machine Learning, Machine Perception and Robotics.
Knowledge Engineering is concerned with building, maintaining and the use of expert knowledge-based systems.
Such systems are computer programs that contain large amounts of knowledge, rules and reasoning mechanisms to provide solutions to real-world problems.
Computers and machines can only mimic human beings if they have access to an abundance of information relating to the world.
Effective Knowledge Engineering can transform data into information into ‘knowledge on demand’ and enable rational decision-making.
However, the development of these systems can be a slow and tedious business.
Machine Learning is another area of research and development that is central to the AI field.
In 1959, Arthur Samuel defined Machine Learning as a science that ‘gives computers the ability to learn without being explicitly programmed’.
It focuses on the development of computer programs that can teach themselves to grow and change when exposed to new data.
The process involves searching through data looking for patterns and adjusting program actions accordingly.
Facebook’s News Feed uses machine learning to personalise each member’s feed and Google’s Self Drive car is the very essence of Machine Learning.
Machine Perception is the capability of a computer system to interpret data in a manner that is similar to the way humans use their senses to relate to the world around them e.g. facial, object and speech recognition.
Traditionally, input to a computer is limited to a keyboard (or a mouse) but advances in technology, both in hardware and software, have allowed computers to take in sensory input in a way similar to humans.
The computer uses this sensory input (as well as traditional means) to gather information with greater accuracy and to present it in a way that is more comfortable for the user.
Robotics is the fourth major field related to AI.
It deals with the conception, design, construction, operation and use of robots managed by computer systems for their control, sensory feedback and information processing.
Robots require intelligence to handle tasks such as object manipulation and navigation and are widely used in industry to perform laborious, high precision and dangerous tasks.
ADVANTAGES AND DISADVANTAGES OF ARTIFICIAL INTELLIGENCE
Technology experts are in strong agreement of the many and varied benefits afforded to individuals, industry and society by Artificial Intelligence:
- Machines do not require sleep or breaks and are able to function without stopping.
- They can continuously perform the same task without getting bored or tired.
- They have already replaced human beings in many repetitive, laborious and painstaking tasks in an industrial setting e.g. assembly line in the automotive industry.
- Machines can shoulder greater responsibilities and can be programmed to manage themselves.
- They can carry out dangerous tasks and the risk to human health and safety is reduced.
- Computers can process and store huge volumes of data
- The chances of error are almost nil and greater precision and accuracy is achieved.
- Intelligent machines can operate in hostile environments where humans would toil e.g. interplanetary space, the oceans depths, underground mines deep into the earth.
- They are not hindered by the emotional side of the human psyche and can therefore arrive at logical and rational conclusions.
But there are perceived disadvantages too:
- There is a fear of Robots superseding humans.
- Human beings should continue to be the masters of Machines, but if somehow things were reversed then our world would descend into chaos.
- If the control of Machines got into the wrong hands it could lead to mass destruction. They don’t think before acting, just carry out what they have been programmed to do.
- The construction and maintenance costs of computers and machines equipped with Artificial Intelligence capability is extremely high and very time consuming.
- Human concepts such as care, understanding and togetherness cannot be understood by Machines – they will always lack the human touch.
- There is an ethical and moral argument about creating replicas of human beings.
- If robots begin to replace humans in a substantial number of work areas, it will lead to unemployment for many humans.
- People will be left with little to do and this may result in the destructive use of free time.
- Thinking machines lack a creative mind and are not able to contribute as effectively as human being when creativity and originality are required.
- The storage, access & retrieval of data is not as effective as in the case of the human brain.
Artificial Intelligence (AI) may well sound like something out of a Science Fiction movie, but we are already experiencing it in our lives today and in many different forms.
Its influence is set to grow in years ahead, but for now here are examples of applications today
- Smartphones use AI for predictive text and correcting human spelling errors, for GPS Map Applications (e.g. Google Maps) and for making user-choice recommendations.
- Fraud detection in smart card-based systems in the Financial Industry uses AI.
In a game where the computer plays as our opponent, it is with the help of AI that the machine plans the next moves in response to ours.
- Algorithms can help the doctors assess patients and their health risks.
It can help them know the side effects that various medicines can have.
Surgery simulators use Machine intelligence in training medical professionals.
- Robotic radiosurgery helps achieve precision in the radiation given to tumors, thus reducing the damage to surrounding tissues.
- Automated Online Assistants (avatars on web pages) use AI to deliver automated Customer Service at reduced costs.
- Fuzzy logic (degrees of truth logic) controllers have been developed for automatic gearboxes in automobiles.
- At Sony CSL Research Laboratory, their Flow Machines software has created pop songs by learning music styles from a huge database of songs.
- In the field of Aviation, surrogate operators use Artificial Intelligence for combat and training simulators, mission management aids, support systems for tactical decision making and post processing of the simulator data into symbolic summaries.
- British Telecommunications (and others) make use of Heuristic Search (algorithms rank next step alternatives) to manage work schedules of their technicians.
- The company ‘Narrative Science’ makes computer generated news and reports commercially available (including summarizing team sporting events based on statistical data from the game).
In 1997, a chess-playing program (Deep Blue) beat reigning World Champion Gary Kasparov.
THE ARTIFICIAL INTELLIGENCE RESURGENCE
Human-Level Artificial Intelligence has been defined as ‘AI which can reproduce everything a human can do, approximately’ and Google’s Head of Technology, Ray Kurzweil recently predicted that we will achieve Human Level AI by the year 2029.
Not everyone agrees with Kurzweil’s timescale, however there is no doubt that AI has been enjoying a major resurgence in recent times.
- The speed, availability and sheer scale of supporting infrastructures is enabling bolder algorithms to tackle more ambitious problems.
- This includes computer components which are reducing in cost and size whilst having the ability to process more data and quicker.
Cloud Computing, specifically ‘Infrastructure as a Service’, is enabling researchers to develop their ideas at a fraction of the cost leading to a proliferation of start-ups.
- The intuition by all manners of industry to collect, analyze and store every piece of available data (Big Data) has brought a high demand for solutions that go beyond simple statistical analysis of data – insights and intelligence are the order of the day.
New emerging open source technologies e.g. Hadoop is allowing speedier development of scaled AI technologies applied to large and distributed data sets.
- Larger players are investing heavily in various AI technologies e.g. IBM’s scale of investment in Watson, Google’s investment in driverless cars, DeepMind Health and DeepMind for Google.
- The public are generally more aware of Artificial Intelligence thanks in no small part to the advent and of Intelligent Virtual Assistants like Siri (developed & launched by Apple).
WEAK AI AND STRONG AI
THE FUTURE DIRECTION OF ARTIFICIAL INTELLIGENCE
Developments in the Artificial Intelligence space are already reshaping industries, enterprises and human-computer interactions.
62 per cent of Organizations will be using Artificial Intelligence (AI) by 2018 according to Narrative Science, patenting their AI creations at a faster rate than ever before.
‘Care-bots’ could prove to be a fantastic solution as the world’s populations see an exponential rise in elderly people. Japan is leading the way with a third of government budget on robots devoted to the elderly.
The goal of Strong AI is to develop Artificial Intelligence to the point where the machine’s intellectual capability is functionally equal to that of a human.
This ambitious objective is not without controversy and captivating conversations are taking place about the future of Artificial Intelligence and what it will mean for humanity.
The world’s leading experts disagree on a number of fronts e.g. future impact on the job market, when human-level AI will be developed, whether this will lead to an intelligence explosion and whether this is something we should welcome or fear.
- The truth is that the controversial development of human-level AI is not going to go away and any number of predictions are emerging as to what we may experience in the not too distant future (by the year 2029 according to Ray Kurzweil).
Pieter Abbeel (University of California) says robots will keep us safer, especially from disasters.
- Yoky Matsuoka (VP Technology, Nest) predicts that robotic limb implants will make humans better at everything.
- Thomas Dietterich (AI Advancement) hopes AI will turn us into ‘Super-Humans’ by prolonging the performance of our eyes, ears and limbs.
- Stuart Russell (University of California) says very smart computers could solve all our problems, including climate change.
- Oren Etzioni (Allen Institute for Artificial Intelligence) says AI might even save the world
- Peter Stone (University of Texas) says these changes will happen so slowly we won’t notice it at first
In truth, the possibilities and solutions that Strong AI can deliver to mankind seem endless although progress has been slow and may simply be testimony to its difficulty if not its impossibility.
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- Machine-To-Machine (M2M): Technologies and Applications
- Private: IoT and Connected Cars Technologies
– brought to you by senior research members of Telefocal Asia.