The term "artificial intelligence" or "AI" was coined at the 1956 Dartmouth conference. The generally accepted definition is the Turing test, first proposed in 1950, as the ability of a machine communicating using natural language over a teletype to fool a person into believing it was a human. "AGI" or "artificial general intelligence" extends this idea to require machines to do everything that humans can do, such as understand images, navigate a robot, recognize and respond appropriately to facial expressions, distinguish music genres, and so on.
We want AGI for two reasons. People don't want to work and don't want to die. First, we pay people USD $75 trillion per year worldwide to do work that machines aren't smart enough to do. Some people oppose this out of fear that robots will put everyone out of work, but this is not the case. We have already been automating labor for hundreds of years and we are better off for it. Machines are already stronger, faster, and in many ways smarter than humans, but we still own them for our benefit. Instead of replacing us, they make us more productive and increase our earnings.
The second reason is more controversial and not generally accepted, even among transhumanists. But one of the requirements of AGI is to model (predict) the behavior of individual humans. As humans, we do this all the time to facilitate communication with others. We can save words by guessing what the other person knows and doesn't know. Given enough observation time and data, we could develop very accurate models of human minds. Now suppose that we built a robot that looked like you and programmed it to carry out its predictions of your actions in real time. To everyone that knew you, the robot would be you.
If I presented you with your robotic copy and offered you the option to shoot yourself to become immortal, I doubt that you would. But uploading your mind (with the ability to make backups) won't be presented this way. If I offered to turn on the robot at the moment of your death, you might decide differently. Or maybe your relatives or loved ones would make the decision for you. Or perhaps you would just see people go in for a procedure where they come out younger, stronger, smarter, and happier in their new robotic bodies.
We don't "need" AI but we want it. AI is an enormously difficult problem, but the incentive to solve it is also enormous. The ROI on automating human labor is world GDP divided by interest rates, or about $1 quadrillion. The ROI on immortality is world GDP times life expectancy, or about $5 quadrillion.
The human brain and body are enormously complex, but I do not believe the technical obstacles are insurmountable. A human brain sized neural network with 10^14 synapses and 10 ms response time would require a 10 petaflop supercomputer and 100 terabytes of memory. I estimate that the software, if it had the same information content as our genome, would be roughly 100 million to 1 billion lines of code.
The central goals of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. General intelligence is still among the field's long-term goals. There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. The AI field is interdisciplinary, including computer science,
mathematics, psychology, linguistics, philosophy and neuroscience, as well as other specialized fields such as artificial psychology.
A much better definition of AI would be, IMO, "To make computers easily do all that which comes easy to humans". Computers need to be able to read, write, navigate a changing world full of other agents with goals at odds with its own, to *learn* how to walk gracefully, to get better at any task *with practice*.
These are all human traits that underlie our ability to learn to play chess and solve integrals. Starting with the final skill (logic based reasoning, math, games) is the wrong approach. AI should be based on educating a simple machine capable of learning anything. This is much easier than we have previously thought.
Thanks to early thinkers, artificial intelligence became increasingly more tangible throughout the 1700s and beyond. Philosophers contemplated how human thinking could be artificially mechanized and manipulated by intelligent non-human machines.
The thought processes that fueled interest in AI originated when classical philosophers, mathematicians, and logicians considered the manipulation of symbols (mechanically), eventually leading to the invention of a programmable digital computer, the Atanasoff Berry Computer (ABC) in the 1940s. This specific invention inspired scientists to move forward with the idea of creating an “electronic brain,” or an artificially intelligent being.
Characteristics of a AI
1. Feedback (learning from sensors)
Feedback (learning from self created symbolic representations of a model of their environment) (we call this thought)
2, The ability to visualise (see images - computers process images but they do not see them - we see the result . (The philosophers call the internalise experiences such a seeing and feeling qualia) The computer people are not usually aware of such phenomena.
3, The ultimate Quale (singular form) is consciousness. With this ability you can model outcomes from mental images. The process we call evolution has supplied us with a series of generic actions called goals which allow us to use a form of decomposition and reduce a generic action to a sequences of real actions. With this you can use language (discourse production), mathematics and even programming
Thus AI or machines with intelligence have very little to do with computing
4, Popular AI (or computer-orientated hype over the label AI) Everything you hear about tends to belong to this category. Machine learning, artificial neural networks. Big Data techniques, Data mining techniques - all computing in a sort of heuristic semi-numerical techniques way. The only possible exemption is real-time robotics.
Currently we are not progressing AI any more than we have done in the last 50+ years. The only real example (not called AI) is ourselves.
Google CEO said AI will have a bigger impact on humanity than some of the other well-known innovations.
AI is basically of two types-
1). Weak AI
2). Strong AI
1). Weak AI- Weak AI is designed to complete a particular task. It helps to solve the specific problems. Weak AI is bounded by the set of rules and it works according to it.
Weak AI can also be called narrow AI because it focuses on narrow tasks and does the best job in it.
The best examples of weak AI can be apple's SIRI, and the robots used in manufacturing products.
2). Strong AI- Strong AI can simulate the actions performed by human beings. It has an understanding of power and thinking capacity like the human brain.
Strong AI can also be known as Full AI as it can entirely equate with the human brain.
The best example of strong AI can be the robots used in Hollywood movies.
Applications of AI
1, Gaming − AI plays crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where machine can think of large number of possible positions based on heuristic knowledge.
2, Natural Language Processing − It is possible to interact with the computer that understands natural language spoken by humans.
3, Expert Systems − There are some applications which integrate machine, software, and special information to impart reasoning and advising. They provide explanation and advice to the users.
4, Vision Systems − These systems understand, interpret, and comprehend visual input on the computer. For example,A spying aeroplane takes photographs, which are used to figure out spatial information or map of the areas.Doctors use clinical expert system to diagnose the patient.Police use computer software that can recognize the face of criminal with the stored portrait made by forensic artist.
5, Speech Recognition − Some intelligent systems are capable of hearing and comprehending the language in terms of sentences and their meanings while a human talks to it. It can handle different accents, slang words, noise in the background, change in human’s noise due to cold, etc.
5, Handwriting Recognition − The handwriting recognition software reads the text written on paper by a pen or on screen by a stylus. It can recognize the shapes of the letters and convert it into editable text.
6, Intelligent Robots − Robots are able to perform the tasks given by a human. They have sensors to detect physical data from the real world such as light, heat, temperature, movement, sound, bump, and pressure.
Conclusion
In future, slowly but surely, AI will take over classroom and will revolutionaries the educational industry.
AI has heavily influenced different sectors that we may not recognize. It is now a very important part of linguistics, mathematics, neuroscience, philosophy and psychology as well. John McCarthy, one of the founders of AI, once said that “as soon as it works, no one calls it AI anymore.”
Artificial intelligence is going to change how humanity thinks about the role of culture, god, faith, reality and
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