Progress in artificial intelligence
Artificial intelligence has been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, scientific discovery and toys. However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore." "Many thousands of AI applications are deeply embedded in the infrastructure of every industry." In the late 90s and early 21st century, AI technology became widely used as elements of larger systems, but the field is rarely credited for these successes.
To allow comparison with human performance, artificial intelligence can be evaluated on constrained and well-defined problems. Such tests have been termed subject matter expert Turing tests. Also, smaller problems provide more achievable goals and there are an ever-increasing number of positive results.
The broad classes of outcome for an AI test are:
- optimal: it is not possible to perform better
- strong super-human: performs better than all humans
- super-human: performs better than most humans
- par-human: performs similarly to most humans
- sub-human: performs worse than most humans
- Connect Four
- Rubik's Cube
- Computer poker players, sub-human for full ring Texas hold 'em (approaching strong super-human in simpler versions of poker)
See also solved games.
- Backgammon: super-human
- Bridge: nearing strong super-human
- Chess: nearing strong super-human
- Crosswords: super-human
- Driving a car: super-human. Google driverless cars are safer and smoother when steering themselves than when a human takes the wheel.
- Jigsaw puzzles: strong super-human
- Reversi: strong super-human
- Scrabble: strong super-human
- Quiz show question answering: strong super-human
- Optical character recognition for printed text (nearing par-human for Latin-script typewritten text)
- Handwriting recognition
- Object recognition
- Speech recognition
- Word-sense disambiguation
- Natural language processing
- Most everyday tasks performed by humans.
- Applications of artificial intelligence
- List of artificial intelligence projects
- List of emerging technologies
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- There are several ways of evaluating machine translation systems. People competent in a second language frequently outperform machine translation systems but the average person is often less capable. Some machine translation systems are capable of a large number of languages, like google translate, and as a result have a broader competence than most humans. For example, very few humans can translate from Arabic to Polish and French to Swahili and Armenian to Vietnamese. When comparing over several languages machine translation systems will tend to outperform humans.