A branch of Computer Science called Artificial Intelligence (AI) pursues creating computers/machines as intelligent as human beings. John McCarthy the father of Artificial Intelligence described AI as, “The science and engineering of making intelligent machines, especially intelligent computer programs”. Artificial Intelligence (AI) is a branch of Science that deals with helping machines find solutions to complex problems in a more human-like fashion. This generally involves borrowing characteristics from human intelligence and applying them as algorithms in a computer-friendly way. Artificial intelligence courses in Bangalore have risen in demand due to the vast majority of job opportunities.
A flexible or efficient approach can be taken depending on the requirements established, which influences how artificial the intelligent behavior appears. Artificial intelligence courses in Bangalore offer government-certified education standards & support to guarantee a stable future for future AI specialists.
AI Approaches
The difference between machine and human intelligence is that humans think/act rationally compared to machines. Historically, all four approaches to AI have been followed, each by different people with different methods. Develop formal models of knowledge representation, reasoning, learning, memory, and problem-solving that can be rendered in algorithms. There is often an emphasis on provably correct systems and guarantees of finding an optimal solution.
- Act Well
- For a given set of inputs, generate an appropriate output that is not necessarily correct but gets the job done.
- A heuristic (heuristic rule, heuristic method) is a rule of thumb, strategy, trick, simplification, or any other kind of device that drastically limits the search for solutions in large problem spaces. Heuristics do not guarantee optimal solutions; in fact, they do not guarantee any solution at all: all that can be said for a useful heuristic is that it offers solutions that are good enough most of the time.
- Think like humans or Cognitive science approach
Focus not just on behavior and I/O but also look at the reasoning process. The Computational model should reflect “how” results were obtained. Provide a new language for expressing cognitive theories and new mechanisms for evaluating them. GPS (General Problem Solver): The goal is not just to produce humanlike behavior (like ELIZA), but to produce a sequence of steps of the reasoning process that is similar to the steps followed by a person in solving the same task.
Applications of Artificial Intelligence
In 1981 Artificial Intelligence became an Industry means the theories and techniques proposed in Artificial Intelligence literature were accepted by Industries and they started investing in the area of Artificial Intelligence. The concepts of Artificial Intelligence are implemented in various fields along with artificial intelligence courses in Bangalore. A few of them are listed as follows.
- Game Playing
AI plays a crucial role in strategic games such as chess, poker, tic-tac-toe, etc., where machines can think of a large number of possible positions based on heuristic knowledge.
- 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, changes in human noise due to cold, etc.
- Intelligent Robots
Robots have sensors to detect physical data from the real world such as light, heat, temperature, movement, sound, bump, and pressure. They have efficient processors, multiple sensors, and huge memory, to exhibit intelligence.
- Understanding Natural Language
The computer can now understand natural languages and hence humans can now interact using natural spoken languages. The computer has to be provided with an understanding of the domain the text is about, and this is presently possible only for very limited domains.
- Expert Systems
A “knowledge engineer” interviews experts in a certain domain and tries to embody their knowledge in a computer program for carrying out some task. How well this works depends on whether the intellectual mechanisms required for the task are within the present state of AI. When this turned out not to be so, there were many disappointing results. One of the first expert systems was MYCIN in 1974, which diagnosed bacterial infections of the blood and suggested treatments. It did better than medical students or practicing doctors, provided its limitations were observed. Namely, its ontology included bacteria, symptoms, and treatments and did not include patients, doctors, hospitals, death, recovery, and events occurring in time. Its interactions depended on a single patient being considered.
Since the experts consulted by the knowledge engineers knew about patients, doctors, death, recovery, etc., it is clear that the knowledge engineers forced what the experts told them into a predetermined framework. The usefulness of current expert systems depends on their users having common sense. Artificial intelligence courses in Bangalore provide a platform for AI enthusiasts across domains to integrate artificial intelligence with their present operational approach.
