How Practical and Conventional Artificial Intelligence are different

Artificial intelligence and machine learning are one of the words that worth the buzz, it has moved much beyond the concept of robotic movies and lab research; it has entered into our day to day life. Our smallest of the activity is being influenced by it. So when we hear or talk about artificial intelligence what comes to our mind first is still the vision of some sci-fi movie. But the truth is that AI is being incorporated in the smart software development which enables the task accomplishment so easily. Now we are being more focused on giving each and every discretionary details to machine like humans. In short, we are working hard to give a human life to machines through the processing of a vast number of details and data which was made available to them. Much development from booking a cab for the ride to using the Google map for the different geo-location through mobile application, we are being influenced by AI.

With technological development, the world of AI is also expanding with new updates that occur with every passing second; new up-gradation is constantly being made on the outlook of the artificial intelligence industry also. In this article, we will also try to understand the two different ideology on which artificial intelligence is based that is conventional artificial intelligence and practical artificial intelligence, but first let's just have a look at some of the basics of artificial intelligence like what is AI and how it works and why it is needed at all.

What is AI and why is it needed?

Artificial intelligence is defined as the stimulation of the human behavioral process by the machine specifically the computers. Such a process may include the learning, information about rules and regulations for accessing any information and reasoning that is using these rules and regulations to reach a conclusion that is approximately definite in nature. AI enables the machine to do self-corrections too. The most popular aspect of AI contains speech organization, machine sensors, and expert systems.

In other words we can say that artificial intelligence os the intersectional ad interdisciplinary science that focuses on the construction of the machines that are capable of performing the task which might require complex human intelligence, it has multiple layers and approaches to it which has vast explanation, but no doubt we can say that artificial intelligence has brought a definite change in the technology industry especially the virtual industry.

The main reason for which everyone will agree is the creation of the expert system that has the power to exhibit the behavior which is intelligent on the other hand is capable of learning more, demonstrating the issues and advice accordingly.

Also, this will help the machine to find better solutions to the problems that are complex and apply them as per the human behavior and algorithm for a computer-friendly result.

Application of artificial intelligence can be found in gaming, speech processing, and recognition system, healthcare industry, and automobiles.

Conventional and Practical Artificial Intelligence

the whole artificial Intelligence methodology is based on two schools of thought - conventional and computational intelligence.

Conventional Artificial Intelligence

Conventional AI mostly involves matter like machine learning. It is more focused and revolves around the statistical calculations and outcome. This can also be presented as a formula basis. This field of AI is also known as symbolic AI, neat AI or logical intelligence. Conventional AI is the one that represents the collection of the components and methods which are based on the logic answering of the problems. This was the most famous form of AI which was popular in the mid-90s and was given name old fashioned artificial intelligence or GOFR, as the philosophical implications of artificial intelligence was still a new factor in the 90s, the focus is on the intelligence aspect.

Conventional AI methodology contains

• Expert system - This implies the reasoning capabilities that are used for reaching a particular conclusion. The artificial intelligence-enabled expert machine can process a huge amount of information which is known and this machine will deliver solution and reactions based on this information.
• Case-based reasoning - This is the process that helps in the solving of new issues which are based on the memory of the past occurs problems.
• Bayesian network -  This represents the set of different variables in the same frame that has a joint probability of the distribution with their own independent expressions and assumptions.
• Behaviour-based AI - This mainly consists of the AI system which was developed to behave just as human intelligence, by humans own hands. This uses the human perception to reach a conclusion. This may include reasoning too.

The researchers in conventional artificial intelligence are based on the finding solution that could exactly mimic humans through the manipulation of their symbols that are structurally based on knowledge of the past. This approach of conventional artificial intelligence restricts itself in the changing

Practical Artificial Intelligence

Practical artificial intelligence is the present-day modification that is rooted more in the present day to day uses of the AI. It is the most valuable application of the intelligence that can be accomplished by the machines. With the advancement of time, more focus has been shifted to find out the economic boost in the use of artificial intelligence that has given birth to practical AI.

The main aim of practical AI is to have a practical approach in integration of the machine learning as well as the artificial intelligence in various practical fields like software development with changes with the scenario of the technology all across the globe.

As per Lotfi Zahid, finding or possessing more better computational tools and methods (practical artificial intelligence) which should be far more influential than the old system (conventional artificial intelligence) of the predictive logical methodology based design system of intelligence that represent the core conventional traditional AI is becoming the aim of many AI-driven companies. In the initial period’s machine were designed in such a way so that the symbols could be easily used to process the inputs in such a way that they are certain but this might contain uncertainty. But now the focus is being shifted to make the artificial intelligence being practically available and accessible to all.

When most of the modern data intelligence or the practical AI is directed toward the direction of finding specific sub-problem and its solution like in the medical field how robotics are governing the field of surgery through the automated system of information specific to the knowledge, the conventional AI is indented to produce the genre feature on the machine which are not point oriented but much human generalized behaviour. This may require no or minimal intelligence and reasoning just an initial designing that contain input and output which were represented in the form of the symbols.

The biggest drawback of such technology was that it stressed on the use of logic that makes it more and more fuzzier, also known as soft or weak AI. To fight with these shortcomings of the symbolic or conventional AI, the idea of intelligent computation come into the force at least inspired to do so. The whole idea of emphasis on the logic and formal representations of the code of the knowledge which makes the approach pretty much bottoms up.

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