Introduction to conventional computing system
In the current era the technology worked very rapidly in the world due to this the artificial intelligence system and as well as the traditional and conventional computing system are both significant equally. Whereas both systems are the important part of the modern computing system, but both systems have different worked approached as they have different functions and application. It’s necessary to understand the differences of both systems to use the application and as well as to run the functions.
Traditional Computing Systems
The Traditional computing systems is the backbone of the technology for many years, and it’s also called as traditional computing. This system has the binary logic system where the operations worked in binary language and are performed the task by using the series of already installed instructions and also the rules.
The history of traditional computing start from the early 20th century when the first electronic computer ENIAC is developed in 1945.
Traditional computing systems are the combination of many basic architecture such as memory, CPU, storage and as well as the input/output devices. They worked good in many complicated and repetitive tasks, operating systems, databases, and also for the business applications.
What is Artificial Intelligence?
Artificial Intelligence is the whole new technology. Generally, AI means the creating device or machines from where we can get all information and do the things the human intelligence wanted. Furthermore, one can learn from the experience and also can understand the many languages and then made the decision of their choice.
AI can be split into three main types:
- Narrow AI: Narrow AI is used for the specific tasks such as the voice recognition and for the image classification.
- General AI: General AI is used for the theoretical form of AI that can do any work that a human intelligence can.
- Superintelligent AI. This AI is more intelligent than humans in all way.
Key differences between AI and traditional computing
Learning and Adaption
The main differences present between the AI and traditional computing is all learning process and as well as the adaptation processes. Moreover, the traditional computing systems are not moveable that is static, this means this system is based on fixed instructions. Whereas the AI systems are moveable that is it is dynamic this system is not based on the fixed instructions, they can learn from the given data and get better and better with the passage of time without any being programmed.
Methods
Traditional computing system have the rule-based technology. These systems have the instructions and rules for the any kind of answer. This system uses the data driven methods. Machine learning algorithms need the large data to find patterns and for making predictions, which are the more flexible and are the creative solutions.
Decision Making
Traditional computing has the limitation for the preprogrammed rules and instructions. The decisions can make by using the data analysis with the help of AI. Therefore, the AI can handle calmly all the complex and the ambiguous situations better.
Data Processing
Traditional systems are good for the structured data. They easily process the data in databases more efficiently. Artificial intelligence can also process the unstructured and unorganized data such as images, audio and text etc., so it’s more unique and versatile with different sort of data.
Speed and Efficiency
Sometime the AI systems outperform the conventional computing of processing the speed and its efficiency, mostly for the complex tasks. AI has the ability to process parallel by the use of specialized hardware such as GPUs and TPUs etc. are contributed to increase the performance.
Technological Foundations
Hardware Requirements
Conventional computing systems mainly depend on the CPUs for performing the tasks. AI have the advanced level of hardware such as Graphics Processing Units GPUs and Tensor Processing Units TPUs that help to accelerate the machine learning computations.
Software and Algorithms
Traditional computing has the advanced algorithms which are designed for performing the specific tasks. AI have the machine learning algorithms which adapt and generate the data by giving inputs and making them more useable, flexible and also powerful.
Data
AI have the data on large scale. By Having the data on large scale is the functional key to train the AI models. As Deep learning needs the huge amount of data to get the accuracy. Whereas the Traditional systems are less dependent on the big data.
Applications and Use Cases
Traditional Computing Applications
Traditional computing systems are used in business, operating system and the database management system. They are used worked that require more reliability and the predictability.
AI Applications
AI applications are used in healthcare, finance and different autonomous vehicles. AI also help in the medical diagnostics and predicts the stock market trends and as well as for the powers self-driving cars. They are very unique, versatile and powerful source.
Advantages and Disadvantages
Advantages of Traditional Computing
Reliability: It makes the systems with predictable performance.
Cost: They are Generally cheaper to impose, implement and as well as to maintain.
Advantages of AI
Flexibility: Theses helps to Adapts to new data and evolving the conditions.
Accuracy: It Improved the accuracy and precision in tasks such as image and the speech recognition.
Complexity Handling: It Excels the vast data and also in analyzing vast, unstructured and unorganized datasets.
Disadvantages of Traditional Computing
Adaptability: It has the less ability to learn the new things and adapt to new information.
Innovation: It Restricted to already present rules and instructions.
Disadvantages of AI
Ethical Concerns: They have the many Issues which are related to privacy, bias and the job displacement.
Cost: High implementation and need the maintenance costs.
Complexity: It Requires the specialized knowledge and resources as well.
Future Prospects
The future of computing is because of both AI and traditional systems. Emerging trends in AI are natural language processing, robotics and as well as the cognitive computing. Traditional computing is evolving with the help of quantum computing and the edge computing system. The combination of artificial intelligence and traditional systems will be unlocking the new possibilities and the drive technology in future.
Summary
In this article AI and traditional computing are very different and have their own capabilities and as well as strengths, they can also be complementary to each other. The Traditional computing is more reliable and are inexpensive, whereas the AI is more flexible and solve the problems in all the filed. After understanding and using both system we can used both tech landscape better and innovate more and more.