How exactly does AI work?

​Translator | Bugatti

Reviewer | Sun Shujuan

AI has become extremely important for modern businesses and other types of organizations because it can do all of the above. By combining large amounts of data with intelligent iterative processing algorithms, AI systems can learn from patterns and characteristics in the data they analyze.

Every time an AI system processes data, it tests and measures its own performance and gains new knowledge. Because AI never needs to rest, it can quickly complete thousands of tasks, learn a lot of knowledge in a short period of time, and eventually become extremely good at whatever it is trained to do.

However, to understand how AI really works, you need to understand that AI is not just a computer program or application software, but a complete discipline or science.

AI systems have many different parts, and you can think of them as subfields of the overarching science of AI.

These areas include:

• Machine learning: A specific application of AI that allows a computer system, program, or application software to learn automatically and obtain better results based on experience, All this without programming. Machine learning allows AI to find patterns in data, uncover insights, and improve the results of any task the system is designed to accomplish.
• Deep Learning: A specific type of machine learning that allows AI to learn and improve by processing data. Deep learning uses artificial neural networks that simulate biological neural networks in the human brain to process information, find connections between data, make inferences, or obtain results based on positive and negative reinforcement.
• Neural Network: The process of repeatedly analyzing a data set to find connections and interpret meaning from undefined data. Neural networks function similarly to those in the human brain, allowing AI systems to take in large data sets, discover patterns in the data, and answer questions about it.
• Cognitive computing is another important part of AI systems, designed to simulate human-computer interaction, allowing computer models to simulate the mechanism of the human brain when performing complex tasks (such as analyzing text, speech, or images).
• Natural language processing (NLP) is an important part of AI because it allows computers to recognize, analyze, interpret and truly understand human language, whether written or spoken. Natural language processing is essential for any AI-based system that interacts with humans, whether through text or voice input.
• Computer Vision – One of the most common applications of AI technology, it uses pattern recognition and deep learning to examine and interpret image content. Computer vision allows AI systems to recognize elements of visual data, such as the CAPTCHAs found everywhere online, which are learned by humans helping them identify image elements such as cars, crosswalks, bicycles, or mountains.

#What technology does AI require?

AI is not new, but due to significant advances in technology, it has been widely used and used in an increasingly wide range of applications in recent years.

In fact, the explosive growth in the scale and value of AI is closely related to recent technological advances, including:

• Larger and more accessible data sets—AI relies on Data is booming. As data grows rapidly and access to data becomes easier, the importance of AI increases. Without developments like the “Internet of Things,” AI would have far fewer potential applications.
• Graphics Processing Units – GPUs are one of the key factors driving the value of AI, as they are critical for providing AI systems with the ability to perform the millions of calculations required to perform interactive processing. GPUs provide the computing power AI needs to quickly process and interpret big data.
• Intelligent Data Processing - New and more advanced algorithms allow AI systems to analyze data faster and at multiple levels simultaneously, helping these systems analyze data sets extremely quickly so that they can perform better and faster Understand complex systems and predict rare events.
• Application Programming Interfaces – APIs allow AI capabilities to be added to traditional computer programs and software applications, actually making those systems and programs smarter by enhancing their ability to recognize and understand patterns in data.

Original title: ​​But how does AI actually Work?​​ ​, Author: Annoberry​

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