Over 900 different fields of expertise, computer science ranks first in the professional rankings of top universities worldwide.
Global telecommunications, international business, medical breakthroughs, distance education, online shopping, online dating, and various applications of the Internet, these amazing things also make the computer science profession famous. Its scale and complexity are also growing rapidly.
With the release of ChatGPT, artificial intelligence has become a new hot topic, once again driving the application of computer science projects.
So, Binle takes everyone to comprehensively analyze the field of artificial intelligence.
What is artificial intelligence?
Artificial Intelligence is a branch of computer science that can accomplish tasks that traditionally require human intelligence through the use of computers. Artificial intelligence can process large amounts of data in ways that humans cannot process. The goal of artificial intelligence is to be able to recognize patterns, make decisions, and make judgments like humans.

AI attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a way similar to human intelligence. These systems and machines can replicate the learning, reasoning, and problem-solving abilities of human thinking to varying degrees.
The commonly used technologies such as autonomous driving, facial recognition, speech recognition, and user interest based intelligent algorithm recommendation also fall within the scope of artificial intelligence.
Artificial intelligence can be divided into six major fields:
1. Machine Learning

Machine learning is an artificial intelligence feature that allows computers to automatically acquire data and learn from difficulties or instances they encounter without programming. Machine learning emphasizes the development of algorithms that can analyze data and generate predictions. Its main application is in the field of healthcare, for disease diagnosis and medical scanning interpretation.
Fundamentally, it is the science that enables machines to translate, execute, and study data to solve real-world problems. It basically focuses on applications that adjust based on experience and improve their decision-making potential or predictive accuracy over a period of time.
In the past few years, it has brought us autonomous vehicle, image and voice recognition, demand forecasting models, useful web search and a wide range of applications.
2. Neural Network
By stacking multiple perceptrons, neural networks combine the neural system of the human brain with machines to perform tasks. Neural networks collect information by processing various training instances, and then encode brain neurons into systems or machines.
Simply put, a neural network is a set of algorithms used to find element relationships between data strings by imitating the process of human brain operations.
Neurons in neural networks are mathematical functions that collect and classify information based on specific structures, and the network strongly implements various statistical techniques to complete tasks. Due to the application of various learning models, this data analysis process will also provide answers to many previously unresolved related issues.
From prediction to market research, they are widely used for fraud detection, risk analysis, stock trading prediction, sales prediction, and so on.
3. Robotics
Nowadays, with the continuous advancement of technology, robotics technology is a rapidly developing field. Research, design, and build new robots to serve various practical purposes, whether it is for home, business, or military purposes.

Robotics integrates many other fields such as mechanical engineering, electrical engineering, information engineering, computer engineering, mathematics, etc. It involves the design, construction, operation, and use of robots. The goal of robotics technology is to design machines that can assist and assist humans.
Machines developed through robotics technology can replace humans and replicate human behavior. Robots can be used for various purposes in various situations, but many robots are also used in hazardous environments (including inspecting radioactive materials, bomb detection), or in places where humans cannot survive (such as space, underwater), as well as cleaning up harmful substances and radiation.
4. Expert System
Expert systems refer to computer systems that mimic the decision-making intelligence of human experts. These systems are designed for specific fields such as medicine, science, etc. It performs this operation by using inference and inference rules based on user queries to extract knowledge from its knowledge base.
The performance of expert systems is based on the expert knowledge stored in their knowledge base. The more knowledge stored in the knowledge base, the greater the improvement in system performance. Its main features include sensitivity, reliability, ease of understanding, and strong execution.
In 1970, the first expert system was introduced. By extracting knowledge stored in his knowledge base, he was identified as the expert who could solve the most complex problems at the time.
5. Fuzzy Logic
In the real world, sometimes we face situations where it is difficult to identify whether conditions are true, and their fuzzy logic provides relevant flexibility for reasoning, leading to inaccuracies and uncertainties in any condition.
The term fuzzy logic was introduced in 1965 when mathematician Lotfi Zadeh proposed the theory of fuzzy sets. Simply put, fuzzy logic is a technique that represents and modifies uncertain information by measuring the accuracy of assumptions. Fuzzy logic is also used for reasoning about concepts of natural uncertainty. Fuzzy logic can facilitate and flexibly implement machine learning techniques, and help to logically mimic human thinking.

Fuzzy logic is just a form of standard logic, where one concept represents any real number between 0 and 1. If the concept is completely correct, the standard logic is 1, and the completely incorrect concept is 0. But in fuzzy logic, there is also an intermediate value that is partially true and partially false.
6. Natural Language Processing
As a computational processing technology for human language, NLP can help computers and humans communicate through natural language. It enables computers to read and understand data by imitating human natural language.
NLP is a method for searching, analyzing, understanding, and exporting information from textual data. Computers can use this aspect of artificial intelligence to interpret, recognize, locate, and process human language and speech, with the most common applications being text translation, sentiment analysis, and speech recognition.
The purpose of introducing this component is to make the connection between machines and human language as seamless as possible, so that computers can logically respond to human speech or queries.
The employment prospects of artificial intelligence
With the continuous development of technology and the expansion of applications, the demand for artificial intelligence professionals is also increasing. The average annual salary for a master's degree in artificial intelligence in the United States is $102000.

Popular positions include: artificial intelligence engineer, data scientist, machine learning engineer, computer vision engineer, etc. Employment directions include technology companies such as Google, Amazon, Microsoft, Apple, and IBM, financial institutions such as banks, insurance companies, and investment institutions, healthcare institutions, and biotechnology companies.

人工智能神校盘点

1. Carnegie Mellon University CMU
As the leading figure in the field of CS in the United States, CMU has consistently ranked first in undergraduate and master's programs in CS for many years. As one of the few schools dedicated to computer science, CMU has launched a new master's program at its Pittsburgh campus - the Master of Engineering Artificial Intelligence (MSc in Engineering Artificial Intelligence, abbreviated as MS EAI). This project mainly studies the theory, methods, and applications of artificial intelligence, and provides many practical courses, including machine learning experiments, intelligent control experiments, etc.

2. MIT
MIT is one of the prestigious institutions in the field of artificial intelligence. As one of the top scientific and engineering institutions in the world, MIT has a long research tradition in the field of artificial intelligence. Since the 1950s, the Massachusetts Institute of Technology has made significant breakthroughs and contributions in the fundamental theory and application research of artificial intelligence. The artificial intelligence program at MIT emphasizes interdisciplinary integration. Students can deepen their understanding and application of artificial intelligence by collaborating with other disciplines such as computer science, psychology, neuroscience, physics, etc.

3. Stanford University
The Artificial Intelligence program at Stanford University is renowned for its outstanding educational and research achievements. Stanford University emphasizes the combination of theory and practice, providing a practice oriented teaching method. Students can apply their knowledge to solve practical problems and cultivate innovative thinking and practical skills by participating in laboratory projects, research centers, entrepreneurial projects, and internship opportunities. Students can choose to delve deeper into multiple fields such as machine learning, deep learning, natural language processing, computer vision, and participate in cutting-edge research projects.

4. University of California, Berkeley UCB
The University of California, Berkeley is located in the Silicon Valley region, at the center of innovation and entrepreneurship, with a geographical advantage in learning artificial intelligence. Schools work closely with technology companies, entrepreneurial incubators, and investment institutions to provide students with abundant innovation and entrepreneurial resources. Students can participate in entrepreneurship projects, technology incubators, and entrepreneurship competitions to transform artificial intelligence technology into commercial solutions.

Although artificial intelligence is currently one of the top majors, one should not make hasty choices. The key to success is to complement one's own strengths and skills. In the increasingly fierce competition for artificial intelligence applications, the schools applying must have a gradient. For more related application questions, you can add Binle Mentor for free consultation!