Artificial Intelligence Technology Classification

After more than sixty years of development, artificial intelligence technology currently focuses on six major areas of research, namely machine learning, computer vision, natural language processing, knowledge representation, automatic reasoning and robotics.

With the development of big data, currently machine learning, computer vision and natural language processing related technologies have received widespread attention, and some Agents (artificial intelligence products) based on machine learning technology have been gradually deployed into production environments. (Recommended learning: PHP Video Tutorial)

Although the market is currently clamoring for artificial intelligence, and many large Internet companies have begun to deploy in the field of artificial intelligence, the field of artificial intelligence is still in a state of turmoil. In the early stages of industry development, current artificial intelligence products are still in the "weak artificial intelligence stage", and agents still have many requirements for operating scenarios.

The development and application of artificial intelligence technology requires the support of a series of technologies, including Internet of Things technology, cloud computing technology, edge computing technology, big data technology, etc.

The steps of machine learning include data collection, data sorting, algorithm design, algorithm implementation, algorithm training, algorithm verification and algorithm application. Algorithm design is the core of machine learning, and data collection It is the basis of machine learning. Therefore, with the support of big data, machine learning has developed to a certain extent in the big data era. Simply put, the larger the amount of data, the better the effect of machine learning will be.

Computer vision is the science of making computers see. Machine vision uses cameras, analog-to-digital conversion, and digital signal processing to capture and analyze visual information. It is often compared to human vision, but machine vision is not bound by biology and can be programmed to see through walls. It is used in a variety of applications from signature recognition to medical image analysis. Computer vision, which focuses on machine-based image processing, is often confused with machine vision.

Natural Language Processing (NLP) is the processing of human rather than computer language through computer programs. One of the older and most famous examples of NLP is spam detection, which looks at the subject line and text of an email and determines whether it is spam. Current NLP methods are based on machine learning. NLP tasks include text translation, sentiment analysis, and speech recognition.

Knowledge representation is a branch of machine learning that focuses on identifying patterns in data.

Robotics technology is an engineering field focused on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. They are used on assembly lines in automobile production or by NASA to move large objects in space. Recently, researchers are using machine learning to build robots that can interact in social environments.

At present, our country is continuing to promote the upgrading of the industrial structure, and networking and intelligence are important contents of the upgrading of the industrial structure. Therefore, the future development space of artificial intelligence technology is still very worth looking forward to. Behind the upgrading of the industrial structure must be the upgrading of the talent structure. Therefore, for professionals, mastering certain artificial intelligence technologies will enhance their workplace competitiveness to a certain extent.

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