Artificial intelligence (AI) is a branch of computer science that uses computing and related technologies to simulate, extend and expand human intelligence, with the goal of using algorithms and technologies to train converter models through generative training, and computer programs and technologies that think and solve problems in a way similar to human intelligence when input prompts; Commonly used AI such as autonomous driving, smart furniture, ChatGPT, etc.
The development goals of artificial intelligence vary in different stages and application scenarios, but in general, there are mainly the following aspects:
1.ChatGPT: A chatbot service that enables the knowledge model to think, learn and understand like a human through prompt training. In recent years, enterprises have accumulated enough project knowledge base, trained customer service, and provided Q&A services for system users, including natural language processing, image recognition, speech recognition, machine learning and other fields of research, aiming to enable machines to understand and process human language, images and voices and other information, as well as learn and reason from data, thereby reducing costs and improving revenues.
2.Deep learning: With artificial intelligence, computers can automatically learn and improve through large amounts of data, enabling efficient learning and decision-making. Deep learning is an important branch in the field of artificial intelligence, which uses neural network models to simulate the learning process of the human brain, so as to achieve automatic feature extraction and classification of complex data. Deep learning has made significant progress in many fields and is gradually being applied to real life and work, improving efficiency and accuracy.
In the medical field, deep learning technology can assist doctors in disease diagnosis and program formulation. By analyzing medical image data, deep learning models can identify tumors, lesions and other abnormalities, providing doctors with a more accurate and objective basis for diagnosis.
In the financial sector, deep learning technology also plays an important role. For example, in terms of risk assessment, deep learning models can accurately assess the credit status and potential risks of enterprises by mining and analyzing large amounts of financial data, and provide decision support for banks and other financial institutions.
2.Image recognition: Image recognition refers to the technology that uses computers to analyze and understand images to identify objects and objects in a variety of different patterns. This technique can perform pre-processing of the image, such as denoising, smoothing, transformation, etc., to enhance the important features of the image. Mainly used in graphic design, etc.; Commonly used software, stable diffusion, etc.
Figure 2 Stable Diffusion official website.
Artificial intelligence can be classified according to different criteria.
1. According to the computing power, it is divided into three categories: weak artificial intelligence, strong artificial intelligence and superartificial intelligence.
Weak AI is only focused on completing a specific task and cannot truly understand the meaning of the information.
Strong AI systems include learning, language, cognition, reasoning, creativity, and planning, with the goal of processing never-before-seen details in an unsupervised learning environment, understanding human information, and learning interactively with humans.
Super-artificial intelligence refers to the fact that by simulating human intelligence, artificial intelligence begins to have the consciousness of independent thinking, forming a new intelligent group, and can think alone like humans.
2. Another way to classify artificial intelligence is to divide artificial intelligence into cognitive AI, machine learning AI and deep learning.
Cognitive AI is the most popular branch and is responsible for all interactions that feel "human-like", able to deal with complexity and ambiguity, and constantly learning.
Machine learning AI refers to a model trained by a large amount of data in a specific field, which can make decisions and ** autonomously.
Deep learning is a subfield of machine learning, inspired by the neural networks in the human brain, by building deep neural network models to process large-scale data, to achieve more accurate and efficient learning**.
In general, there are various ways to classify AI, and different classification methods reflect the different characteristics and application scenarios of AI.