01. Self-driving cars
Autonomous vehicles are a type of intelligent vehicle, also known as wheeled mobile robots. They primarily rely on an in-vehicle intelligent driving controller, mainly composed of a computer system, to achieve autonomous driving. The technologies involved in autonomous driving encompass multiple aspects, such as computer vision and automatic control technology.
Developed countries such as the United States, the United Kingdom, and Germany began researching self-driving cars in the 1970s, while China started its own research in the 1980s. In 2005, a self-driving car named Stanley completed a race track in the Mojave Desert in the United States at an average speed of 40 km/h, covering a distance of approximately 282 kilometers in 6 hours, 53 minutes, and 58 seconds. Stanley was a modified Volkswagen Touareg, a collaborative project between Volkswagen's Technical Research Department, the Electronics Research Laboratory of the Volkswagen Group, and Stanford University. Its exterior was equipped with cameras, radar, and laser rangefinders to sense the surrounding environment, while its interior featured an autonomous driving control system to handle commands, navigation, braking, and acceleration. In 2006, Carnegie Mellon University developed the self-driving car Boss, which could safely drive through streets near an air force base, following traffic rules and avoiding other vehicles and pedestrians.
In recent years, with the rise of artificial intelligence, autonomous driving has become a hot topic, and many companies both domestically and internationally have invested heavily in research on autonomous and driverless vehicles. For example, Google's Google X lab is actively developing the Google Driverless Car, and Baidu has launched its "Baidu Autonomous Vehicle" R&D program; its self-developed autonomous vehicle, Apollo, even made an appearance at the 2018 CCTV Spring Festival Gala. However, in the past two years, it has been discovered that the complexity of autonomous driving far exceeds expectations from a few years ago, and there is still a long way to go before it can be truly commercialized.
02. Facial Recognition
Facial recognition, also known as portrait recognition or face recognition, is a biometric technology that identifies individuals based on their facial features. The technologies involved in facial recognition primarily include computer vision and image processing.
Research on facial recognition systems began in the 1960s. With the development of computer and optical imaging technologies, facial recognition technology improved significantly in the 1980s. In the late 1990s, facial recognition technology entered its initial application stage. Currently, it is widely used in various fields, such as finance, law enforcement, public security, border control, aerospace, power, education, and healthcare. An interesting case study of facial recognition technology applications is that Jacky Cheung has been dubbed a "fugitive nemesis" because police have used facial recognition technology to apprehend fugitives multiple times at his concerts. On April 7, 2018, after the start of Jacky Cheung's Nanchang concert, a fan in the stands was escorted away by police. He was actually a fugitive; security personnel had identified him using a facial recognition system. On May 20, 2018, at Jacky Cheung's Jiaxing concert, a suspect surnamed Yu was identified as a fugitive by a facial recognition system while passing through a security gate and was subsequently arrested by police. As facial recognition technology matures and gains wider social acceptance, it will be applied to more fields, bringing more changes to people's lives.
03. Machine Translation
Machine translation, a branch of computational linguistics, is the process of using computers to convert one natural language into another. The primary technology used in machine translation is Neural Machine Translation (NMT), which currently outperforms human abilities in many languages. With the acceleration of economic globalization and the rapid development of the internet, the value of machine translation technology in promoting political, economic, and cultural exchanges has become increasingly apparent, bringing numerous conveniences to people's lives. For example, when reading English documents, we can easily convert English to Chinese using websites like Youdao Translate and Google Translate, eliminating the hassle of consulting dictionaries and improving the efficiency of learning and work.
04. Voiceprint Recognition
Biometric identification technologies include many types, among which, besides facial recognition, voiceprint recognition is currently widely used. Voiceprint recognition is a biometric authentication technology, also known as speaker identification, which includes speaker recognition and speaker confirmation. The process of voiceprint recognition involves the system collecting the speaker's voiceprint information and recording it in a database. When the speaker speaks again, the system collects this voiceprint information and automatically compares it with existing voiceprint information in the database to identify the speaker's identity.
Compared to traditional identification methods (such as keys and ID cards), voiceprint recognition is resistant to forgetting and allows for remote authentication. With current algorithm optimization and random password technology, voiceprints can also effectively prevent recording and synthesis, resulting in high security, rapid response, and accurate recognition. Furthermore, compared to biometric identification technologies such as facial recognition and iris recognition, voiceprint recognition technology can collect users' voiceprint features through telephone channels, network channels, etc., giving it a significant advantage in remote identity verification. Currently, voiceprint recognition technology has numerous application cases, including voiceprint verification, voiceprint locks, and blacklisted voiceprint databases, and can be widely used in finance, security, smart homes, and other fields, with diverse application scenarios.
05. Intelligent Customer Service Robot
An intelligent customer service robot is an artificial intelligence entity that uses machines to simulate human behavior. It possesses capabilities such as speech recognition and natural language understanding, and can perform business reasoning and scripted responses. When a user visits a website and initiates a conversation, the intelligent customer service robot quickly analyzes the user's intent based on the visitor's address, IP address, and access path obtained by the system, and responds to the user's true needs. Simultaneously, the intelligent customer service robot possesses a massive industry-specific knowledge base, enabling it to provide standardized responses to common user inquiries and improve response accuracy. Intelligent customer service robots are widely used in commercial services and marketing scenarios, helping customers solve problems and providing decision-making support. Furthermore, during the response process, the intelligent customer service robot can undergo adaptive training using rich dialogue data, thus becoming increasingly precise in its response scripts.
With the vertical development of intelligent customer service robots, they can now deeply address the problems in many specific business scenarios. For example, e-commerce companies face pre-sales inquiries. For most e-commerce companies, user inquiries generally revolve around topics such as price, discounts, and product sourcing. Traditional human customer service representatives answer these repetitive questions daily, making it impossible to provide timely service to customers with more complex questions. Intelligent customer service robots, on the other hand, can answer various simple, repetitive questions from users and provide 24/7 consultation and problem-solving services. Their widespread application has also significantly reduced the cost of human customer service for businesses.
06. Intelligent Outbound Calling Robot
Intelligent outbound calling robots are a typical application of artificial intelligence in speech recognition. They can automatically initiate outbound calls, proactively introducing products to user groups in the form of synthesized natural human voice. During the outbound call, they can use speech recognition and natural language processing technology to obtain customer intent, then use targeted scripts to conduct multi-round interactive conversations with users, finally classifying users as targets and automatically recording the key points of each call to successfully complete the outbound call.
Since the beginning of 2018, intelligent outbound calling robots have experienced explosive growth. They can interact without emotional fluctuations and automatically complete tasks such as answering, categorizing, recording, and tracking, helping businesses complete tedious, repetitive, and time-consuming operations. This frees up human labor, reduces significant labor costs and repetitive tasks, allowing employees to focus on target customers and create higher business value. However, intelligent outbound calling robots also bring a downside: frequent disruptions to users. To protect users' legitimate rights and promote the healthy development of voice call services, the Ministry of Industry and Information Technology issued the "Regulations on the Management of Short Message and Voice Call Services (Draft for Comments)" on August 31, 2020. This means that future outbound calling services, whether human or AI-powered, will require certified operators and will be conducted under regulatory supervision. This also places higher demands on the user experience and service quality of intelligent outbound calling robots.
07. Smart Speaker
Smart speakers are electronic products that utilize artificial intelligence technologies such as voice recognition and natural language processing. With their rapid development, they are seen as the future gateway to smart homes. Essentially, a smart speaker is a machine with voice interaction capabilities capable of conversing. By directly interacting with it, home consumers can perform tasks such as selecting music, controlling home appliances, and accessing lifestyle services.
The foundational technologies supporting smart speaker interaction primarily include Automatic Speech Recognition (ASR) technology, which converts human speech into text; Natural Language Processing (NLP) technology, which analyzes text for parts of speech, syntax, and semantics; and Text-to-Speech (TTS) technology, which converts text into natural speech streams. With the support of artificial intelligence, smart speakers are increasingly creating more applications in home scenarios through more natural voice interaction.
08. Personalized Recommendations
Personalized recommendation is an artificial intelligence application based on clustering and collaborative filtering technologies. Built upon massive data mining, it analyzes users' historical behavior to establish recommendation models, proactively providing users with information matching their needs and interests, such as product recommendations and news recommendations. Personalized recommendations can help users quickly locate products they need, reducing passive consumption and increasing user interest and retention. They can also help businesses quickly attract traffic, accurately identify user groups and positioning, and effectively market their products.
Personalized recommendation systems are widely used in various websites and apps. Essentially, they consider multiple factors such as the user's browsing information, basic user information, and preferences for items or content. They rely on recommendation engine algorithms to classify indicators, cluster information content that matches the user's target factors, and achieve accurate personalized recommendations through collaborative filtering algorithms.
09. Medical Image Processing
Medical image processing is a typical application of artificial intelligence in the medical field. It processes medical images generated by various imaging mechanisms, such as MRI and ultrasound imaging, which are widely used in clinical medicine.
Traditional medical imaging diagnosis primarily relies on observing two-dimensional slices to identify lesions, often depending on the physician's experience. However, computer image processing technology can perform image segmentation, feature extraction, quantitative analysis, and comparative analysis on medical images, enabling lesion identification and annotation, automatic target delineation for tumor radiotherapy, and three-dimensional image reconstruction during surgery. This application assists physicians in qualitative and even quantitative analysis of lesions and other target areas, significantly improving the accuracy and reliability of medical diagnosis. Furthermore, medical image processing plays a crucial supporting role in medical teaching, surgical planning, surgical simulation, various medical research projects, and the reconstruction of two-dimensional medical images.
10. Image Search
Image search is an information retrieval application that has seen increasing user demand in recent years, and it is divided into two types of search methods: text-based and content-based.
Traditional image search only recognizes elements such as color and texture of the image itself. Deep learning-based image search also incorporates semantic features such as faces, poses, geographic locations, and characters, performing multi-dimensional analysis and matching on massive amounts of data. The application and development of this technology not only meets the current user demand for image matching search to easily find identical or similar targets, but also ensures that enterprises can focus their product iterations and service upgrades more effectively by analyzing user needs and behaviors, such as searching for the same product or comparing similar items.
Artificial intelligence (AI) is a branch of computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can react in a way similar to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, and expert systems. Since its inception, AI has matured in both theory and technology, and its applications have continued to expand. It is conceivable that future AI-driven technological products will serve as "containers" of human wisdom.
