Application of artificial intelligence in cultural field
In recent years, my country's cultural industry has paid more and more attention to high-tech technologies such as artificial intelligence, showing a development trend of deep and organic integration of culture and technology. Artificial intelligence, which is very popular nowadays, is proved by its wide application in the cultural field. The sparks brought about by the collision of technology and culture give us more possibilities for expressing history. This is not only the specific application and continuous implementation of high and new technologies, but also a living process of improving the digitalization and intelligence level of cultural products, thereby increasing the added value of the cultural industry. The constantly evolving and upgrading artificial intelligence technology has played a driving role to varying degrees in many fields of cultural industries such as literature, film and television, music, design, games, media, publishing, etc., and has even produced revolutionary changes in some fields. For the fields of literary and artistic creation that require extreme creativity, artificial intelligence can liberate users from procedures and repetitive labor, allowing them to devote more energy to activities such as creativity, design, planning, research and development, and creation, thereby improving cultural Productivity and speed of innovation. Today, let us take a look at what new ways AI artificial intelligence has brought us in the field of culture!
1. Content distribution
AI can distribute based on different communication scenarios and carry out personalized customized distribution based on user preferences. By training the distribution system and combining it with user behavior data from the media, we can accurately analyze and gain insight into the characteristics of different user groups, and achieve personalized customization and recommendations for different news consumers to adapt to the specific needs of users.
2. In terms of media asset management
The intelligent media management system can better manage all available media resources. Intelligent content storage and retrieval can make it easier to use all the content available in the media, thereby saving time and creating better content for the audience. For example, the Douyin platform uses artificial intelligence to help manage massive video resources to improve users' attention allocation and traffic allocation mechanisms.
3, In the fields of film, television, music and art
Artificial intelligence can greatly improve people’s work efficiency in editing, lighting, post-production and many other processes. We are all in Explore the use of AI to create more touching works of art. In the field of film and television, defects caused by too little light can be automatically corrected into full-light and natural images. In the field of music, artificial intelligence has been able to participate in various aspects such as theme selection, preliminary generation, arrangement, and sound synthesis. In the field of art, artificial intelligence is also involved in many aspects such as the creation, protection and realization of culture and art. Such culture has led and inspired the development of technology. With the realization of technology and mankind's continuous understanding of the objective world, it has promoted The logic and authenticity of cultural works are constantly improving.
4, Game field
The application of artificial intelligence is mainly divided into two aspects: On the one hand, artificial intelligence is used for the development of game content, such as making games Various materials such as models, textures, sounds, non-player characters, etc. For example, a variety of game development tools are developed based on machine learning and neural network technology. Its functions include automatically generating materials from photos, restoring low-pixel images to higher definition, etc.; researchers at the Georgia Institute of Technology in the United States use AI to watch game videos. , teaching it how to re-engineer the game.
5, Intangible cultural heritage protection
Throughout the 5,000-year history of mankind, from the historical scene to the concept of the scene, we can use artificial intelligence to protect one by one accomplish. Artificial intelligence can collect data and use 3D imaging technology to scan the required objects to form virtual reality scenes and reproduce the real historical scenes and characters from thousands of years ago. Based on the fact that there are not many opportunities to come into contact with intangible cultural heritage, the intelligent chat robot has the ability to understand natural language through machine learning. It can use the advantages of big data to instantly provide users with effective and useful information about the intangible cultural heritage items they want to know. , which makes up for the shortcomings of traditional machine one-way communication, enhances users' understanding of intangible cultural heritage, and thereby improves the efficiency of intangible cultural heritage dissemination. In addition, artificial intelligence can create a good personalized learning experience. When users need to provide information or interact, artificial intelligence machines can answer or judge based on their own understanding, allowing users to obtain good intangible cultural heritage knowledge. experience.
Written at the end
In fact, the combination of cultural industry and AI goes far beyond the above-mentioned media fields. AI has broad application prospects in film and television production, games, literary creation, etc. The advancement of technology has provided huge market opportunities for various fields of the cultural industry, but it has also brought various risks and challenges, which has also put forward higher requirements for all aspects of the industry. The rational use of artificial intelligence to promote the innovative development of the digital cultural industry requires the joint efforts of all parties to solve the problem.
The above is the detailed content of Application of artificial intelligence in cultural field. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP

Improve developer productivity, efficiency, and accuracy by incorporating retrieval-enhanced generation and semantic memory into AI coding assistants. Translated from EnhancingAICodingAssistantswithContextUsingRAGandSEM-RAG, author JanakiramMSV. While basic AI programming assistants are naturally helpful, they often fail to provide the most relevant and correct code suggestions because they rely on a general understanding of the software language and the most common patterns of writing software. The code generated by these coding assistants is suitable for solving the problems they are responsible for solving, but often does not conform to the coding standards, conventions and styles of the individual teams. This often results in suggestions that need to be modified or refined in order for the code to be accepted into the application

To learn more about AIGC, please visit: 51CTOAI.x Community https://www.51cto.com/aigc/Translator|Jingyan Reviewer|Chonglou is different from the traditional question bank that can be seen everywhere on the Internet. These questions It requires thinking outside the box. Large Language Models (LLMs) are increasingly important in the fields of data science, generative artificial intelligence (GenAI), and artificial intelligence. These complex algorithms enhance human skills and drive efficiency and innovation in many industries, becoming the key for companies to remain competitive. LLM has a wide range of applications. It can be used in fields such as natural language processing, text generation, speech recognition and recommendation systems. By learning from large amounts of data, LLM is able to generate text

Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it

Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A

Machine learning is an important branch of artificial intelligence that gives computers the ability to learn from data and improve their capabilities without being explicitly programmed. Machine learning has a wide range of applications in various fields, from image recognition and natural language processing to recommendation systems and fraud detection, and it is changing the way we live. There are many different methods and theories in the field of machine learning, among which the five most influential methods are called the "Five Schools of Machine Learning". The five major schools are the symbolic school, the connectionist school, the evolutionary school, the Bayesian school and the analogy school. 1. Symbolism, also known as symbolism, emphasizes the use of symbols for logical reasoning and expression of knowledge. This school of thought believes that learning is a process of reverse deduction, through existing

Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S

According to news from this website on July 5, GlobalFoundries issued a press release on July 1 this year, announcing the acquisition of Tagore Technology’s power gallium nitride (GaN) technology and intellectual property portfolio, hoping to expand its market share in automobiles and the Internet of Things. and artificial intelligence data center application areas to explore higher efficiency and better performance. As technologies such as generative AI continue to develop in the digital world, gallium nitride (GaN) has become a key solution for sustainable and efficient power management, especially in data centers. This website quoted the official announcement that during this acquisition, Tagore Technology’s engineering team will join GLOBALFOUNDRIES to further develop gallium nitride technology. G
