Japan aims to become the global leader in artificial intelligence
Shock! Japan attempts to become the world's overlord of artificial intelligence and increase Japan's GDP by 50% through artificial intelligence, but it actually ignores the law and does not follow the rules! Japan goes all out: Copyright does not apply to artificial intelligence training!
Surprisingly, the Japanese government recently reiterated that it will not enforce copyright protection on data used in artificial intelligence training. The policy allows AI to use any data "whether it is for non-profit or commercial purposes, whether it is an act other than copying, or content obtained from illegal websites or elsewhere." Japan Education, Culture, Sports, Science and Technology Minister Keiko Nagaoka confirmed the bold stance at a local meeting, saying Japan's laws would not protect copyrighted material used in AI datasets.
Japan, artificial intelligence and copyright! There is little coverage of this condition in English. The Japanese government seems to believe that concerns about copyright, particularly those related to anime and other visual media, are holding back Japan’s progress in AI technology. In order to remain competitive, Japan is going all out to find a copyright-free approach and explore it.
The news is part of Japan’s grand plan to become a leader in artificial intelligence technology. As strong competitors in the field of artificial intelligence chips, local technology companies known for their advanced 2-nanometer chip technology are gradually stepping into the spotlight. With chip companies elsewhere looking shaky, Japanese chip manufacturing may be a safer bet. Japan is also stepping up within the G7 to help shape global rules for artificial intelligence systems.
Not all Japanese agree with this decision. Many animation and graphics creators worry that artificial intelligence could devalue their work. Instead, academics and business are putting pressure on the government to take advantage of the country's lax data laws and push Japan to become a global leader in artificial intelligence.
Since the 1990s, although Japan is the world's third largest economy, its economic growth has been poor. Among the G7 countries, Japan has the lowest per capita income. The effective use of artificial intelligence may increase a country's GDP by 50% or more in a short period of time. It's an exciting prospect for Japan, which has endured years of low growth.
It’s all about data! Western access to data is also key to Japan’s AI ambitions. The more high-quality training data available, the better the AI model will be. Despite Japan's long cultural tradition, the amount of training data for Japanese is significantly smaller compared to the available language resources for Western English. However, Japan has a wealth of anime content that is popular around the world. Japan’s position seems clear – if the West uses Japanese culture for AI training, then the West’s cultural resources should also be used for Japanese AI.
What impact does this incident have on the world? Japan's move adds a new variable to the regulatory debate, which has also attracted widespread attention around the world. In Japan, we see a different dynamic. The world's third-largest economy said it would not hinder research and development of artificial intelligence. Furthermore, it is preparing to use this new technology to directly compete with the West.
As a friendly reminder, every country will do what is best for its citizens. In theory, U.S. law does the same with AI training data. If the West is going to use Japanese culture to train data, we really shouldn't be surprised if Japan decides to reciprocate.
Japan has a long history and high achievements in the field of artificial intelligence (AI). Japanese research institutions, businesses, and the government are actively investing in the research and development of artificial intelligence technology. Japan is extensively involved in the field of artificial intelligence, and its research and development directions include machine learning, natural language processing, computer vision, robotics and other fields.
Japanese companies such as Sony, Panasonic and Toyota have made significant progress in the field of artificial intelligence. In addition, the Japanese government is also promoting the development of the AI field and has formulated a series of policies and strategies, such as the "Society 5.0" plan, which aims to achieve the integration of artificial intelligence, big data, Internet of Things and other technologies and inject new vitality into the Japanese economy.
On a global scale, Japan's position in the field of AI is still quite competitive, but compared with the United States, China and other countries, Japan may be slightly deficient in some aspects. In the field of artificial intelligence in the future, Japan maintains a high level of technology research and development and application, so it has broad development prospects.
Japan’s biggest advantage is its chip manufacturing level! Since the 1980s, Japan has emerged in the semiconductor industry and once dominated the global market. In fields such as DRAM, flash memory, and image sensors, Japanese chip manufacturers have made remarkable achievements.
However, as global competition intensifies, especially the rapid rise of the semiconductor industry in countries such as the United States and South Korea, Japanese chip manufacturers' market share in certain areas has been challenged. Despite this, Japan still has a high level and competitiveness in chip technology.
In their respective fields of expertise, Japanese chip manufacturers such as Toshiba, Sony, and Renesas Electronics have world-leading technology. Sony has a huge market share and the world's leading competitive technology in the field of image sensors. In addition, Japan also has advantages in fields such as radio frequency devices, power semiconductors, and analog chips.
In general, although Japan’s chip technology may no longer be the global leader in some areas, it still has high competitiveness and technical level in specific areas. Japanese chip manufacturers are still working hard to adapt to changing market demands and technology development trends.
The above is the detailed content of Japan aims to become the global leader in artificial intelligence. 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

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

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

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 |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

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 site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year
