Large Language Models (LLMs) have made significant advancements across numerous domains, but their capabilities in Chinese Classical Literature and Language Arts (CCLLA) remain largely unexplored due to the limited scope and tasks of existing benchmarks. To fill this gap, we propose WenMind, a comprehensive benchmark dedicated for evaluating LLMs in CCLLA.

In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future world competition pattern. As the builder and operator of information and communication infrastructure, the telecom sector provides infrastructure support for the development of AI, and even takes the lead in the implementation of AI applications. How to enable the application of AIGC (GPT) and implement AIGC in the telecom sector are questions that telecom practitioners must ponder and answer. Through the study of GPT, a typical representative of AIGC, the authors have analyzed how GPT empowers the telecom sector in the form of scenarios, discussed the gap between the current GPT general model and telecom services, proposed for the first time a Telco Augmented Cognition capability system, provided answers to how to construct a telecom service GPT in the telecom sector, and carried out various practices. Our counterparts in the industry are expected to focus on collaborative innovation around telecom and AI, build an open and shared innovation ecosystem, promote the deep integration of AI and telecom sector, and accelerate the construction of next-generation information infrastructure, in an effort to facilitate the digital transformation of the economy and society.

Katy stared at the computer monitor in stunned silence. The message displayed was monumental, something that would forever change humanity. A month ago, she was selected as the director of a joint U.S. Cyber and Space Command surveillance team tasked with analyzing Chinese space-based communications satellites utilizing quantum computing codes. The Chinese have made significant advances in quantum computing and artificial intelligence in the past ten years. There were fears in the U.S. national security enterprise that the Chinese would obtain technical dominance.

The prime minister says she wants the UK to lead the world in deciding how artificial intelligence can be deployed in a safe and ethical manner. In a speech at the World Economic Forum in Davos, Theresa May said a new advisory body, previously announced in the Autumn Budget, will co-ordinate efforts with other countries. In addition, she confirmed that the UK would join the Davos forum's own council on artificial intelligence. But others may have stronger claims. Earlier this week, Google picked France as the base for a new research centre dedicated to exploring how AI can be applied to health and the environment.

Artificial intelligence, or AI, is everywhere these days, from self-driving cars and voice-activated software like Siri and Alexa. It's being used in fields from criminal justice to finance. So this year in All Tech Considered, we're going to spend some time exploring AI. Its leadership wants to dominate the tech world. It's one way China can beat possible competitors and adversaries.

Sören Schwertfeger finished his postdoctorate research on autonomous robots in Germany, and seemed set to go to Europe or the United States, where artificial intelligence was pioneered and established. China, which for years watched enviously as the West invented the software and the chips powering today's digital age, has become a major player in artificial intelligence, what some think may be the most important technology of the future. Experts widely believe China is only a step behind the United States. Beijing is backing its artificial intelligence push with vast sums of money.

When Gang Xu, a 46-year-old Beijing resident, needs to communicate with his Canadian tenant about rent payments or electricity bills, he opens an app called iFlytek Input in his smartphone and taps an icon that looks like a microphone, and then begins talking. The software turns his Chinese verbal messages into English text messages, and sends them to the Canadian tenant. In China, over 500 million people use iFlytek Input to overcome obstacles in communication such as the one Xu faces. Some also use it to send text messages through voice commands while driving, or to communicate with a speaker of another Chinese dialect. The app was developed by iFlytek, a Chinese AI company that applies deep learning in a range of fields such as speech recognition, natural-language processing, machine translation, and data mining (see "50 Smartest Companies 2017").

China's top security officer has revealed plans to use artificial intelligence to predict crime, terrorism and social unrest before it happens. Meng Jianzhu, the head of the Chinese Community Party's central commission for political and legal affairs, said the government would start to use AI software which uses machine learning, data mining and computer modelling to predict where crime and disorder is likely to occur. "Artificial intelligence can complete tasks with a precision and speed unmatchable by humans, and will drastically improve the predictability, accuracy and efficiency of social management," Mr Meng told colleagues at a meeting in Beijing on Friday. He said security forces should look for patterns in data about terror attacks and build an analysis model to help authorities predict where the attack may strike, Chinese news website thepaper.cn Mr Meng also called for all elements of the Chinese state and the party to share data with each other and for renewed efforts to integrate surveillance footage systems across the country.

To understand the potential of these new systems, it helps to know how current machine translation works. The current de facto standard is Google Translate, a system that covers 103 languages from Afrikaans to Zulu, including the top 10 languages in the world–in order, Mandarin, Spanish, English, Hindi, Bengali, Portuguese, Russian, Japanese, German, and Javanese. Google's system uses human-supervised neural networks that compare parallel texts–books and articles that have been previously translated by humans. By comparing extremely large amounts of these parallel texts, Google Translate learns the equivalences between any two given languages, thus acquiring the ability to quickly translate between them. Sometimes the translations are funny or don't really capture the original meaning but, in general, they are functional and, overtime, they're getting better and better.

Editor's note: The AI Magazine is initiating a series of articles Since the 1970's AI research has become very active in China and certain results have been achieved. After that, many university departments awarding majors in computer science were organized. They tried to expand the applications of the computer and to develop theories. Considerable efforts were made for this purpose, but these brought few notable results, as a practical process is too complex to identify. However a veteran worker or a technician often manages somewhat better than a computer in process control.