Chat means chat, and GPT is the acronym for Gene Rate Pre trained Transformer. Genrative means generation, and its function is to create or produce something new; Pre trained refers to a model of artificial intelligence that is learned from a large amount of textual materials, while Transformer refers to a model of artificial intelligence. Don't worry about T, just focus on the words G and P. We mainly use its Generative function to generate various types of content; But we need to know why it can produce various types of content, and the reason lies in P. Only by learning a large amount of content can we proceed with reproduction. And this kind of learning actually has limitations, which is very natural. For example, if you have learned a lot of knowledge since childhood, can you guarantee that your answer to a question is completely correct? Almost impossible, firstly due to the limitations of knowledge, ChatGPT is no exception, as it is impossible to master all knowledge; The second is the accuracy of knowledge, how to ensure that all knowledge is accurate and error free; The third aspect is the complexity of knowledge, where the same concept is manifested differently in different contexts, making it difficult for even humans to grasp it perfectly, let alone AI. So when we use ChatGPT, we also need to monitor the accuracy of the output content of ChatGPT. It is likely not a problem, but if you want to use it on critical issues, you will need to manually review it again. And now ChatGPT has actually been upgraded twice, one is GPT4 with more accurate answering ability, and the other is the recent GPT Turbo. The current ChatGPT is a large model called multimodality, which differs from the first generation in that it can not only receive and output text, but also other types of input, such as images, documents, videos, etc. The output is also more diverse. In addition to text, it can also output images or files, and so on.

US President Joe Biden signed an executive order on Wednesday restricting investments in China, intended to further stymie China's advances in three cutting-edge technology areas: semiconductors and microelectronics, quantum information technologies and certain artificial intelligence systems. The "decoupling" of high tech from China began under Donald Trump, and the Biden administration has continued that ambition. However, the new order doesn't target US investments already invested in China, but the new ones. The Biden administration has repeatedly claimed that the US restrictions will be narrowly targeted and will not "have a fundamental impact on affecting the investment climate for China." Biden's new executive order is still subject to consultation with the US business community and the public and is not expected to take effect until next year. The order has been brewed for a long time and has generated a lot of publicity. But almost no one believes that this executive order will deal a new practical blow to Chinese high technology, because almost everyone knows that China needs American technology more than American money. The order has gained much attention because it is seen as part of a broader trend of the US drifting away from China. The promulgation and brewing process of the executive order reflects the strong desire of American political elites to suppress China's high-tech development, as well as a fierce game between those supporting the executive order and the concerns of the technology and economic sectors about a potential backfire on the US. It is a kind of compromise. Washington obviously hopes that major allies will follow Biden's executive order. The UK's Sunak government has made cautious statements, stating that it is consulting business and the financial sector before deciding whether to follow suit. In fact, China also has the ability to influence the extent to which Biden's executive order is implemented, as well as the extent to which the US will go in terms of "decoupling" from China. We are definitely not just passive recipients of US policies. American political elites are eager to "decouple" from China as quickly and deeply as possible, but they fear two things: First, this will immediately damage the performance of relevant high-tech companies in the US, undermine their influence and further innovation. The current Biden administration, in particular, does not want to incur strong resentment from Silicon Valley and Wall Street toward the escalating "decoupling," which will ultimately lead to the loss of support for the Democratic Party. Second, they are afraid of pushing China toward more resolute independent innovation to achieve breakthroughs in key technologies such as chips. If the US "decoupling" policy gives birth to major technological achievements in China, it means that Washington will completely lose the gamble: They originally wants to stifle China's high-tech development, but ends up strangling their own companies. What China needs to do next is to fully unleash our innovation vitality, continuously reduce our dependence on high-tech products from the US, and prove that as long as we are determined to achieve independent innovation, we have the ability to accomplish things. We need to prove that being pressured by the US will only make us stronger. As long as there are several solid proofs of this trend, the US policy community will fall into unprecedented chaos, and their panic will be much more severe than when they saw the rapid expansion of the Chinese economy before Trump started the trade war. Regardless of the future of China-US relations, the current battle will be the key battle that determines the future competition between China and the US. China can only win and cannot afford to lose. High-tech products such as chips are not isolated. The innovation power of China's entire manufacturing industry and the creative vitality of the whole society are the foundation for shaping these key achievements. When pressured by the US, our society needs to generate confidence and resilience from all directions, and we need to accelerate and seize every opportunity, rather than shrink and simply defend. Otherwise, the US will gain the upper hand in momentum, and we will truly be in a passive and defensive position. We must see that the US is on the offensive, but its offensive is becoming weaker and weaker, and it is always hesitant with each step. What is presented to China are difficulties and risks, but also the dawn of victory.

On July 5, Microsoft co-founder Bill Gates appeared on the Next Big Idea podcast to discuss his vision for Superhuman artificial intelligence and technological progress. At the same time, it said that the enthusiasm of the AI market is far more than the Internet bubble. Gates believes that the current threshold for entry in the AI field is very low, and the entire market is in a fever period, AI startups can easily get hundreds of millions of dollars in financing, and even have raised $6 billion (about 43.734 billion yuan) in cash for a company. "Never before has so much capital poured into a new area, and the entire AI market has fallen into a 'frenzy' in terms of market capitalization and valuation, which dwarfs the frenzy of the Internet and automotive periods in history." Gates said. At this stage, the rapid development of the artificial intelligence industry is a veritable gold industry, and Nvidia's market value is therefore soaring, and the total market value reached 3.34 trillion US dollars on June 18 local time, surpassing Microsoft and Apple in one fell fell, becoming the world's most valuable listed enterprise. But in fact, doubts about the field of artificial intelligence have also risen one after another and have never stopped.

An artificial intelligence (AI) team at Stanford University apologized for plagiarizing a large language model (LLM) from a Chinese AI company, which became a trending topic on the Chinese social media platforms, where it sparked concern among netizens on Tuesday. We apologize to the authors of MiniCPM [the AI model developed by a Chinese company] for any inconvenience that we caused for not doing the full diligence to verify and peer review the novelty of this work, the multimodal AI model Llama3-V's developers wrote in a post on social platform X. The apology came after the team from Stanford University announced Llama3-V on May 29, claiming it had comparable performance to GPT4-V and other models with the capability to train for less than $500. According to media reports, the announcement published by one of the team members quickly received more than 300,000 views. However, some netizens from X found and listed evidence of how the Llama3-V project code was reformatted and similar to MiniCPM-Llama3-V 2.5, an LLM developed by a Chinese technology company, ModelBest, and Tsinghua University. Two team members, Aksh Garg and Siddharth Sharma, reposted a netizen's query and apologized on Monday, while claiming that their role was to promote the model on Medium and X (formerly Twitter), and that they had been unable to contact the member who wrote the code for the project. They looked at recent papers to validate the novelty of the work but had not been informed of or were aware of any of the work by Open Lab for Big Model Base, which was founded by the Natural Language Processing Lab at Tsinghua University and ModelBest, according to their responses. They noted that they have taken all references to Llama3-V down in respect to the original work. In response, Liu Zhiyuan, chief scientist at ModelBest, spoke out on the Chinese social media platform Zhihu, saying that the Llama3-V team failed to comply with open-source protocols for respecting and honoring the achievements of previous researchers, thus seriously undermining the cornerstone of open-source sharing. According to a screenshot leaked online, Li Dahai, CEO of ModelBest, also made a post on his WeChat moment, saying that the two models were verified to have highly similarity in terms of providing answers and even the same errors, and that some relevant data had not yet been released to the public. He said the team hopes that their work will receive more attention and recognition, but not in this way. He also called for an open, cooperative and trusting community environment. Director of the Stanford Artificial Intelligence Laboratory Christopher Manning also responded to Garg's explanation on Sunday, commenting "How not to own your mistakes!" on X. As the incident became a trending topic on Sina Weibo, Chinese netizens commented that academic research should be factual, but the incident also proves that the technology development in China is progressing. Global Times

Beijing self-driving cars on the road will usher in legislative protection. Recently, the Beijing Municipal Bureau of Economy and Information Technology solicited comments on the "Beijing Autonomous Vehicle Regulations (Draft for Comment)". The city intends to support the use of autonomous vehicles for urban public electric bus passenger transport, online car booking, car rental and other urban travel services. In addition to application scenarios, the draft for comments also standardizes autonomous driving innovation from many aspects, such as whether there is a driver, how to deal with traffic problems, and so on. The release of the opinion draft also means that the commercialization of automatic driving is accelerating, and perhaps soon we will be able to experience the convenience of automatic driving. In addition, the accelerated pace of autonomous driving, and whether it will have an impact on the taxi and traditional network car industry, it is also worth thinking about.