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Stanford AI project team apologizes for plagiarizing Chinese model

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

Could a $600 billion funding gap crush the AI industry?
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.
Samsung Electronics wins cutting-edge AI chip order from Japan's Preferred Networks
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Koenigsegg Fused Three Hypercars Into One To Make The Chimera
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Coexisting and cooperating with China is the only choice for the US
US Secretary of State Antony Blinken declared at the Munich Security Conference: "If you're not at the table in the international system, you're going to be on the menu." The arrogant thinking of American political elites is evident: Whoever does not comply with the US will be excluded from the table of the American-led system and put on the menu. How arrogant. The US is actively pushing for "decoupling" from China and trying to persuade the entire West to "decouple" from China, using the term "de-risking." Washington hopes to ultimately contain China's development in order to maintain American hegemony. However, this time, Washington is facing a historically experienced and strategically rich Eastern civilization. Previous opponents targeted by the US have chosen to confront the US strategically. The US not only has the strongest technological and military capabilities but also controls global financial and information networks with a large number of allies. 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ChatGPT: Explained to Kids(How ChatGPT works)
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.