LONDON, July 9 (Reuters) - U.S.-based hedge fund Elliott Associates on Tuesday urged a London court to overturn a verdict supporting the London Metal Exchange's (LME) cancellation of nickel trades partly because the exchange failed to disclose documents. The LME annulled $12 billion in nickel trades in March 2022 when prices shot to records above $100,000 a metric ton in a few hours of chaotic trade. Elliott and market maker Jane Street Global Trading brought a case demanding a combined $472 million in compensation, alleging at a trial in June last year that the 146-year-old exchange had acted unlawfully. London's High Court ruled last November that the LME had the right to cancel the trades because of exceptional circumstances, and was not obligated to consult market players prior to its decision. Lawyers for Elliott told London's Court of Appeal that the LME belatedly released documents in May detailing its "Kill Switch" and "Trade Halt" internal procedures. It also newly disclosed an internal report that Elliott said detailed potential conflicts of interest at the exchange. "It was troubling that one gets disclosure out of the blue in the Court of Appeal for the first time," Elliott lawyer Monica Carss-Frisk told the court. Jane Street Global did not appeal the ruling. "If we had had them (documents) in the proceedings before the divisional court, we may well have sought permission to cross examine." LME lawyers said the new documents were not relevant. "The disclosed documents do not affect the reasoning of the divisional court or the merits of the arguments on appeal," the exchange said in documents prepared for the appeal hearing. "Elliott's appeal is largely a repetition of the arguments which were advanced, and rightly rejected." The LME said it had both the power and a duty to unwind the trades because a record $20 billion in margin calls could have led to at least seven clearing members defaulting, systemic risk and a potential "death spiral". Elliott said the ruling diluted protection provided by the Human Rights Act and also wrongly concluded the LME had the power to cancel the trades.

BEIRUT/JERUSALEM July 3 (Reuters) - An Israeli strike killed one of Hezbollah's top commanders in south Lebanon on Wednesday, prompting retaliatory rocket fire by the Iran-backed group into Israel as their dangerously poised conflict rumbled on. The Israeli military said it had struck and eliminated Hezbollah's Mohammed Nasser, calling him commander of a unit responsible for firing from southwestern Lebanon at Israel. Nasser, killed by an airstrike near the city of Tyre in southern Lebanon, was the one of the most senior Hezbollah commanders to die yet in the conflict, two security sources in Lebanon said. Sparked by the Gaza war, the hostilities have raised concerns about a wider and ruinous conflict between the heavily armed adversaries, prompting U.S. diplomatic efforts aimed at deescalation. Israeli Defence Minister Yoav Gallant said Israeli forces were hitting Hezbollah "very hard every day" and will be ready to take any action necessary against the group, though the preference is to reach a negotiated arrangement. Hezbollah began firing at Israeli targets at the border after its Palestinian ally Hamas launched the Oct. 7 attack on Israel, declaring support for the Palestinians and saying it would cease fire when Israel stops its Gaza offensive. Hezbollah announced at least two attacks in response to what it called "the assassination", saying it launched 100 Katyusha rockets at an Israeli military base and its Iranian-made Falaq missiles at another base in the town of Kiryat Shmona near the Israeli-Lebanese border. Israel's Channel 12 broadcaster reported that dozens of rockets were fired into northern Israel from Lebanon. There were no reports of casualties. The Israeli Defence Ministry said that air raid sirens sounded in several parts of northern Israel. Israel's military did not give a number of rockets launched but said most of them fell in open areas, some were intercepted, while a number of launches fell in the area of Kiryat Shmona.

The Ukrainian presidential office said on July 8 local time that Russia's large-scale attacks on many parts of Ukraine have killed 36 people and injured 140 others. According to the Ukrainian State Emergency Service, a total of 619 rescue workers and 132 equipment participated in the rescue work across Ukraine that day. Ukrainian President Zelensky said on social media on the 8th that Russia launched more than 40 missiles of various types at Ukraine that day. Residential buildings and infrastructure in many cities in Ukraine were damaged in varying degrees of attacks, and a children's hospital was destroyed. Rescue departments are currently conducting emergency rescue on the scene. The Russian Ministry of Defense issued a statement on the 8th local time saying that Ukrainian officials' claim that Russia used missiles to attack Ukrainian civilian facilities was untrue. The damage suffered by Kiev was caused by the fall of missiles launched by the city's air defense system.

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

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.