link1s.site

Israeli strike kills 16 at Gaza school, military says it targeted gunmen

CAIRO/GAZA, July 6 (Reuters) - At least 16 people were killed in an Israeli strike on a school sheltering displaced Palestinian families in central Gaza on Saturday, the Palestinian health ministry said, in an attack Israel said had targeted militants.

The health ministry said the attack on the school in Al-Nuseirat killed at least 16 people and wounded more than 50.

The Israeli military said it took precautions to minimize risk to civilians before it targeted the gunmen who were using the area as a hideout to plan and carry out attacks against soldiers. Hamas denied its fighters were there.

At the scene, Ayman al-Atouneh said he saw children among the dead. "We came here running to see the targeted area, we saw bodies of children, in pieces, this is a playground, there was a trampoline here, there were swing-sets, and vendors," he said.

Mahmoud Basal, spokesman of the Gaza Civil Emergency Service, said in a statement that the number of dead could rise because many of the wounded were in critical condition.

The attack meant no place in the enclave was safe for families who leave their houses to seek shelters, he said.

Al-Nuseirat, one of Gaza Strip's eight historic refugee camps, was the site of stepped-up Israeli bombardment on Saturday. An air strike earlier on a house in the camp killed at least 10 people and wounded many others, according to medics.

In its daily update of people killed in the nearly nine-month-old war, the Gaza health ministry said Israeli military strikes across the enclave killed at least 29 Palestinians in the past 24 hours and wounded 100 others.

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.
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
Former British PM Sunak appoints Conservative Party shadow cabinet
On July 8, local time, former British Prime Minister Sunak announced the appointment of the Conservative Party Shadow Cabinet, which is the first shadow cabinet of the Conservative Party in 14 years. Several former British cabinet members during Sunak's tenure as prime minister were appointed to the Conservative Party Shadow Cabinet, including James Cleverly as Shadow Home Secretary and Jeremy Hunt as Shadow Chancellor of the Exchequer. But former Foreign Secretary Cameron was not appointed as Shadow Foreign Secretary. In addition, the new leader of the Conservative Party will be elected as early as this week. On July 4, the UK held a parliamentary election. The counting results showed that the British Labour Party won more than half of the seats and won an overwhelming victory; the Conservative Party suffered a disastrous defeat, ending its 14-year continuous rule.
Hedge fund Elliott challenges court verdict it lost against LME on nickel
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.
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.