
Wto: Members have more trade promotion measures than restrictions
The latest trade monitor released recently by the World Trade Organization shows that between mid-October 2023 and mid-May 2024, WTO members continued to introduce more trade promotion measures than trade restrictive measures. The WTO said it was an important signal of members' commitment to keep trade flowing amid the current geopolitical uncertainty. According to WTO statistics, during the monitoring period, WTO members adopted 169 trade promotion measures on commodities, more than the 99 trade restrictive measures introduced. Most of the measures are aimed at imports. Commenting on the findings, WTO Director-General Ngozi Okonjo-Iweala said that despite the challenging geopolitical environment, this latest trade monitoring report highlights the resilience of world trade. Even against the backdrop of rising protectionist pressures and signs of economic fragmentation, governments around the world are taking meaningful steps to liberalize and boost trade. This demonstrates the benefits of trade on people's purchasing power, business competitiveness and price stability. The WTO monitoring also identified significant new developments in economic support measures. Subsidies as part of industrial policy are increasing rapidly, especially in areas related to climate change and national security.

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

Portadown businessman avoids jail for sexual assault of teen under his employment
Defence said the defendant 'continues to deny' the charges and bail in the sum of £1,000 was fixed for appeal
A Portadown man has avoided jail after sexually assaulting a 16-year-old shop worker under his employment. -ADVERTISEMENT- Brian Thomas Chapman (58), of Moyallan Road, appeared before Newry Magistrates’ Court on Monday for sentencing on two counts of sexual assault. The prosecution outlined that on September 23, 2020, a 16-year-old student in the employment of Brian Chapman, disclosed to her mother about incidents that had occurred in her workplace. She said Chapman had put his hand on her thigh and the back of her leg. She also disclosed that she had been getting extra money from him and he had been sending her text messages. The allegations were reported to police the next day, September 24. The victim then took part in an interview on October 9, in which she said, when she was alone in Chapman’s office, he placed his hand on her upper thigh and his other hand on her lower back, underneath her trousers. The defendant was arrested and interviewed at Lurgan police station, where he denied the allegations. His phone was seized and an examination was carried out. The first interview of the defendant took place on October 9, during which he admitted to sending a message about wanting the victim to work 24/7, but stated this was a joke. The second interview took place on January 28, 2021, where he admitted to sending the 24/7 message, but denied sending other messages, such as “hope you’re spending the pounds on something special”. Throughout this process, Chapman denied sending the messages and denied any of the sexual assaults alleged by the victim. On the Chapman’s criminal record, the prosecution added that he was convicted of three common assaults on appeal. In terms of commission, these matters pre-dated this case but the conviction occurred during the running of this case and also involved a female working for the defendant. Prosecution continued that the age of the victim was an aggravating feature, arguing there was a “vulnerability” due to the “power-imbalance” between Chapman and the young student working for him. An additional aggravating feature, they said, was that during the course of the defence, part of the defence was that the victim had “manipulated or manufactured” some of the text messages that were sent. A defence lawyer, speaking on the pre-sentence report, noted the author deemed Chapman to be of low risk. He also noted that similar offences were contested in the County Court in respect of another complaint, with the judge substituting indecent assault charges for common assault. He also argued a Sexual Offences Prevention Order (SOPO) was not necessary as the offending was four years ago, there has been no repetition and risk had been addressed. District Judge Eamonn King noted the defendant was convicted on two of four original charges following a contest, which ran over a number of days, with the case adjourned for a pre-sentence report and victim impact statement to be produced. He added the defendant “continues to deny” the charges and seeks to appeal the outcome. District Judge King, on reading the pre-sentence report, noted the defendant “denies ever hugging or touching the individual and he denies any sexual attraction to the victim”, but pointed to a paragraph in the report which stated, “From the available evidence, it’s possible to surmise that he demonstrated risk taking and impulsive behaviour. It appears that he took advantage of his position and power in a bid to meet his sexual needs, given the victim’s young age and the fact that he was her employer”. The report added that this demonstrated “limited victim empathy and responsibility due to his denial of the offences”. On the victim impact statement, District Judge King described her as a young girl getting her first job, with the “world as her oyster”. He continued: “As a result of what she says occurred, that turned on its head. It left her feeling inwardly uncomfortable, anxious and lonely. She cut herself off from her friends. She stopped going out. She didn’t want to go to school.” He also described a “degree of manipulation” in the case, as this was the victim’s first job and there was a power imbalance between her as an employee, and Chapman as the employer. In his sentencing remarks, District Judge King, said: “I’ve taken time to emphasise to the victim in this case that the victim did nothing wrong. The victim did everything right and the victim shouldn’t feel lonely, anxious or isolated. “The victim should feel confident, strong and outgoing.” Owing to the defendant’s ongoing denial of the charges, he added: “My sentencing exercise isn’t the conclusion of the case today, but I will sentence, so that we can move towards the conclusion going forward. “I am satisfied, irrespective of what the pre-sentence report says, that the defendant took advantage of someone, attempted to groom someone and was guilty of the two offences.” On the two counts, Chapman was sentenced to three months in prison, suspended for two years. He was also made subject to a Sexual Offences Prevention Order (SOPO) for five years and placed on the sex offenders’ register for seven years. Following sentencing, District Judge King fixed bail for appeal at £1,000.

China proposes to establish BCI committee to strive for domestic innovation
China is mulling over establishing a Brain-Computer Interface (BCI) standardization technical committee under its Ministry of Industry and Information Technology (MIIT), aiming to guide enterprises to enhance industrial standards and boost domestic innovation. The proposed committee, revealed by the MIIT on Monday, will work on composing a BCI standards roadmap for the entire industry development as well as the standards for the research and development of the key technologies involved, according to the MIIT. China has taken strides in developing the BCI industry over the years, not only providing abundant policy support but also generous financial investment, Li Wenyu, secretary of the Brain-Computer Interface Industrial Alliance, told the Global Times. From last year to 2024, both the central and local governments have successively issued relevant policies to support industrial development. The MIIT in 2023 rolled out a plan selecting and promoting a group of units with strong innovation capabilities to break through landmark technological products and accelerate the application of new technologies and products. The Beijing local government also released an action plan to accelerate the industry in the capital (2024-2030) this year. In 2023, there were no fewer than 20 publicly disclosed financing events for BCI companies in China, with a total disclosed amount exceeding 150 million yuan ($20.6 million), Li said. “The strong support from the government has injected momentum into industrial innovation.” The fact that China's BCI industry started later than Western countries such as the US is a reality, leading to the gap in China regarding technological breakthroughs, industrial synergy, and talent development, according to Li. To further close gaps and solve bottlenecks in BCI industrial development, Li suggested that the industry explore various technological approaches to suit different application scenarios and encourage more medical facilities powered by BCI to initiate clinical trials by optimizing the development of BCI-related ethics. Additionally, he highlighted that standard development is one of the aspects to enhance the overall level and competitiveness of the industry chain, which could, in turn, empower domestic BCI innovation. While China's BCI technology generally lags behind leading countries like the US in terms of system integration and clinical application, this has not hindered the release of Neucyber, which stands as China's first "high-performance invasive BCI." Neucyber, an invasive implanted BCI technology, was independently developed by Chinese scientists from the Chinese Institute for Brain Research in Beijing. Li Yuan, Business Development Director of Beijing Xinzhida Neurotechnology, the company that co-developed this BCI system, told the Global Times that the breakthrough of Neucyber could not have been achieved without the efforts of the institute gathering superior resources from various teams in Beijing. A group of mature talents were gathered within the institute, from specific fields involving electrodes, chips, algorithms, software, and materials, Li Yuan said. Shrugging off the outside world's focus on China’s competition with the US in this regard, Li Yuan said her team doesn’t want to be imaginative and talk too much, but strives to produce a set of products step by step that can be useful in actual applications. In addition, Li Wenyu also attributed the emergence of Neucyber to the independent research atmosphere and the well-established talent nurturing mechanism in the Chinese Institute for Brain Research. He said that to advance China’s BCI industry, it is necessary not only to cultivate domestic talents but also to introduce foreign talents to enhance China's research and innovation capabilities. The proposed plan for establishing the BCI standardization technical committee under the MIIT will solicit public opinions until July 30, 2024.

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.