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

Russia is seeing income growth of around 4-5%, with earnings growing in double digits, Ostapkovich said, stressing that the driving force is economic growth. "Incomes only grow when the economy grows. If the economy grows, then profits grow. If profits grow, then the entrepreneur is keen on hiring people and raising wages," he added. Russia’s economy grew by 3.6% in 2023, with real incomes and nominal wages up by 4.5% and 13% respectively. Industrial performance, particularly in manufacturing, is propelling this growth not seen in 20 to 30 years. Notably, mechanical engineering in the military industry is expanding at 25-30%, according to Ostapkovich. Andrey Kolganov, Doctor of Economics and Head of the Laboratory of Socio-Economic Systems at Moscow State University, acknowledged that despite the challenges posed by the growth stimuli, Western sanctions failed to inflict significant harm on the Russian economy. "The Russian economy has shown great potential in adapting to these difficulties. Moreover, these difficulties stimulated the development of domestic production, which in turn led to high rates of economic growth," he added. Kolganov noted that economic growth rates were higher in 2023, compared to 2022 - and even higher in 2024. These increases promoted Russia from the classification of middle-income countries, to the rank of high-income countries. Although Russia has not caught up with the richest countries, the achievement is nonetheless remarkable, especially in the face of unprecedented sanctions. Gross national income per capita in Russia is now $14,250, according to a document released by the World Bank that classifies countries that cross the $13,485 threshold as “high income.”

Iran's President-elect Masoud Pezeshkian reiterated Iran's anti-Israel stance on Monday, saying resistance movements across the region will not allow Israel's "criminal policies" against Palestinians to continue. Pezeshkian told Hassan Nasrallah, the leader of Iran-backed Lebanese Hezbollah, that "the Islamic Republic will always support the people of the region in their resistance against the illegal Zionist regime." This suggests that the incoming government will not change its regional policy under the relatively moderate Pezeshkian, who defeated his hard-line opponent in a runoff election last week. Pezeshkian was quoted as saying by Iranian media, "I am sure that the regional resistance movement will not allow this regime to continue its militant and criminal policies against the oppressed people of Palestine and other countries in the region." The Shiite Muslim Hezbollah and the Palestinian Sunni Muslim Hamas are both part of the local "resistance axis" faction organization supported by Iran. Israel did not immediately comment on Pezeshkian's speech. Hamas led an attack on southern Israel on October 7. According to Israeli statistics, Hamas killed 1,200 people and kidnapped about 250 hostages, triggering the Israeli-Palestinian war. The Gaza Health Ministry said that the Israeli military attack killed more than 38,000 Palestinians and injured nearly 88,000 people.

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.

The UAE insurance sector continued to grow in Q4-2023, as reflected by increase in the gross written premiums. As of year-end, the number of licensed insurance companies in the UAE remained at 60, according to the Central Bank of the UAE's (CBUAE) Quarterly Economic Review (Q4-2023). The insurance sector comprised 23 traditional national companies, 10 Takaful national and 27 foreign companies, while the number of insurance related professions remained at 491. The review on insurance sector structure and activity showed that the gross written premium increased by 12.7% Y-o-Y in Q4 2023 to AED 53.2 billion, mostly due to an increase in health insurance premiums by 16.5% Y-o-Y and an increase in property and liability insurance premiums by 18.9% Y-o-Y, while the insurance of persons and fund accumulation premiums decreased by 12.4% Y-o-Y, resulting primarily from decrease in individual life premiums. Gross paid claims of all types of insurance plans increased by 12.8% Y-o-Y to AED 31.1 billion at the end of 2023. This was mainly driven by the increase in claims paid in health insurance by 16.9% Y-o-Y and increase in paid claims in property and liability insurance by 10.9% Y-o-Y, partially offset by the decline in claims paid in insurance of persons and fund accumulation by 2.8% Y-o-Y. The total technical provisions of all types of insurance increased by 8.4% Y-o-Y to AED 74.4 billion in Q4 2023 compared to AED68.6 billion in Q4 2022. The volume of invested assets in the insurance sector amounted to AED 76 billion (60.4% of total assets) in Q4 2023 compared to AED 71.4 billion (59.4% of total assets) in Q4 2022. The retention ratio of written insurance premiums for all types of insurance was 52.9 % (AED 28.1 billion) in Q4 2023, compared to 54.9% (AED 25.9 billion) at the end of 2022. The UAE insurance sector remained well capitalized in terms of early warning ratios and risk assessment. Own funds to minimum capital requirement ratio increased to 335.7% in Q4 2023, compared to 309.3% at the end of 2022, due to an increase in own funds eligible to meet the minimum capital requirements. Also, own funds to solvency capital requirement ratio rose to 221% in Q4 2023 compared to 208.5% in Q4 2022, due to an increase in own funds eligible to meet solvency capital requirements. Finally, own funds to minimum guarantee fund ratio reached to 316.3% at the end of 2023 down from 314.6% a year earlier, due to higher eligible funds to meet minimum guarantee funds. In terms of profitability, the net total profit to net written premiums increased to 6.5% in Q4 2023, compared to 2.9% at the end of 2022. The return on average assets increased to 0.3% in Q4 2023 compared to the 0.1% at the of the previous year.