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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.

Google extends Linux kernel support to 4 years
According to AndroidAuthority, the Linux kernel used by Android devices is mostly derived from Google's Android Universal Kernel (ACK) branch, which is created from the Android mainline kernel branch when new LTS versions are released upstream. For example, when kernel version 6.6 is announced as the latest LTS release, an ACK branch for Android15-6.6 appears shortly after, with the "android15" in the name referring to the Android version of the kernel (in this case, Android 15). Google maintains its own set of LTS kernel branches for three main reasons. First, Google can integrate upstream features that have not yet been released into the ACK branch by backporting or picking, so as to meet the specific needs of Android. Second, Google can include some features that are being developed upstream in the ACK branch ahead of time, making it available for Android devices as early as possible. Finally, Google can add some vendor or original equipment manufacturer (OEM) features for other Android partners to use. Once created, Google continues to update the ACK branch to include not only bug fixes for Android specific code, but also to integrate the LTS merge content of the upstream kernel branch. For example, the Linux kernel vulnerability disclosed in the July 2024 Android security bulletin will be fixed through these updates. However, it is not easy to distinguish a bug fix from other bug fixes, as a patch that fixes a bug may also accidentally plug a security vulnerability that the submitter did not know about or chose not to disclose. Google does its best to recognize this, but it inevitably misses the mark, resulting in bug fixes for the upstream Linux kernel being released months before Android devices. As a result, Google has been urging Android vendors to regularly update the LTS kernel to avoid being caught off guard by unexpectedly disclosed security vulnerabilities. Clearly, the LTS version of the Linux kernel is critical to the security of Android devices, helping Google and vendors deal with known and unknown security vulnerabilities. The longer the support period, the more timely security updates Google and vendors can provide to devices.
Russia's economic strength gives it high-income status despite sanctions
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.”
How the iPhone 16 With AI Could Send Apple's Market Value to $4T
Apple could be on track to reach a $4 trillion market capitalization with the artificial intelligence (AI) iPhone 16 upgrade cycle coming, Wedbush analysts said. The analysts said the iPhone 16 supercharged with AI could bring a "golden upgrade cycle" for Apple. Apple's recently announced iOS 18 with Apple Intelligence and OpenAI partnership are also expected to create monetization opportunities and increase share value. Apple (AAPL) could be on the path to a $4 trillion market capitalization as an iPhone upgrade cycle approaches, driven by the iPhone 16 supercharged with artificial intelligence (AI) capabilities, according to Wedbush analysts. 1 Apple's recently announced iOS 18 with Apple Intelligence and OpenAI partnership are also expected to create monetization opportunities and increase share value. AI iPhone 16 Upgrade Cycle Coming Soon Wedbush analyst said that an AI iPhone 16 could bring "a golden upgrade cycle for Cupertino looking ahead with pent-up demand building globally." "The Street is now starting to slowly recognize that with Apple Intelligence on the doorstep in essence Cupertino will be the gatekeepers of the consumer AI Revolution," they said, with 2.2 billion iOS devices globally and 1.5 billion iPhones. Wedbush suggested a "consumer AI tidal wave" could start with the iPhone 16 in mid-September, adding that estimates indicate 270 million iPhones users have not upgraded in over four years. Recovery in China To Support Upgrade Cycle The analysts indicated that iPhone supply stabilization in Asia is also "a very good sign heading into a monumental iPhone 16 upgrade cycle." Wedbush's projections come amid ongoing concerns for the iPhone maker in the China region amid increased competition, though there have been recent signs of improving shipments. They projected that June "will be the last negative growth quarter for China with a growth turnaround beginning in the September quarter," when the iPhone 16 is expected to be released. AI and iOS 18 Could Also Boost Share Value Apple unveiled iOS 18 supercharged by Apple Intelligence and an AI partnership with OpenAI at its developers' conference in June. Wedbush analysts said the partnership with the Chat-GPT maker "creates the highway for developers around the globe to focus on iOS 18 and this in turn will create a myriad of monetization opportunities for Cook & Co. over the coming years." The analysts estimated that "this could result in incremental Services high margin growth annually of $10 billion for Apple" driven by hardware and software. They added they believe "AI technology being introduced into the Apple ecosystem will bring monetization opportunities on both the services as well as iPhone/hardware front and adds $30 to $40 per share." Apple shares were little changed in early trading Monday, though they have gained more than 17% since the start of the year. Do you have a news tip for Investopedia reporters? Please email us at tips@investopedia.com SPONSORED Trade on the Go. Anywhere, Anytime One of the world's largest crypto-asset exchanges is ready for you. Enjoy competitive fees and dedicated customer support while trading securely. You'll also have access to Binance tools that make it easier than ever to view your trade history, manage auto-investments, view price charts, and make conversions with zero fees. Make an account for free and join millions of traders and investors on the global crypto market.
Will chatGPT lead to job losses?
In fact, ChatGPT can bring more opportunities to many industries, such as customer service, marketing, speech recognition, and more. ChatGPT can help businesses engage with customers more effectively, improve the customer experience, and give businesses more time and resources to focus on other tasks. Come to see While ChatGPT can replace humans in certain situations, it is not a complete replacement for humans. In many cases, human-to-human communication is still the most effective way. Therefore, the emergence of ChatGPT will not lead to the unemployment of all people, but will cause structural changes in the labor force and the redistribution of occupations.
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