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The Pangu model was an artificial intelligence model jointly developed by Huawei Cloud, Circulation Intelligence, and Pengcheng Laboratory. It included the NMP (Natural Language Processing) model, the MV (Machine Vision) model, and the scientific computing model. It was officially released in April 2021. The Pangu Model 5.0, released on June 21st, 2024, was upgraded in three aspects: full series, multi-mode, and strong thinking. In terms of multi-modes, it could better and more accurately understand the physical world, including text, pictures, video, radar, infrared, remote sensing, and more. For example, identifying satellite remote sensing images to analyze regional crop growth for yield estimation, pest and disease monitoring, and so on. Models with different parameters can be adapted to different business scenarios. For example, the Pangu E series with billions of parameters supports end-side intelligent applications such as mobile phones and PCs; the Pangu P series with billions of parameters is suitable for low-delay and high-efficiency reasoning scenarios; the Pangu U series with billions of parameters handles complex tasks; and the Pangu S series super large model with trillions of parameters helps enterprises handle complex cross-domain multi-tasks. The Pangu model had many advantages and wide applications. Compared to ChatGPM, Pangu not only supported text, picture, and video input, but also supported radar, infrared, and remote sensing, which could simulate the real physical world. For example, in the aspect of intelligent driving, there is no need for modeling. It can carry out physical reasoning, automatic adjustment of parameters, detection and identification of various objects, realize intelligent driving without relying on high-definition maps, and can be applied to other vehicles through manual driving learning. It has applications in high-speed rail inspection, national grid power grid inspection, Wugang, Shanghai Development Bank, government affairs and other fields. In terms of weather, the Pangu Meteorology Model was the first AI model with accuracy exceeding traditional numerical prediction methods. Its speed was more than 10,000 times faster than traditional numerical prediction methods. It could provide global weather forecast in seconds. Its weather forecast results included a variety of weather elements and could be directly applied to multiple weather research sub-scenarios. The European Medium-Range Weather Projection Center had launched the model for free viewing of the weather forecast for the next 10 days. In addition, the Pangu model could allow the robot to complete more than ten complex mission plans, generate virtual videos needed by the robot to learn complex scenes, realize object recognition, question and answer interaction, high-fives and water delivery, and other functions in the field of humanoid robots. It could also enable various forms of industrial robots and service robots to do dangerous and heavy work. The Huawei Cloud Pangu NMP model passed all 38 tasks such as text analysis, abstract summary, text rewrite, and knowledge Q & A, demonstrating comprehension ability (such as text analysis, reasoning, etc.) and generation ability (such as abstract summary, machine translation, etc.). Its overall model architecture is layered, including basic and high-level abilities in terms of service core technical capabilities, and can be improved in various ways to provide humane Q & A services in the field of government affairs and improve office efficiency. 'The Myth of True Love in the Pangu Progenitor Universe' is equally wonderful. Please click to read it!

Here are some big AI models that might be helpful in writing a thesis: - ** GT4 **: Has powerful natural language processing capabilities, can help generate the framework of the thesis, provide relevant opinions and arguments, etc. However, it was a foreign model, and there might be network and data security restrictions when using it. - ** A Word from the Heart **: Able to understand user needs and provide ideas and materials for thesis writing. It was an artificial intelligence developed by Baidu and could use Baidu's knowledge graph and other resources. - ** Iflystar **: Can be used to analyze the topic of the thesis, providing some support in terms of language expression and logical combing. When writing a thesis using the AI model, you can use the following functions: - ** Generation of content **: Generates relevant paragraph content according to the theme entered. However, you need to check the accuracy and creativity of the generated content to avoid plagiarism. - ** Thought Expansion **: When encountering a bottleneck in thinking, the large model can provide some different perspectives and ideas to help broaden the vision of the thesis. - ** grammar and format checking **: Some large models can check for grammar errors in the thesis and give suggestions for format. However, when writing a thesis using an AI model, one should also pay attention to: - ** Accuracy verification **: You can't completely rely on the output of the model. You need to carefully verify the facts and data. - ** Academic standards **: Follow academic ethics and standards, use AI tools reasonably, and ensure that the thesis is a reflection of your own research results. " A Short History of the Future: Legends of the Intelligent Era " was equally exciting. Everyone was welcome to click and read it!

On June 28th, 2024, in the AI open source model ranking list released by Hugging Face, Ali Tongyi's Thousand Questions Model Qwen2 - 72B once again reached the top, becoming the No.1 in the global open source model ranking list. The second place was Facebook's llama3. Moreover, Ali's previous open source Qwen 1.5 basic and Chat versions were also on the list. In the top 10 of this list, Ali occupied four places. In addition, there was the November ranking of China's AI big model platform, but the reference materials did not give the specific ranking. 'The Myth of True Love in the Pangu Progenitor Universe' is equally wonderful. Please click to read it!

There were applications related to the Hunyuan model, such as the Hunyuan Assistant Mini programs (already online on WeChat), and the Hunyuan model APP (which could be used to operate 3D characters such as DreamWorks). In addition, the company also released the Yuanbao APP based on the Hunyuan model technology, which connected to more than 600 business scenarios of the company.

The official website of the Tiangong AI model is: <anno data-annotation-id ="000fd123 - 4110 - 4445-a110-a100 - 80111111000"></anno>. You can go to this website to see if there is any related download content. If you want to know more about the follow-up, click on the link and read it!

Huawei Pangu Concept's stocks are mainly distributed in the industries of 'IT Services',' vertical application software ', ' black home appliances ', ' film and television theatres','special equipment',' software development 'and the specific stocks are as follows: 1. IT services: iSoft Power (SZ301236), Yunding Technology (SZ000409), Beyondtech (SZ002649), Saiyi Information (SZ300687), Nanwei Software (SH603636), Dianke Digital (SH600850), Advanced Data Communication (SZ300541), Changshan Beiming (SZ000158); 2. vertical application software: Keda Controllers (BZ831832); 3. Black appliances: Jiulian Technology (SH688609); 4. Film and television theater: Jebsen (SZ300182); 5. Special equipment: Mayanson (SZ300275); 6. Software development: Tuoersi (SZ300229), Tuowei Information (SZ002261), Beixinyuan (SZ300352), Pan-micro Network (SH603039), and creative information (SZ300366). 'The Myth of True Love in the Pangu Progenitor Universe' is equally wonderful. Please click to read it!

The Pangu model was an artificial intelligence model jointly developed by Huawei Cloud, Circulation Intelligence, and Pengcheng Laboratory. It covered the large model of natural language processing, machine vision, and scientific computing. It was a large-scale artificial intelligence model for deep learning and training in specific industries or fields. It had powerful learning and reasoning capabilities, and could process massive amounts of data and extract valuable information from it. Different series are suitable for different scenarios. For example, Pangu E series of billions of parameters can be embedded in the terminal to run small models;Pangu P series of parameters can solve most AI application scenarios between 10 billion and 90 billion;Pangu U series of billions of parameters become a solid base for enterprise general large models;Pangu S series of trillions of parameters can handle cross-domain complex tasks. Moreover, Pangu Model 5.0 was upgraded in three aspects: full series, multi-mode, and strong thinking, including multi-mode understanding and multi-mode generation. It combined the thought chain technology and strategy search depth to improve the ability in mathematics, complex task planning, and logical thinking. 'The Myth of True Love in the Pangu Progenitor Universe' is equally wonderful. Please click to read it!

Training a large model involved many aspects, and the following were some of the key elements: ** 1. Model structure ** 1. ** Single-round dialogue sample ** - In the big model training, questions and instructions could be used as prompt input and answers as output. When calculating loss, the pad token had to be blocked. 2. ** Multiple dialogue samples ** - One way was to assume that the multiple rounds were Q1A1/Q2A2/Q3A3, which could be converted into three training samples: Q1->A1, Q1A1Q2- >A2, and Q1A1Q2A2Q3- >A3. However, there was a problem with this method. Most of the data was a pad token, which led to inefficient utilization of training data. There would also be the problem of data repetition. The repeated expansion of training data was the number of sessions * average number of rounds. At the same time, the repetition of the previous part would also make the training efficiency low. - The improved method was for decoder-only models. The input of the multi-round dialogue sample was <eos>Q1A1Q2A2Q3A3<eos><eos>. When calculating the loss, only the <eos>A1A2 <eos>and A3 <eos>parts needed to be calculated, so that session-level training could be carried out. ** 2. Selection and processing of samples ** 1. ** sample composition ** - As for the ratio of the Chinese and English mixed samples, there was no difference between different situations. For samples with strong logical reasoning (such as code, mathematics, etc.), the larger the model, the higher the mixing ratio. 2. ** Quality of sample ** - ** Basic Cleansing **: To clean the data that will cause the ppl to collapse, politically-sensitive data, and to remove the duplicate. - ** Advanced Cleansing **: You can produce a variety of labels to describe the data, but as the optimization goes on, the input output ratio of these labels becomes more and more difficult to evaluate. - ** PhI-style synthetic data **: For open source teams and small companies, the cost of building a pre-trained and cleaned pipeline is relatively high. They can do some clustered topics based on open source data, and then based on these topics, throw them into a larger model to build a batch of high-quality data. - [Buying data is also a way to obtain samples.] 3. ** Training samples from different training stages ** - ** High-quality samples at the end of the experiment (minipm)**: Normal samples were used in the fast convergence stage and the stable stage, and high-quality samples were mixed in the tempering stage for textbook learning. - ** High-quality samples in the early stage **: High-quality samples are used in the rapid convergence stage to allow the model to converge quickly. In the stable stage, the proportion is gradually adjusted to add more ordinary samples. The tempering stage is the same as the stable stage. - ** High-quality samples throughout the entire process (Phil method)**: High-quality samples throughout the entire process. In addition to sample-related content, training a large model also needed to consider many factors such as computing power and model structure. Different models might need to be adjusted and optimized according to their own characteristics. "A Short History of the Future: Legends of the Intelligent Era" was equally exciting. Everyone was welcome to click and read it!

According to the information provided, some of the companies that had outstanding performance in the field of AI models were 360, iFlytek, Palm Reading Technology, Hengsheng Technologies, Hehe Information, etc. These companies had their own highlights in terms of AI layout and business development. For example, 360 fully embraced artificial intelligence, self-developed 360 GPM, and promoted the implementation of the "360 smart brain"; iFlyTe had related achievements such as iFlyTe Spark; Palm Reading Technology had a certain connection with Wenxin Yiyan; Hang Sen Electronic released the financial industry model LightGPM; He He Information released the acge text Vectorization Model, but did not explicitly mention which were listed leading companies. Sorry, based on the information I retrieved, I don't know how to accurately answer which are the leading companies in the AI model market. 'The Myth of True Love in the Pangu Progenitor Universe' is equally wonderful. Please click to read it!

Concepts related to the Huawei AI model include: Leo shares (Active in the market in cooperation with the big language model), Jincai Internet (Cooperating with Huawei to develop the "Xinzhi Yue Finance Model"), Beixinyuan (Source Mixin AI ability platform has been adapted to domestic excellent large model AI products), Dongfang Guoxin, Rongji Software, Duolun Technology, Haoyun Technology, Gao Xinxing, Changliang Technology, Human M Network, Gaoling Information, Yuncong Technology, Sichuan University Zhisheng, Cape Cloud, Xinchen Technology, Tuowei Information, Changshan Beiming, Tongfang, Digital China (These companies have completed compatibility testing or in-depth cooperation with Huawei's MindSpore), Jebsen (signed a video model cooperation with Huawei Cloud), Changshan Beiming (as a strategic partner of Huawei and other identities, the stock price was stimulated by Pangu's big model news), etc. 'The Myth of True Love in the Pangu Progenitor Universe' is equally wonderful. Please click to read it!