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AI Power of the Crowd Share and Be Shared
In the age of AI, computing power is the 'oil' of the artificial intelligence world. Let us together mine the 'oil' of the era of artificial intelligence.
Become the platform for the 2024 AI Boom Year, the decentralized computing power 'oil' of the global AI era.
Milestone
In the Era of Artificial Intelligence, Computing Power is the Oil.
May 30, 2023, Nvidia's market value surpassed one trillion US dollars, becoming the world's highest-valued chip company, twice the value of TSMC. It is also the fifth technology giant to enter the trillion-dollar club following Apple, Microsoft, Google, and Amazon. Nvidia has now become the biggest winner in the AI era, as global chip giants have taken control over the 'new generation oil.' Just six months ago, its market value was only 270 billion US dollars, which increased by 2.5 times in just over six months due to the artificial intelligence boom. The global surge of ChatGPT owes much to Nvidia, which initially provided 10,000 A100 GPU chips for its core hardware. Just as smartphones need Qualcomm and MediaTek chips, AI large models require Nvidia chips. The core elements of AI large models are computing power, algorithms, and parameters. If algorithms and parameters reflect a company's technical level, then computing power depends on the number of chips used. Currently, Nvidia dominates the AI chip market, holding over 60% of the market share. With every major player now developing AI, Nvidia's orders are more than they can supply. The price of A100 chips has soared by 40%, with orders backed up until December. Nvidia is currently the biggest winner in the AI era. Due to U.S. restrictions, it is difficult for many countries, companies, and individuals around the world to purchase chips like the A100 and H100.
DecentralizedAI computing power
Decentralized Computing Power Platform in the Era of Artificial Intelligence
Decentralized AI computing power refers to the distribution of AI computational capabilities across multiple nodes, rather than concentrating them in a single central node. This dispersed AI computing power can help reduce the waste of computational resources, improve computational efficiency, and simultaneously ensure data privacy and security.
The core of this dispersed AI computing capability is a decentralized network, consisting of multiple nodes, each with equal rights and obligations. These nodes can be servers, GPUs, or other computational resources owned by individuals, organizations, or enterprises. They can also be part of distributed computing platforms, such as OpenAI's DALL-E.
By distributing AI computing power across multiple nodes, users can better control their data privacy and security. Moreover, a decentralized network can also enhance the utilization of computational resources, reducing waste and costs.
Dispersed AI computing capability is a very important concept as it helps users better control their data privacy and security, improve the efficiency of computational resource usage, and is also expected to drive the development of decentralized computing technology.
Project Overview
When discussing the AI Computing Power Oilfield, it can be described as an AI training and upgrading platform based on the concept of decentralized computing power. This platform utilizes the idle computing power of users' mobile devices, providing the necessary computing power for AI models through an Application Programming Interface (API).
On this platform, each user is assigned a mobile application that allows them to provide computing power by running small-scale programs. These programs can be machine learning algorithms, deep learning models, or other forms of AI training. Users who provide computing power will receive rewards from the platform, which can be used to purchase resources needed for AI training, such as GPUs and TPUs.
The AI Computing Power Ark platform adopts a decentralized approach, enabling every user to freely provide and obtain computing power without the need for centralized institutions. This approach helps to increase the enthusiasm of computing power providers and ensures the fairness of resource distribution.
The goal is to have every individual’s mobile chip contribute computing power to our artificial intelligence. This is possible because modern smartphones are equipped with processors and storage devices capable of performing computational tasks, thus providing computing power for AI training and inference. By utilizing the idle computing power of individuals to assist in AI learning, better training results and faster inference speeds can be achieved.
In summary, the AI Computing Power Ark is an application that uses idle mobile computing power for AI training and upgrading. It achieves efficient computing power distribution and management through the concept of decentralized computing, offering new ideas and pathways for the development of AI technology.
Product Advantages and Future
The advantage of the AI Computing Power Ark lies in its decentralized approach, allowing each user to freely provide and obtain computing power without reliance on centralized institutions. This decentralization enhances the enthusiasm of computing power providers and ensures fair resource distribution. Additionally, AI Computing Power Ark employs the concept of decentralized computing, enabling free allocation of computing power to different AI models for training and upgrading, thus improving the efficiency and flexibility of computing power utilization.
Furthermore, the AI Computing Power Oilfield adopts blockchain technology, ensuring the security and stability of the platform. Blockchain technology secures data safety and privacy while enabling decentralized transactions and settlements, thereby enhancing the platform's efficiency and quality.
In summary, the advantages of AI Computing Power Ark include its decentralized approach, which improves the efficiency and flexibility of computing power utilization; the use of decentralized computing concept, ensuring fair resource distribution; and the adoption of blockchain technology, ensuring platform security and stability. These advantages make AI Computing Power Ark a popular AI computing platform. As an AI computing platform, AI Computing Power Ark has a broad development prospect. With the continuous development and popularization of AI technology, the demand for AI computing power is increasing. AI Computing Power Ark leverages users' idle mobile computing power for AI training and upgrading, enhancing the enthusiasm of providers and ensuring fair resource distribution. This decentralized approach also helps improve the platform's security and stability.
Additionally, with the widespread adoption of mobile internet, more people have idle mobile computing power, expanding AI Computing Power Ark's user base and potential market.
Technical Framework
Decentralized Architecture: The AI Computing Power Oilfield adopts a decentralized approach, allowing each user to provide computing power through their mobile devices, without relying on centralized institutions. This decentralization enhances the enthusiasm of computing power providers and ensures fair resource distribution.
Blockchain Technology: The AI Computing Power Oilfield employs blockchain technology to ensure the security and stability of the platform. Blockchain technology secures data safety and privacy, and also enables decentralized transactions and settlements, thereby improving the platform's efficiency and quality.
Computing Power Sharing Platform: The AI Computing Power Oilfield has built a computing power sharing platform, where users can freely provide and obtain computing power on the platform without depending on centralized institutions. This platform improves the efficiency and flexibility of computing power utilization.
Smart Contracts: AI Computing Power Ark utilizes smart contract technology to ensure the automation and fairness of the platform's transaction and settlement processes. Smart contracts enable decentralized transactions and settlements and also ensure the security and privacy of data.
The Roles of Computing Power, Algorithms, and Parameters in the Field of Artificial Intelligence
Computing Power refers to computational capacity, or the processing speed of computers. In the field of artificial intelligence, computing power plays a crucial role. Artificial intelligence models require continuous computation and training to learn and optimize. If the computing power is insufficient, the training speed of the model becomes very slow, or it might even be impossible to train. Therefore, adequate computing power is a prerequisite for efficient training and accurate prediction of AI models.
Algorithms refer to the algorithms used in AI models, that is, the mathematical models and algorithms employed by the models. The algorithm is the core of an AI model; it determines the accuracy and efficiency of the model. Different algorithms are suitable for different scenarios and tasks. For example, neural network algorithms are suitable for image and speech recognition tasks, while decision tree algorithms are suited for classification tasks, and so on.
Parameters refer to the parameters within the model, that is, the mathematical parameters used by the model to fit data. Parameters are at the core of the model; they determine the model's accuracy and generalization ability. Adjusting the parameters can improve the model's accuracy, but too many parameters can make the model overly complex and difficult to train. Therefore, the selection and adjustment of parameters is a very important skill in the field of artificial intelligence.
In summary, computing power, algorithms, and parameters all play a very important role in the field of artificial intelligence. Adequate computing power ensures efficient training and accurate prediction of models, while the selection and adjustment of algorithms and parameters can make the models more accurate and intelligent.
The Importance of Computing Power
In the era of artificial intelligence, computing power plays a vital role and can be considered as the energy source of artificial intelligence. This is because artificial intelligence algorithms require a large amount of computational resources for training and inference, especially in areas like deep learning, where the investment in computational resources directly affects the performance and accuracy of the models.
Therefore, the competition for computing power has become an important aspect of the artificial intelligence field. Major technology companies are actively investing in powerful computational infrastructures and algorithm research to gain stronger computing capabilities, thereby maintaining a competitive edge.
Beyond the intrinsic value of computing power, investments in computing power also contribute to the development of the entire artificial intelligence ecosystem. Strong computational capabilities can speed up the training and inference of models, allowing for the use of more data, and further driving the innovation and development of algorithms.
Roadmap--2024
January 1, 2024: Launch of the Starcoin Computing Power Oilfield Project.
First Quarter of 2024: Achievement of the Star Computing Power Model 1.0.
Second to Third Quarter of 2024: Launch of the Star Test Mainnet.
Fourth Quarter of 2024: Launch of the Star Computing Power Application Store: Star Store.
AI Power of the Crowd Share and Be Shared
In the age of AI, computing power is the 'oil' of the artificial intelligence world. Let us together mine the 'oil' of the era of artificial intelligence.
Become the platform for the 2024 AI Boom Year, the decentralized computing power 'oil' of the global AI era.
Milestone
In the Era of Artificial Intelligence, Computing Power is the Oil.
May 30, 2023, Nvidia's market value surpassed one trillion US dollars, becoming the world's highest-valued chip company, twice the value of TSMC. It is also the fifth technology giant to enter the trillion-dollar club following Apple, Microsoft, Google, and Amazon. Nvidia has now become the biggest winner in the AI era, as global chip giants have taken control over the 'new generation oil.' Just six months ago, its market value was only 270 billion US dollars, which increased by 2.5 times in just over six months due to the artificial intelligence boom. The global surge of ChatGPT owes much to Nvidia, which initially provided 10,000 A100 GPU chips for its core hardware. Just as smartphones need Qualcomm and MediaTek chips, AI large models require Nvidia chips. The core elements of AI large models are computing power, algorithms, and parameters. If algorithms and parameters reflect a company's technical level, then computing power depends on the number of chips used. Currently, Nvidia dominates the AI chip market, holding over 60% of the market share. With every major player now developing AI, Nvidia's orders are more than they can supply. The price of A100 chips has soared by 40%, with orders backed up until December. Nvidia is currently the biggest winner in the AI era. Due to U.S. restrictions, it is difficult for many countries, companies, and individuals around the world to purchase chips like the A100 and H100.
DecentralizedAI computing power
Decentralized Computing Power Platform in the Era of Artificial Intelligence
Decentralized AI computing power refers to the distribution of AI computational capabilities across multiple nodes, rather than concentrating them in a single central node. This dispersed AI computing power can help reduce the waste of computational resources, improve computational efficiency, and simultaneously ensure data privacy and security.
The core of this dispersed AI computing capability is a decentralized network, consisting of multiple nodes, each with equal rights and obligations. These nodes can be servers, GPUs, or other computational resources owned by individuals, organizations, or enterprises. They can also be part of distributed computing platforms, such as OpenAI's DALL-E.
By distributing AI computing power across multiple nodes, users can better control their data privacy and security. Moreover, a decentralized network can also enhance the utilization of computational resources, reducing waste and costs.
Dispersed AI computing capability is a very important concept as it helps users better control their data privacy and security, improve the efficiency of computational resource usage, and is also expected to drive the development of decentralized computing technology.
Project Overview
When discussing the AI Computing Power Oilfield, it can be described as an AI training and upgrading platform based on the concept of decentralized computing power. This platform utilizes the idle computing power of users' mobile devices, providing the necessary computing power for AI models through an Application Programming Interface (API).
On this platform, each user is assigned a mobile application that allows them to provide computing power by running small-scale programs. These programs can be machine learning algorithms, deep learning models, or other forms of AI training. Users who provide computing power will receive rewards from the platform, which can be used to purchase resources needed for AI training, such as GPUs and TPUs.
The AI Computing Power Ark platform adopts a decentralized approach, enabling every user to freely provide and obtain computing power without the need for centralized institutions. This approach helps to increase the enthusiasm of computing power providers and ensures the fairness of resource distribution.
The goal is to have every individual’s mobile chip contribute computing power to our artificial intelligence. This is possible because modern smartphones are equipped with processors and storage devices capable of performing computational tasks, thus providing computing power for AI training and inference. By utilizing the idle computing power of individuals to assist in AI learning, better training results and faster inference speeds can be achieved.
In summary, the AI Computing Power Ark is an application that uses idle mobile computing power for AI training and upgrading. It achieves efficient computing power distribution and management through the concept of decentralized computing, offering new ideas and pathways for the development of AI technology.
Product Advantages and Future
The advantage of the AI Computing Power Ark lies in its decentralized approach, allowing each user to freely provide and obtain computing power without reliance on centralized institutions. This decentralization enhances the enthusiasm of computing power providers and ensures fair resource distribution. Additionally, AI Computing Power Ark employs the concept of decentralized computing, enabling free allocation of computing power to different AI models for training and upgrading, thus improving the efficiency and flexibility of computing power utilization.
Furthermore, the AI Computing Power Oilfield adopts blockchain technology, ensuring the security and stability of the platform. Blockchain technology secures data safety and privacy while enabling decentralized transactions and settlements, thereby enhancing the platform's efficiency and quality.
In summary, the advantages of AI Computing Power Ark include its decentralized approach, which improves the efficiency and flexibility of computing power utilization; the use of decentralized computing concept, ensuring fair resource distribution; and the adoption of blockchain technology, ensuring platform security and stability. These advantages make AI Computing Power Ark a popular AI computing platform. As an AI computing platform, AI Computing Power Ark has a broad development prospect. With the continuous development and popularization of AI technology, the demand for AI computing power is increasing. AI Computing Power Ark leverages users' idle mobile computing power for AI training and upgrading, enhancing the enthusiasm of providers and ensuring fair resource distribution. This decentralized approach also helps improve the platform's security and stability.
Additionally, with the widespread adoption of mobile internet, more people have idle mobile computing power, expanding AI Computing Power Ark's user base and potential market.
Technical Framework
Decentralized Architecture: The AI Computing Power Oilfield adopts a decentralized approach, allowing each user to provide computing power through their mobile devices, without relying on centralized institutions. This decentralization enhances the enthusiasm of computing power providers and ensures fair resource distribution.
Blockchain Technology: The AI Computing Power Oilfield employs blockchain technology to ensure the security and stability of the platform. Blockchain technology secures data safety and privacy, and also enables decentralized transactions and settlements, thereby improving the platform's efficiency and quality.
Computing Power Sharing Platform: The AI Computing Power Oilfield has built a computing power sharing platform, where users can freely provide and obtain computing power on the platform without depending on centralized institutions. This platform improves the efficiency and flexibility of computing power utilization.
Smart Contracts: AI Computing Power Ark utilizes smart contract technology to ensure the automation and fairness of the platform's transaction and settlement processes. Smart contracts enable decentralized transactions and settlements and also ensure the security and privacy of data.
The Roles of Computing Power, Algorithms, and Parameters in the Field of Artificial Intelligence
Computing Power refers to computational capacity, or the processing speed of computers. In the field of artificial intelligence, computing power plays a crucial role. Artificial intelligence models require continuous computation and training to learn and optimize. If the computing power is insufficient, the training speed of the model becomes very slow, or it might even be impossible to train. Therefore, adequate computing power is a prerequisite for efficient training and accurate prediction of AI models.
Algorithms refer to the algorithms used in AI models, that is, the mathematical models and algorithms employed by the models. The algorithm is the core of an AI model; it determines the accuracy and efficiency of the model. Different algorithms are suitable for different scenarios and tasks. For example, neural network algorithms are suitable for image and speech recognition tasks, while decision tree algorithms are suited for classification tasks, and so on.
Parameters refer to the parameters within the model, that is, the mathematical parameters used by the model to fit data. Parameters are at the core of the model; they determine the model's accuracy and generalization ability. Adjusting the parameters can improve the model's accuracy, but too many parameters can make the model overly complex and difficult to train. Therefore, the selection and adjustment of parameters is a very important skill in the field of artificial intelligence.
In summary, computing power, algorithms, and parameters all play a very important role in the field of artificial intelligence. Adequate computing power ensures efficient training and accurate prediction of models, while the selection and adjustment of algorithms and parameters can make the models more accurate and intelligent.
The Importance of Computing Power
In the era of artificial intelligence, computing power plays a vital role and can be considered as the energy source of artificial intelligence. This is because artificial intelligence algorithms require a large amount of computational resources for training and inference, especially in areas like deep learning, where the investment in computational resources directly affects the performance and accuracy of the models.
Therefore, the competition for computing power has become an important aspect of the artificial intelligence field. Major technology companies are actively investing in powerful computational infrastructures and algorithm research to gain stronger computing capabilities, thereby maintaining a competitive edge.
Beyond the intrinsic value of computing power, investments in computing power also contribute to the development of the entire artificial intelligence ecosystem. Strong computational capabilities can speed up the training and inference of models, allowing for the use of more data, and further driving the innovation and development of algorithms.
Roadmap--2024
January 1, 2024: Launch of the Starcoin Computing Power Oilfield Project.
First Quarter of 2024: Achievement of the Star Computing Power Model 1.0.
Second to Third Quarter of 2024: Launch of the Star Test Mainnet.
Fourth Quarter of 2024: Launch of the Star Computing Power Application Store: Star Store.