In the MMC network, $MMC token serves as a utility token based on Computing Power as the Basis of Value, which aims to promote the trading and use of computing resources and provide more convenient trading and usage methods for computing nodes and end-users.
In the computing marketplace, people who hold $MMC can use it to purchase computing resources, and computing nodes can accept $MMC as a payment method for transactions. This trading method reduces transaction costs and time, and improves the liquidity and utilization of computing resources.
In addition to serving as a medium of exchange, MMC can also be used to reward the contribution of idle computing power to the network, subsidize buyers of computing power, and incentivize developers to contribute to the ecosystem. Smart contracts can be used to automate the management of computing resources and rewards, ensuring fair allocation of resources.
In the MMC ecosystem, $MMC can be used in various application scenarios, such as decentralized AI applications, blockchain games, and blockchain storage. These application scenarios can use $MMC to achieve more flexible and efficient resource management and trading methods, thereby improving the efficiency and performance of blockchain applications.
More computing power leads to new applications, which in turn attract more users. The growth of users inevitably leads to an explosion in demand for computing power. The flywheel has quietly begun to turn, and change is already underway. MMC, as a digital asset based on computing power pricing, will become an important part of the digital economy.
In the computing marketplace, people who hold $MMC can use it to purchase computing resources, and computing nodes can accept $MMC as a payment method for transactions. This trading method reduces transaction costs and time, and improves the liquidity and utilization of computing resources.
In addition to serving as a medium of exchange, MMC can also be used to reward the contribution of idle computing power to the network, subsidize buyers of computing power, and incentivize developers to contribute to the ecosystem. Smart contracts can be used to automate the management of computing resources and rewards, ensuring fair allocation of resources.
In the MMC ecosystem, $MMC can be used in various application scenarios, such as decentralized AI applications, blockchain games, and blockchain storage. These application scenarios can use $MMC to achieve more flexible and efficient resource management and trading methods, thereby improving the efficiency and performance of blockchain applications.
More computing power leads to new applications, which in turn attract more users. The growth of users inevitably leads to an explosion in demand for computing power. The flywheel has quietly begun to turn, and change is already underway. MMC, as a digital asset based on computing power pricing, will become an important part of the digital economy.
MMC Protocol: This protocol enhances the efficiency of dist.
MMC establishes a computing power RWA trading market by investing in and incubating Compute DAO, providing MMC token rewards. For more information, refer to the Compute DAO whitepaper.
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GPUs are the lifeblood of AI, powering complex computations.
But here’s the game-changer: MMC's decentralized approach.
It harnesses GPU resources more efficiently than ever before.
This not only accelerates AI development but also levels the playing field for all developers.
Dive into MMC’s service offerings today!
But here’s the game-changer: MMC's decentralized approach.
It harnesses GPU resources more efficiently than ever before.
This not only accelerates AI development but also levels the playing field for all developers.
Dive into MMC’s service offerings today!
The mission of MMC DAO is to promote the sustainable development and innovation of the MMC ecosystem, provide better governance and participation opportunities for members of the MMC community, and ultimately realize the vision of decentralized computing power to eliminate the digital divide and centralized monopoly.
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Minimum recommended hardware configuration:
AMD EPYC 7343 3.2GHz, 16C/32T, 128M Cache (190W)
32GB RDIMM, 3200MT/s, Dual Rank 16Gb BASE x8
7.68TB NVMe U.2
PowerEdge R6525 Motherboard, with 2 x 1Gb Onboard LOM (BCM5720)MLK V2
Dual, Hot-plug, Redundant Power Supply (1+1) 1100W
Broadcom 25 Gigabit P225P SFP28 Dual Port Network Card
AMD EPYC 7343 3.2GHz, 16C/32T, 128M Cache (190W)
32GB RDIMM, 3200MT/s, Dual Rank 16Gb BASE x8
7.68TB NVMe U.2
PowerEdge R6525 Motherboard, with 2 x 1Gb Onboard LOM (BCM5720)MLK V2
Dual, Hot-plug, Redundant Power Supply (1+1) 1100W
Broadcom 25 Gigabit P225P SFP28 Dual Port Network Card
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🚀 MMC Testnet Event Wrap-up🎉
The MMC Testnet Event wrapped up on October 20th, marking an exciting step forward. Thank you to all participants for your commitment and effort in this journey. Your feedback has been invaluable, and together, we’re setting the stage for the future! 🌐
Highlights:
👥 Participants: 18,064
🔄 Transactions: 189.5M
💎 MMCP Distributed: 20.88M
🔧 What’s Next?
We’ve noted your feedback on gas fees, token tracking, and GPU mining. Our team is working on solutions as we prepare for the mainnet launch. Stay tuned for updates and be ready to join the next phase of our journey! 📈
The MMC Testnet Event wrapped up on October 20th, marking an exciting step forward. Thank you to all participants for your commitment and effort in this journey. Your feedback has been invaluable, and together, we’re setting the stage for the future! 🌐
Highlights:
👥 Participants: 18,064
🔄 Transactions: 189.5M
💎 MMCP Distributed: 20.88M
🔧 What’s Next?
We’ve noted your feedback on gas fees, token tracking, and GPU mining. Our team is working on solutions as we prepare for the mainnet launch. Stay tuned for updates and be ready to join the next phase of our journey! 📈
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🚀 Get ready for the future of AI and blockchain!
Micro Matrix Computing
Explore MC: Decentralized AI Computing Power Application Network | Micro Matrix Computing
Learn about MC (Matrix Computing), a leading decentralized AI computing power application network. Discover its role as a representative project in the AI computing power domain. Join us today to e...
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AI Training and Inference
The process of utilizing MMC for AI training and AI inference is as follows:
Resource Preparation: MMC integrates idle GPUs from abandoned Ethereum (ETH) miners and Filecoin (FIL) miners to build a distributed GPU computing network. Before using MMC, it is necessary to ensure that the computing nodes have the appropriate hardware and the capability to connect to the MMC network.
Task Scheduling: The MMC protocol handles task scheduling and task distribution. During AI training, the task scheduling module divides the tasks into appropriate computing units and distributes them to participating computing nodes in the MMC network. This ensures that tasks can be efficiently and in parallel executed across the distributed GPU computing nodes.
AI Model Training: When using MMC for AI model training, the task scheduling module distributes the training tasks to available computing nodes. These nodes utilize their GPU computing power to execute the training tasks, performing backpropagation and parameter optimization using datasets, ultimately training high-performance AI models.
AI Inference: Once the AI models are trained, MMC can be used for AI inference. Inference tasks involve passing input data to the trained models and generating corresponding output results. The task scheduling module distributes the inference tasks to computing nodes, which leverage their GPU computing power to perform real-time processing of input data and generate inference results.
By distributing AI training and inference tasks to the distributed GPU computing network of MMC, task processing speed and computational efficiency can be accelerated. MMC's distributed architecture provides greater computational power and flexibility, enabling more efficient and scalable AI model training and inference.
It is important to note that utilizing MMC for AI training and inference requires appropriate technical configurations and resource management to ensure smooth task execution. Additionally, MMC provides economic incentives to encourage participation and contribution from computing nodes, further promoting the development and application of AI training and inference.
The process of utilizing MMC for AI training and AI inference is as follows:
Resource Preparation: MMC integrates idle GPUs from abandoned Ethereum (ETH) miners and Filecoin (FIL) miners to build a distributed GPU computing network. Before using MMC, it is necessary to ensure that the computing nodes have the appropriate hardware and the capability to connect to the MMC network.
Task Scheduling: The MMC protocol handles task scheduling and task distribution. During AI training, the task scheduling module divides the tasks into appropriate computing units and distributes them to participating computing nodes in the MMC network. This ensures that tasks can be efficiently and in parallel executed across the distributed GPU computing nodes.
AI Model Training: When using MMC for AI model training, the task scheduling module distributes the training tasks to available computing nodes. These nodes utilize their GPU computing power to execute the training tasks, performing backpropagation and parameter optimization using datasets, ultimately training high-performance AI models.
AI Inference: Once the AI models are trained, MMC can be used for AI inference. Inference tasks involve passing input data to the trained models and generating corresponding output results. The task scheduling module distributes the inference tasks to computing nodes, which leverage their GPU computing power to perform real-time processing of input data and generate inference results.
By distributing AI training and inference tasks to the distributed GPU computing network of MMC, task processing speed and computational efficiency can be accelerated. MMC's distributed architecture provides greater computational power and flexibility, enabling more efficient and scalable AI model training and inference.
It is important to note that utilizing MMC for AI training and inference requires appropriate technical configurations and resource management to ensure smooth task execution. Additionally, MMC provides economic incentives to encourage participation and contribution from computing nodes, further promoting the development and application of AI training and inference.
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🌐 DePIN Track Demo Day is here! Join us on Nov 7 to witness cutting-edge #DePIN innovations in action! 🚀
🗓 Date: Nov 7
🕒 Time: 12:00 PM - 2:00 PM (UTC)
🗓 Date: Nov 7
🕒 Time: 12:00 PM - 2:00 PM (UTC)
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Due to current market conditions I now identify as a memecoin.
The ticker is $MMC
The ticker is $MMC
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NVIDIA’s influence on AI growth shows the potential of this tech revolution. 🌍 #MMC is building a decentralized AI (#DeAI) framework to make these advances more trustworthy and accessible. The future is decentralized and intelligent! 🚀
#Web3 #Innovation
https://www.forbesmiddleeast.com/money/markets/nvidia-rallies-5-ahead-of-earnings-what-to-expect-from-most-important-stocks-report
#Web3 #Innovation
https://www.forbesmiddleeast.com/money/markets/nvidia-rallies-5-ahead-of-earnings-what-to-expect-from-most-important-stocks-report
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Pump is fun and makes it easy to try out buying for newbies. This is very similar to our concept of building MMC. I think it is time for them to cooperate.
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The AI track is heating up, and on-chain solutions are the way forward! 🔥
@MicroMatrixCalc
is perfectly suited for scaling global AI data solutions—transparent, efficient, and decentralized. 🌍
What’s your next big idea in #AI? Let’s make it happen! 🚀
#MMC #DeAI
@MicroMatrixCalc
is perfectly suited for scaling global AI data solutions—transparent, efficient, and decentralized. 🌍
What’s your next big idea in #AI? Let’s make it happen! 🚀
#MMC #DeAI
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MMC Official pinned «Due to current market conditions I now identify as a memecoin. The ticker is $MMC»