What is Decentralized Compute?
Decentralized computing is a way of organizing and processing data without relying on a central server. Instead of being centralized in one place, resources such as CPU, GPU, memory, and storage are shared across multiple computers (also known as nodes). These computers work together to perform tasks without the control of a central organization or authority.
In the crypto and blockchain world, decentralized computing is the key foundation that enables decentralized applications (dApps) and blockchain systems to operate transparently, securely, and without relying on third parties.
Simply put, decentralized computing is like having many people contribute to complete a job instead of relying on just one person, making the job faster, safer and reducing costs.
How decentralized computing works
Decentralized computing networks provide computing services in a distributed and secure manner, distributing computational tasks across multiple network nodes instead of relying on a central server. This provides the following benefits:
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Resource Distribution : Use idle computing power from computers, GPUs or other devices globally, creating an efficient system and reducing waste.
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Anti-censorship : Eliminates dependence on large tech companies, reducing the risk of censorship or restrictions by central servers.
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Transparency and security : Blockchain ensures that all transactions and processes are transparent and immutable, increasing user trust.
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Cost-effective : Leveraging redundant resources means service costs are often lower than centralized platforms like AWS or Google Cloud.
Since 2023, interest in artificial intelligence (AI) has fueled the rapid growth of decentralized computing networks. According to data from CoinMarketCap, AI and Big Data-related tokens have grown significantly, with some tokens such as The Graph (GRT) up 171%, SingularityNET (AGIX) up 857%, Fetch.ai (FET) up 313%, and Ocean Protocol (OCEAN) up 125% year-to-date.

Users who need computing power pay in tokens, while those who provide resources receive rewards corresponding to the work processed.
Smart contracts ensure that all tasks, payments and rewards are automated and transparent. Complex tasks are broken down and processed in parallel, and the results are verified by a consensus mechanism, ensuring accuracy and no fraud.
Results and data are stored on decentralized platforms like IPFS , increasing security and transparency.
Some specific applications:
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Decentralized Computing : Leverage idle GPUs to create an open computing marketplace. Projects like Render Network (RNDR) and Akash Network (AKT) have successfully implemented this model, providing computing power for AI, graphics rendering, and Web3 applications.
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Decentralised ML Training : Focuses on AI training, helping machine learning models learn from data and make decisions on their own. Notable projects include Bittensor and Gensyn.
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zkML : Combining machine learning with Zero-Knowledge Proof techniques , zkML enables verification of models and algorithms without revealing detailed data.
Some popular Decentralized Compute projects
Decentralized AI Compute and GPU Networks
Render Network focuses on providing decentralized GPU power for rendering images, videos, and complex 3D graphics tasks.
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Practical application: Render Network serves filmmakers, digital artists, and game companies directly, reducing costs and time compared to centralized services.
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Major Partners: There is cooperation with famous developers in the graphics industry.
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Scalability: Leveraging idle GPUs globally, the network provides powerful resources without requiring expensive hardware from the user side.
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Advantages: Cost savings and higher performance service delivery compared to centralized solutions like AWS or Google Cloud.

ZKML (Zero-Knowledge Machine Learning)
RISC Zero is a platform for building Machine Learning models using Zero-Knowledge Proofs (ZKP) technology, ensuring data security.
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Data Security: RISC Zero supports AI training and inference without revealing sensitive data, which is important in industries like healthcare, finance.
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Technological Innovation: Leveraging ZKP, the project brings greater transparency and efficiency in big data processing.
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Growth potential: Widely used in cases requiring high security and privacy, such as identity verification or financial transactions.
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Pros: Enhanced privacy and security in AI, which is difficult to achieve with centralized platforms.
Decentralised ML Training
Bittensor (TAO) and Gensyn are two prominent projects in the field of decentralized Machine Learning training.
Bittensor decentralized network is developed for artificial intelligence, combining blockchain technology with AI to create an open AI ecosystem that is not controlled by any single entity.
As of November 2024, Bittensor’s value has increased by more than 105% YTD, reaching an all-time high in April 2024.
Growth drivers:
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Subnet Expansion: The rapid expansion of subnets in the Bittensor ecosystem has increased network capacity, attracting more developers and users.
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AI Trends: The growing interest in AI has driven the growth and acceptance of Bittensor in the market.
Gensyn is building a decentralized computing network that allows AI developers to access computing resources flexibly and cost-effectively, while ensuring security and transparency through blockchain.
Investors and funding rounds:
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Series A Round (June 12, 2023): Gensyn raises $43 million, led by a16z (Andreessen Horowitz), with participation from CoinFund, Canonical Crypto, Protocol Labs, and Eden Block.
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Seed Round (March 21, 2023): Raised $6.5 million from funds such as Eden Block, Galaxy, and CoinFund.
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Pre-Seed Round (January 1, 2021): Raised $1.1 million from 7percent Ventures, Entrepreneur First, and Id4 Ventures.
In addition to leading the Series A funding round, a16z also announced a strategic partnership with Gensyn, supporting the project in its development and expansion.
ZK Coprocessors
Axiom offers coprocessors based on Zero-Knowledge Proofs to support complex and secure data processing.
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Integration: Axiom easily integrates with existing blockchains, expanding computational capabilities without increasing network load.
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High Security: Based on ZKP technology, Axiom ensures that computations can be verified without revealing the input data.
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Performance: Minimize on-chain processing costs by leveraging off-chain co-processing solutions.
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Helps improve performance and security in blockchain applications, especially in decentralized finance (DeFi) and governance.
Each project represents a major step forward in decentralized computing, helping to shape the future of the field.