Planck, an infrastructure protocol for the booming artificial intelligence, launched a layer 0 blockchain designed to support decentralized AI networks, the company said Tuesday.
The blockchain is intended to be used as the basic infrastructure for AI applications, especially for Decentralized physical infrastructure network (depins). These networks combine hardware, token incentives, and distributed processing to create alternatives to centralized resources such as cloud services.
The move is in line with an increasing push within the cryptocurrency industry, bringing the decentralized Web3 principle into AI development, a sector that remains dominated by centralized players such as OpenAI and Google.
“Currently, high-performance AI computing is being concentrated in the hands of several tech giants,” a Planck spokesman told Cointelegraph.
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Planck is one of several blockchain projects in alternative approaches to AI decentralization. For example, Bittensor focuses on decentralized machine learning, while Fetch.AI facilitates the creation of AI agents through its decentralized platform.
Planck said its blockchain will generate protocol revenue from transaction fees, SDK usage and developer tools. Meanwhile, the GPU operators providing computing resources will reward the protocol’s native token based on the machine’s uptime (proof of connectivity) and actual utilization (proof of exchange).
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GPU rental and AI chip shrinkage
Most of Planck’s revenue comes from renting GPUs and computing contracts. The company said its on-demand model cuts costs by up to 90% compared to traditional cloud services.
The company has earned $1.5 million in revenue since February, mainly from renting GPU power. The company also competes with other infrastructure providers such as Vast.AI, Coreweave and Lambda Taking advantage of ongoing AI chip shortages.
This shortage has fueled explosive growth in the GPU-AS-A-Service sector. according to For the first study, the market reached $4 billion in 2024 and is expected to grow at an interest rate of 23% per year and will reach $32 billion by 2034.
A Planck spokesman said: “Centralized AI computing is very expensive. By spreading the GPU network, Planck can save up to 90% of the cost.”
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