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Decentralized cryptographic processing fuels the growth of AI, with the adoption of Large Language Models (LLMs) rising to 46%

Growing Adoption of AI-centric Decentralized Computing Networks: In the United States, more than four in ten workers have integrated Large Language Models into their work, with this number projected to climb to 30.1 percent by the end of 2024.

Decentralized cryptocomputing propels AI progress, with Large Language Model use escalating to 46%...
Decentralized cryptocomputing propels AI progress, with Large Language Model use escalating to 46% in the current scenario

Decentralized cryptographic processing fuels the growth of AI, with the adoption of Large Language Models (LLMs) rising to 46%

In a significant development, the market for Artificial Intelligence (AI) computing power is expanding rapidly, particularly for companies with existing energy capacity, as stated by Ben Gagnon, CEO of Bitfarms. This shift signifies a new era in technology, where crypto infrastructures are not only limited to digital coins but are also driving the AI models forward, bridging the gap between blockchain technology and the future of artificial intelligence.

Early in 2025, the adoption of Large Language Models (LLMs) grew rapidly, reaching 43.2% by April. This trend remains clearly upward, with 45.9% of U.S. employees now using LLMs, up from 30.1% in December 2024. The increased usage of these models by employees is driving demand for faster and more powerful AI computing power.

In response to this growing demand, companies are shifting their focus towards high-performance computing (HPC) and AI tasks. Bitfarms, for instance, has transitioned from cryptocurrency mining to HPC and AI tasks, leveraging its advanced mining rig technology and aggressive growth strategy through acquisitions and expansion.

Another player in this evolving landscape is Hyper Bit Technologies, which shifted its focus in 2025 from cryptocurrency mining to high-performance computing and artificial intelligence.

Decentralized solutions like Spheron Network could play a central role in the next phase of AI development. Spheron Network is aiming to meet the growing demand for scalable and cost-effective computing capacity for AI. The network uses untapped resources and tokens to create incentives and bridge crypto innovation with the AI revolution.

Spheron Network distributes workloads across a global network, making AI computing power more accessible and affordable for developers and businesses alike. The decentralized approach of Spheron Network allows for efficient scaling and cost-effectiveness compared to traditional cloud services.

Spheron Network provides a community-operated infrastructure for decentralized computing power capable of handling the high demands of modern AI models. The network emphasizes the importance of increased usage per person and the growing complexity of models.

This shift towards decentralized computing power shows how crypto infrastructures can evolve beyond coins, driving AI models and shaping the future of artificial intelligence. Companies, developers, and individual users can benefit from distributed computing models that offer flexibility and cost-efficiency.

In conclusion, the market for AI computing power is vast, and companies with existing energy capacity, like Bitfarms, are well-positioned to capitalize on this opportunity. Decentralized networks like Spheron Network are well-positioned to provide the computing power needed in the new era of AI, making AI technology more accessible and affordable for everyone.

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