In the tech world, two innovations have been making headlines – Bitcoin’s eco-friendly transformation and the growing energy appetite of Artificial Intelligence (AI). Bitcoin, once notorious for its electricity consumption, has embraced renewable energy, while AI, driven by power-hungry processors, faces environmental concerns.
AI’s rapid adoption predicts a rising carbon footprint. Training just one AI model can emit as much CO2 as five cars produce in a lifetime. Generative AI tools like ChatGPT, powered by energy-demanding GPUs, add to the strain. The older GPT-3 model alone consumes significant water and electricity.
Cloud computing, which supports AI and various other tasks, also consumes enormous energy. The global cloud computing infrastructure now exceeds the pre-COVID air travel industry’s carbon footprint.
The solution may lie in blockchain technology. Bitcoin mining, now powered by renewable energy, offers insights into reducing AI’s energy woes. Some mining operations adapt to meet AI’s energy needs, tapping into green or unused energy sources.
Blockchain can create a globally distributed supercloud powered by clean energy. It streamlines revenue distribution among green energy providers within the network. Additionally, it can automate the allocation of carbon credits, speeding up renewable energy infrastructure expansion.
CUDOS, a decentralized blockchain-based network, aims to scale GPU-reliant technologies sustainably. It utilizes blockchain to aggregate renewable energy-powered cloud computing resources across various locations, reducing expenses and environmental impact.
Matt Hawkins, CEO of CUDOS, believes AI adoption is soaring across industries, but challenges like limited processing power and massive energy demands persist. The company seeks to provide a sustainable and scalable cloud model to address these issues.
By distributing computing resources globally, CUDOS offers flexibility for AI and Web3 apps, ensuring compliance and data sovereignty. It minimizes security risks by isolating potential attacks on specific nodes, enhancing overall network security.
