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DeepBrain Chain: A Distributed High-Performance Computing Network for AI

Founded in 2017, DeepBrain Chain aims to create an infinitely scalable, distributed high-performance computing network using blockchain technology. Its goal is to serve as essential infrastructure in the 5G and AI era.

As artificial intelligence becomes increasingly integrated into daily life, the demand for computing power continues to grow. AI development relies on three key components: deep learning models, big data (from the internet, sensors, and IoT), and high-performance computing (GPUs, FPGAs, and specialized chips). The computing requirements for AI models are substantial:

- Image recognition (e.g., ImageNet): 1–10 GPUs
- Protein folding (e.g., AlphaFold/AlphaFold2): 100–200 GPUs
- Language models (e.g., BERT): 100–200 GPUs (or 1,026 TPUs to reduce training time to 76 minutes)
- Large-scale models (e.g., GPT-3): 1,000 GPUs, 175 billion parameters, with training costs reaching millions of dollars
- Multimodal pre-training models (e.g., BAAI’s models): 2,000 GPUs

The AI race is fundamentally a competition for computing power. Addressing the supply-demand imbalance and incentivizing computing power distribution is critical. DeepBrain Chain seeks to optimize global AI computing resources by leveraging blockchain to reduce costs, improve efficiency, and democratize access to AI computing power—accelerating the advancement of artificial intelligence.