NeuralByte (ERC)
  • Introduction
    • NeuralByte Overview
    • Technical Overview
    • Technical Architecture
    • Technical Implementation
    • Challenges in Traditional AI Model Training
  • Ecosystem
    • How NeuralByte Works?
    • Benefits of NeuralByte
    • Decentralized Resource Pool
    • Competitive Pricing Model
    • Elimination of GPU and TPU Dependency
    • Built-in Library for AI Development
  • Others
    • Tokenomics
    • Roadmap Development
    • Links
    • Disclaimer
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  1. Ecosystem

Elimination of GPU and TPU Dependency

Unlike traditional AI processing methods that rely on specialized hardware such as GPUs and TPUs, NeuralByte leverages the collective computing power of its decentralized network. By distributing processing tasks across multiple nodes, NeuralByte effectively overcomes the limitations imposed by centralized hardware, offering scalability and flexibility to users.

  • NeuralByte Token integrates seamlessly with GPU and TPU clusters, harnessing their parallel processing capabilities for accelerated AI and ML workloads.

  • Users can specify their requirements for GPU or TPU resources, and the marketplace matches them with suitable providers.

  • Compatibility with diverse hardware configurations ensures flexibility and scalability.

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Last updated 1 year ago