Methodology
Last updated
Last updated
Darwin's methodology is built upon three core pillars: Economic, Accessible and Scalable. These pillars function in a cyclical, interconnected manner, continuously reinforcing each other to enhance the efficiency and effectiveness of the Darwin system.
Computing Democratization: Our distributed inference network empowers users with lower-end GPUs to actively participate in the ecosystem, breaking down barriers to entry in decentralized computing.
Extremely cost-efficient: Our novel probabilistic inference verification technology is the fastest and cheapest in the field. This innovation makes our network extremely cost efficient.
Unified API for all natural languages: In the real world, the development of Large Language Models is segmented: every cultural community is developing their own models, Chinese (Qwen), French(CroissantLLM), German(IGEL) and etc. In order to make AI apps ubiquitous, we provide a unified API for LLMs of all languages to make localization effortless.
Low Entry-Barriers: We’ve eliminated the traditional barriers to participation, inviting more contributors to build and expand the blockchain and AI node network, fostering innovation and collaboration.
Horizontal Scalability: Designed for growth, our infrastructure supports the horizontal expansion of AI nodes, allowing the network to scale effortlessly as demand increases.