DeepSeek supports companies hosting their R1 open source model, demonstrating how the artificial general intelligence (AGI) landscape is expanding beyond zero-sum competition. First-mover advantages are proving less significant in this emerging market, as building frontier models no longer provides a sustainable competitive moat. Soon, even hosting open source or weight models will become widely accessible. Open science is creating value for all participants, though this perspective remains underappreciated outside specialist circles.
DeepSeek, sometimes referred to as "the WHALE," has emerged as a formidable player in the field. Their engineering team demonstrates exceptional talent, particularly in systems optimization and GPU parallel/CUDA programming—areas where Western companies have unexpectedly ceded ground to Chinese engineers.
Since 2019, DeepSeek has rapidly advanced in large language model (LLM) innovation. They've released portions of their HAI-LLM model training framework and tools for inference and model serving, documenting their work primarily in Chinese-language publications. Their model uses a Mixture-of-Experts (MoE) architecture, which introduces significantly greater technical complexity compared to sparse models.
The company has effectively leveraged open machine learning and AI research literature since the beginning of modern deep learning, refining algorithms to scale their LLMs despite computing resource constraints, especially following the H100 GPU ban. Thanks to open research on arXiv and the Chinese community's expertise in hardware optimization and reverse engineering, they've developed specialized optimizations for the H800 GPU architecture, creatively overcoming challenges imposed by US restrictions.
Unlike the public controversies surrounding OpenAI, Sam Altman, and Elon Musk—characterized by dramatic announcements and vague posts - DeepSeek has distinguished itself through drama-free open source releases of models and tools, demonstrating mastery during AI race chaos.