DeepSeek, a Chinese startup founded in 2023 by Liang Wenfeng, specializes in the development of advanced artificial intelligence (AI) models. The company focuses on open-source large language models (LLMs) with an emphasis on efficiency and low costs.
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In January 2025, DeepSeek launched its AI model named DeepSeek-R1, which is distinguished by its advanced reasoning and mathematical problem-solving capabilities. This model was developed at significantly lower costs compared to competing models, attracting considerable attention from both the tech and financial sectors.
The success of DeepSeek-R1 had a major impact on global stock markets. Following its release, the stock values of major tech companies, including Nvidia, Microsoft, and Alphabet (Google’s parent company), dropped significantly. Investors expressed concerns about a potential challenge to U.S. dominance in artificial intelligence and the risk of losing market share to Chinese competitors.
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Despite its success, DeepSeek faces accusations of censorship and privacy concerns. It is well known that the DeepSeek-R1 model avoids answering politically sensitive questions in compliance with Chinese censorship laws, raising concerns about freedom of speech and the spread of propaganda.
With its innovative approach and rapid growth, DeepSeek is emerging as a major player in artificial intelligence, sparking debates about the future of AI and the need for its global regulation.
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DeepSeek recently introduced its latest artificial intelligence model, DeepSeek-V3, which brings significant innovations in the field of large language models (LLMs). This model utilizes a Mixture-of-Experts (MoE) architecture with a total of 671 billion parameters, while activating 37 billion parameters per token.
Key Innovations of DeepSeek-V3:
Computational Efficiency:
Thanks to optimizations such as the DualPipe algorithm, which overlaps computation and communication, and the use of FP8 mixed precision training, DeepSeek has significantly reduced computational costs.
The model was trained using 2,048 Nvidia H800 GPUs over two months, totaling approximately 2.8 million GPU hours.
In comparison, Meta’s Llama 3 required 30.8 million GPU hours on 16,384 Nvidia H100 GPUs.
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Open-Source Approach:
DeepSeek has made DeepSeek-V3 open-source, allowing researchers and developers worldwide to test and further develop it.
This approach not only supports transparency and collaboration within the AI community but also demonstrates that cutting-edge AI models can be developed with fewer resources. DeepSeek-V3 represents a major step forward in democratizing access to advanced AI technologies.
