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Deep Seek: Revolutionizing AI Startups

Jan 13, 2025

Lecture on Deep Seek: A Dark Horse in AI Startups

Introduction

  • Discussion on Deep Seek, an emerging AI startup from China.
  • Notable for its rapid development in AI, despite challenges like chip embargoes and strict regulations.
  • Has developed a competitive large language model (LLM), DeepSeek v3.

Key Achievements

  • Founded less than two years ago, yet competitive with GPT-4 and other 2024 world-class LLMs.
  • Reduced LLM development costs significantly, making it 1/70th the cost of GPT-4.
  • Sparked a price war in China's AI industry, earning it the nickname "Pinduoduo of AI."

Company Background

  • Founded by engineers from Zhejiang University, originally as a quant hedge fund called High Flyer.
  • By 2021, all trading strategies were algorithm-driven.
  • In 2023, High Flyer announced a new focus on Artificial General Intelligence (AGI), leading to the creation of Deep Seek.

Model Development

  • DeepSeek V3 released in December 2024.
  • Competed well against GPT-4 and Claude 3.5 in benchmarks, especially in math and coding.
  • Developed on H800 chips, completed in 55 days costing around $5.6 million.
  • Compared to other models like Llama, DeepSeek is 11 times faster and 18 times cheaper.

Pricing Strategy

  • API usage cost significantly lower than counterparts like GPT-4.
  • DeepSeek's pricing strategy: price slightly above cost with a small margin.
  • Despite lower prices, company maintained profitability without external funding.

Innovative Training Approaches

  • Introduced Deepseek MoE architecture.
  • Focuses on activating specialized 'expert brains' in the model, reducing costs and training time.
  • Emphasizes cost-effective engineering and algorithmic innovation.

Performance Comparisons

  • DeepSeek vs. GPT-4 in math, coding, and philosophical challenges.
  • Noted for superior performance in math and coding challenges.
  • Deep think mode allows detailed reasoning process but may take more time.

Broader Implications

  • DeepSeek's approach challenges the status quo in AI development.
  • Raises questions about the future of AI leadership and innovation in China.
  • Highlights the shift from monetization focus to prioritizing research and innovation.
  • Open-sourcing their research to contribute to the tech community.

Future Considerations

  • Can China shift its image from low-cost manufacturing to a hub of innovation?
  • Significance of fostering an environment that supports failure and innovation.
  • Potential regulatory challenges for Chinese AI companies on a global stage.
  • Emphasis on building a research-focused culture and tapping into domestic talent.

Conclusion

  • Deep Seek's story signifies a potential shift in China's tech industry.
  • The importance of supporting innovation and research for long-term growth.
  • A transformative model for other startups in the AI landscape.

This concludes the key points from the lecture on Deep Seek and its impact on the AI industry. The startup's innovative strategies and low-cost model have positioned it as a significant player, challenging traditional approaches in AI development.

Full transcript