Deep Seek Mystery - The Plot Thickens
Title: DeepSeek's R1 Model and the AI Industry: A Breakdown of Dario Amade's Essay
In recent news, Dario Amade, the former employee at OpenAI and current CEO and founder of Anthropic, has released an essay discussing deep learning model innovation and GPU export controls to China. This essay comes at a time when evidence suggests that DeepSeek's R1 model may have distilled a significant amount of data from OpenAI's models.
The AI industry is abuzz with rumors and possible evidence that DeepSeek's R1 model was trained using data inappropriately obtained from OpenAI's models. While OpenAI has not definitively accused DeepSeek of this, some instances have been reported where DeepSeek's R1 model claims to have been trained by OpenAI. Although models can hallucinate, this raises concerns within the AI community.
Jonathan Ross, CEO and founder of Grock, an inference provider that only works with open-source models, has commented on the possibility of distillation. Distillation involves a smaller model learning from a larger one, and Ross suggests that DeepSeek may have spent more on research and development, including distilling or scraping data from OpenAI's models, than initially reported.
In his essay, Dario Amade discusses China's export controls and their potential impact on the AI industry. He believes that the recent reaction to DeepSeek's R1 model, including a 16% drop in Nvidia's stock, was an overreaction. Amade argues that this drop shows a lack of understanding among analysts and investors regarding AI advancements.
Amade's essay focuses on two possible futures for AI development, highlighting the importance of export policies. He discusses three dynamics of AI development: scaling laws, shifting curves, and shifting paradigms. Scaling laws dictate that increasing the training of AI systems leads to better results on a range of cognitive tasks. Shifting curves refer to improvements in software, architecture, and hardware that provide significant jumps in efficiency and quality. Shifting paradigms involve changing the underlying scaling process, such as using reinforcement learning to train models to generate chains of thought.
Amade argues that the recent improvements in AI development, such as DeepSeek's R1 model, are a result of these dynamics and not a unique breakthrough. He predicts that AI smarter than humans will require millions of chips, tens of billions of dollars, and is most likely to happen in 2026-2027. If China can acquire the necessary resources, the world could see a bipolar power structure with the US and China leading in AI advancements. However, if China is unable to obtain these resources, the US and its allies will maintain their lead.
Amade emphasizes the importance of export controls in maintaining the US's lead in AI development. He believes that the performance of DeepSeek's models indicates China's seriousness as a competitor in the AI industry. However, he also notes that a double-digit drop in Nvidia's stock following the release of DeepSeek's models was baffling, as the AI industry's future trajectory remains misunderstood by many investors and analysts.
In conclusion, Dario Amade's essay offers insights into the current state of the AI industry, the potential impact of DeepSeek's R1 model, and the importance of export controls in maintaining a competitive edge. As the AI industry continues to evolve, understanding these dynamics will be crucial for investors, analysts, and industry leaders alike.
Link: Deep Seek Mystery
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