DeepSeek shocks the AI world
A high performance, low cost, open-source contender sparks debate
The Chinese AI model DeepSeek has made waves with the release of its latest version (R1), which has
stunned the AI community. When compared to other top-tier models like ChatGPT, DeepSeek’s performance
stands on par, but with a significant advantage—its cost is far lower for end users and software
developers.
There’s little debate about DeepSeek’s capabilities. As an open-source model, it’s fully accessible to the
public, including the model and the techniques used to develop it. While DeepSeek introduced some of its
own innovations, the core methods it employed are widely available within the AI community.
AI research is constantly evolving, with breakthroughs happening regularly. These advancements paved the
way for DeepSeek’s development. What’s truly surprising, however, is that an open-source model like
DeepSeek can match the performance of the most well-funded, closed-source models.
From a technical standpoint, DeepSeek’s architecture is designed to maximize performance per unit of
compute, which in turn lowers costs while maintaining world-class capabilities.
This development has raised several important questions:
- Open Source vs. Closed Source: While models like ChatGPT (OpenAI) and Google’s Gemini are closed
source, Meta’s Llama and DeepSeek are open source. Which approach will prevail? - AI Capital Efficiency: With AI capital expenditures skyrocketing into the hundreds of billions annually,
can efforts spent on optimizing the performance of semiconductor chips significantly lower both
capital and operating costs? - New Competitors in the AI Space: Could the large language AI model industry be disrupted by a surge
of new challengers? - Can China Keep Up?: With increasingly stringent export restrictions on advanced AI chips, can Chinese
companies continue to make strides in AI? DeepSeek, a Chinese startup, has proven that it can
compete with the best, despite these challenges.
What is the probable outcome?
One likely consequence of DeepSeek’s success is that Western companies may adopt some of the techniques used to lower AI costs. This could lead to a reduction in the cost of both training AI models and running inferences. In the medium to long term, this reduced cost will likely drive greater user adoption. For example, the cost of producing AI agents could become much more affordable, benefiting AI-driven workers and robotics development.
The rise of DeepSeek mirrors trends seen in other industries. Historically, when China has faced restrictions on critical technologies and manufacturing equipment, innovative domestic companies have emerged to overcome these barriers. In sectors like robotics, 5G, software and semiconductors, prospects of similar restrictions have led to the development some of world-leading Chinese manufacturers.
The good news is that DeepSeek is open source. With detailed research papers and available code, other researchers and developers can study and build upon the techniques, ultimately advancing AI for the greater good of humanity.
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