TThe announcement of Deepseek, an open-source AI LLM from a Chinese company boasting significantly lower training costs, has rightfully sparked global curiosity. But alongside the justified intrigue, there’s been an overreaction bordering on panic. Some companies are even considering abandoning their AI investments in favor of Deepseek. To me, this is an emotional response rather than a rational one.
Here’s why:
GPUs: The Demand Won’t Decrease
The excitement over Deepseek’s cheaper training costs has led to wild conclusions about GPU demand. However, GPUs are most needed for inference, not just training. Even if training becomes more efficient, the need for GPUs won’t drop. In fact, history shows us that as services get cheaper, adoption widens, creating even greater infrastructure demands. So no, this isn’t the death knell for GPU investments; it might actually fuel their growth.
Propoganda vs Bias
Bias in LLMs is a common topic of debate, but I find it astounding how little attention has been given to Deepseek’s unique context. The model, developed in China, is not just trained on data—it is hardcoded with CCP-approved propaganda on sensitive issues. Prompts about Taiwan, the Uyghurs, forced labor, or the South China Sea return CCP-sanctioned answers, often bypassing reasoning processes entirely.
This presents a serious issue for organizations considering integrating Deepseek into workflows related to relief efforts, business strategy, or geopolitical decisions. Unlike OpenAI’s ChatGPT or Anthropic’s Claude—which are far from perfect but open to criticizing Western policies—Deepseek shows no willingness to deviate from party lines. Before rushing to adopt it, organizations need to weigh these risks carefully.
Acknowledging the Innovation
None of this is to dismiss Deepseek’s impressive achievements. The ability to train an LLM at a fraction of the cost is groundbreaking, and the decision to release it as open-source is a commendable contribution to the global AI community. As Yann LeCun noted, this development underscores the potential of open-source models to rival closed-source alternatives—a win for transparency and innovation.
*MIT Technology Review *has a great article examining the implications of Deepseek's release and changes in the AI landscape. I recommend reading it if you want a deeper understanding.
A Balanced Perspective
Deepseek is an extraordinary technical achievement, but it’s not a panacea. It won’t collapse GPU demand, and it comes with significant ethical and operational concerns. Let’s celebrate the ingenuity while keeping a critical eye on the implications, particularly for businesses and organizations navigating global markets.
In the rush to adopt AI, let’s not lose sight of caution and context. What are your thoughts on Deepseek and the broader implications for AI development?