DeepSeek AI: Open Models vs. Proprietary Control

The AI landscape is evolving rapidly, and as with every breakthrough technology, excitement runs high. However, with DeepSeek AI, there’s a noticeable surge of enthusiasm. While almost everything has been said about DeepSeek, there is one thing that stands out—a point raised by Yann LeCun, a leading figure in AI research: the real question isn’t whether China is catching up to the U.S. in AI, but rather the growing dominance of open models, sometimes even surpassing their proprietary counterparts.

Indeed, this shift in dynamics is worth noting. When a model is made publicly accessible, it provides researchers, developers, and businesses with a solid foundation to innovate faster and more collaboratively. DeepSeek AI, for example, is built on open technologies and resources that anyone can access. This democratization of AI is changing the game in ways we haven’t fully realized yet.

Open Models: The Changing Landscape of AI

Llama, another prominent model, created by Meta, also sits on an open foundation. At its core, Llama leverages the Transformer architecture, which was first introduced in a groundbreaking 2017 research paper. The success of such models is a testament to global collaboration, as many of the best advancements in AI today are the result of collective efforts from researchers across the globe. Llama is a shining example of how far open collaboration can take us.

The difference between DeepSeek AI and Llama is not in their origins or architecture but in how they approach distribution and access. DeepSeek, for example, has chosen to release its weights with a certain level of freedom, which allows for flexibility. While it may not be entirely open-source in the strictest sense, it offers a notable degree of accessibility.

In contrast, Meta’s Llama is distributed under a more restrictive license, which places significant limits on its commercial usage. While both models are available to the public, there are conditions attached—especially when it comes to commercial applications.

The Tension Between Open Source and Proprietary Control

This brings us to an important question: Are major companies genuinely playing the open-source game, or are they using openness merely as a lever to move faster, without giving back in equal measure?

The success of DeepSeek AI demonstrates that an open model can compete with, and even outpace, proprietary approaches. But it also highlights a fundamental contradiction: if the openness isn’t balanced, it becomes a one-way street where some parties reap the benefits without contributing anything back. We’ve already seen this pattern with OpenAI, which started with a commitment to openness but gradually began restricting access to key models.

Could DeepSeek AI eventually follow suit? The possibility is real. The company might choose to maintain an image of openness, continuing to release certain components to the public while locking down critical datasets, optimizations, and other valuable assets.

This creates an interesting dilemma for the future of AI development: How do we ensure that open-source models remain equitable, collaborative spaces rather than becoming a tool for just a few to gain a strategic edge?

Is Open Source Really Open?

The question of whether open-source is truly “open” is more than just theoretical. The key challenge in this space is maintaining the integrity of openness. Open models like DeepSeek can undoubtedly thrive in a world where companies balance open access with responsible use. However, if businesses begin to control access in a way that stifles genuine collaboration, we may find ourselves in a situation where only a handful of players benefit from the openness of others.

So, how do we avoid this potential trap? The future of open-source AI depends on trust and collaboration. Researchers and companies must be willing to contribute, not just consume, and the community must work to keep this balance intact.

In a world where AI’s potential is enormous, we cannot afford to allow open models to be exploited for the gain of just a few. The open-source ethos can still provide an equitable foundation, but it requires that every player—big or small—contributes meaningfully to the ecosystem.

As we watch the evolution of models like DeepSeek and Llama, we should remain vigilant about how these models are distributed and used. Only through true collaboration can open-source AI fulfill its promise as a tool for innovation, not just a stepping stone for the few.