DeepSeek strengthens open-source AI as serious alternative

The release of DeepSeek has solidified open-source AI as a serious contender to centralised AI, according to Dr. Ala Shaabana, co-founder of the OpenTensor Foundation.

DeepSeek, an open-source AI model, was developed at a fraction of the cost of leading models and challenges the traditional approach of centralised AI, which often costs billions to create and train.

“It proves that things like efficiency, collective intelligence, and innovation can actually rival sheer financial power,” stated Dr. Shaabana, highlighting the performance of DeepSeek.

He attributed the rapid growth of open-source AI to a shift in academic practices, where researchers are now required to include their code with published papers for transparency.

This open collaboration is helping to narrow the gap between centralised and open-source systems.

Dr. Shaabana also noted that increased regulations on centralised AI, including potential geographic data restrictions due to geopolitical tensions, may further burden these systems, making them less efficient.

These regulatory pressures could widen the gap between centralised and open-source AI, with the latter benefiting from fewer constraints.

The launch of DeepSeek has caused significant disruption in the AI landscape, leading to unexpected consequences, including a stock market crash and swift responses from US lawmakers.

Reports indicate that the US government, under the Trump administration, is considering tighter export controls on Nvidia AI chips to China due to the impact of DeepSeek.

US Senator Josh Hawley introduced a bill on January 29 to prohibit the import and export of AI products to and from China.

The bill specifically names DeepSeek, with Senator Hawley asserting that every dollar and gigabyte of data entering Chinese AI projects could ultimately be used against the United States.