Takeover

"6 Models in 7 years, I can divide"

Sean Davis Jr
March 02, 2025

The global artificial intelligence race is heating up as the U.S. and China have taken major steps for supremacy. In late January, Chinese AI company, Deepseek, released their latest chatbot, R1, a notable competitor to OpenAI’s ChatGPT. Despite the rumors surrounding cost and efficiency, the ripple effects were felt throughout the industry. U.S. tech companies, Nvidia, Microsoft, and Micron amongst others saw significant stock declines as casual users found Deepseek’s model comparable to U.S. AI models. Deepseek’s release exposed the belief that developing and deploying quality models require high costs. While these stocks have recovered some losses, the proverbial cat is now out of the bag.

One of the reasons as to Deepseek’s popularity has been its open-source model. For the uninitiated, AI founders have long debated the cost-benefit analysis of a closed source versus open source model. In their early days, Sam Altman championed an open source model; however, upon the release of GPT-4, ChatGPT became completely closed source. From their foundation model in 2018 to their GPT-4 Turbo in 2023, ChatGPT has left their commitment to open source models for commercialization and a competitive advantage. Open source models have several competitive advantages such as faster innovation and democratization, cost-effectiveness, and public trust through transparency. On the other hand, closed-source models benefit from monetization, easier regulatory compliance, and enhanced security.

Why does this matter?

Many of the U.S. industry leaders in AI have maintained their closed source for profit approach, whereas Deepseek’s open source model has dismantled the myth that open source companies were behind technologically. The axis of power between the two countries seems to turn on which approach is superior. While both offer notable benefits, the U.S. should use a hybrid model adjusting for the varying gaps in innovation, collaboration, and national security.

If these factors were not enough, both the U.S. and China are ramping up investment in AI. Open AI has announced a four-year, $500 billion investment in their Stargate project - a multi-phased initiative that will build massive data centers across the country to give the U.S. the boost needed to beat China. Simultaneously, China’s investment agency, China International Capital Corporation, has declared the great firewall may make a $1.4 trillion investment in AI over the next six years.

What’s clear is that both countries are prioritizing AI across various industries. With seemingly different approaches, first place in the AI race will be determined through several factors, including: retaining talent and leadership, semiconductor manufacturing, AI model development and training, along with regulation.

But, what does all of this mean for me?

As both countries execute their AI strategies in the quest for supremacy, businesses and citizens alike should take a page from their books. Progress in AI will be developed through investment, education, and collaboration. And I should know, I asked ChatGPT, Deepseek, and Microsoft’s co-pilot “how to build your relationship with AI.” On an individual level, upskilling through prompt engineering and free courses is mandatory for advancement. Think of this in simple terms, evolution will require familiarity with AI. Similar to learning Google or Wikipedia, mastering engagement with AI applications is a process. For small businesses, AI integration is a given. More importantly, the focus must be analyzing how AI can improve systems and what systems require which tools. Optimizing processes with AI from contract drafting (PandaDoc) to scheduling (Calendly AI), are vital for every small business as competition in all industries thickens. Similar to the global AI race, progress will be contingent upon improving our relationship with advanced tools to optimize them or be unknowingly optimized by them.

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