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Collaboration, Open Source, and the Path to a Prosperous AI-Driven Future
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Collaboration, Open Source, and the Path to a Prosperous AI-Driven Future

Moving past adversarial mindset for a global AI collaboration.

Dear Zaiku Community,

As you know, the rapid evolution of artificial intelligence (AI) has sparked intense debate about global competition, particularly between nations such as the United States and China. Headlines and public discourse often frame AI advancement as a zero-sum game: if one country makes significant progress, another must be falling behind. This perspective, however, misses the bigger picture. The real untold story in AI today is not about national rivalries but the transformative power of collaboration, open research, and open-source models. It is these elements, not adversarial competition, that will most likely shape a safer and more prosperous AI-driven future for humanity.

  • The Case of DeepSeek: Consider the recent achievements of DeepSeek, that has brought a global attention to their project. Some observers have interpreted DeepSeek’s success as evidence of one nation "surpassing" another in AI development. But this interpretation misses the point. The real insight as Meta's Yann LeCun put it here, is that open-source models are surpassing proprietary ones. DeepSeek stands as a testament to the strength of open research and collaboration. Its creators leveraged existing open-source technologies such as PyTorch and Llama (nearly open source), which were developed by organisations such as Meta. They built upon the collective knowledge of the global AI community, adding their own innovations and then making their advancements open to all. This approach, building on the work of others and sharing outcomes openly, creates a virtuous cycle of innovation. Because DeepSeek’s work is open-source for auditing, the broader community can now use and improve upon it, pushing the boundaries of AI even further.

Of course, there are some critics pointing out that their model does not include facts about politically sensitive issues such as Tiananmen Square. However, this does not diminish the significance or utility of their achievement. On the contrary, it provides an opportunity for other researchers outside China to make further refinement and inclusivity in future iterations, which could only enhance its value and impact.

  • Moving Beyond Adversarial Thinking: Despite the clear benefits that AI can bring to humanity, much of the public narrative around it remains focused on competition, particularly between nations e.g. US versus China. This adversarial mindset is in our opinion counterproductive. Framing AI as a race to dominance not only fuels fear and mistrust but also discourages the very collaboration that could drives meaningful progress towards the holy grail, Artificial General Intelligence (AGI). If nations and organisations view one another as threats rather than partners, they are less likely to share knowledge, align on ethical standards, or work together to address shared challenges such as bias, misinformation, and security.

The truth is that AI is not a zero-sum game. Advancements in AI by one group or nation often benefit the entire global community, especially when those advancements are shared openly. For example, DeepSeek’s success is not a victory for China; it is a victory for the collaborative spirit of the AI community. By shifting the narrative from competition to collaboration, we can unlock the full potential of AI to address humanity’s most pressing challenges, from climate change to healthcare and global security.

  • Collaborative AI Research Microgrants: At Zaiku Group, we firmly believe that the fusion of mathematical innovation and computational creativity holds the potential to redefine the standards of AI reasoning, making it not only more robust but also more cost-effective and resource-efficient. It is one of our core motivations for establishing the QF Academy: to empower AI researchers with the mathematical tools and knowledge they need to develop next-generation models.

We hope you enjoy the episode and look forward to seeing you next time!

**Important note: The AI-generated voice podcast may contain some historical and technical inaccuracies. However, for the most part, it is accurate and highly engaging.

Many thanks,

Zaiku team

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