Deepseek is a Problem

2026-04-29 · Source: Matthew Berman · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Corporate Strategy & Leadership, Public Policy & Governance · Depth: Intermediate, long

Summary

The US open-source AI landscape faces an existential threat due to a broken business model, contrasting sharply with China's government-subsidized approach. While US closed-source labs like OpenAI and Anthropic pursue Artificial General Intelligence (AGI) with proprietary models, open-source alternatives like Llama, Quen, Gemma, and Deepseek offer security, efficiency, and cost benefits. However, US open-source developers struggle with monetization, as their R&D investments are undercut by others serving inference with higher margins. China's strategy of providing free, competitive models, often optimized for their own chips, poses a significant geopolitical risk, potentially influencing global AI standards and chip industries, and subtly impacting cultural discourse. Nvidia stands out as a potential "white knight" due to its hardware-funded model, investing $26 billion in open-source AI, where model development drives chip sales.

Key takeaway

For CTOs and VPs of Engineering evaluating AI strategies, relying solely on expensive, proprietary US models or cheap, competitive Chinese open-source alternatives presents a critical dilemma. You should actively seek out and support US-based open-source initiatives, particularly those with sustainable models like Nvidia's hardware-funded approach, or advocate for government incentives to foster a robust domestic open-source ecosystem. This mitigates geopolitical risks and ensures greater control over your AI infrastructure and data.

Key insights

The US open-source AI model is failing due to lack of monetization, risking Chinese dominance and geopolitical influence.

Principles

• Open-source AI enhances security and efficiency.
• Government subsidies can enable competitive open-source strategies.
• Hardware companies can fund open-source to drive chip sales.

Method

China's government subsidizes open-source AI development, enabling free distribution to kill margins for competitors and optimize models for domestic hardware, gaining market influence.

In practice

• Consider federal grants or compute quotas for US open-source AI.
• Treat open-source AI as national infrastructure with tax credits.
• Develop vertical application models for specific industries.

Topics

• Open-Source AI
• US AI Strategy
• China AI Policy
• AI Business Models
• Geopolitical AI Risks

Best for: Investor, CTO, VP of Engineering/Data, Director of AI/ML, AI Product Manager, Policy Maker

Related on AIssential

• ChinAI #359: DeepSeek's "Huawei-like" Mission in AI — DeepSeek's soaring valuation reflects its strategic role in China's drive for AI self-sufficiency amidst external tech restrictions.
• AI News: Everyone's Mad At Anthropic Now — Open-source AI models are rapidly closing the performance gap with proprietary models while offering significant cost and privacy advantages.
• US Considers Permits for Global Nvidia, AMD AI Chip Sales — Geopolitical control over AI technology and infrastructure is intensifying, impacting global trade, corporate strategy, and supply chain security.
• China’s DeepSeek previews new AI model a year after jolting US rivals — DeepSeek's V4 model aims to challenge top US AI systems, emphasizing coding prowess and domestic chip compatibility.
• What’s next for Chinese open-source AI — Chinese open-source AI models offer near-frontier capabilities at a fraction of the cost, rapidly reshaping global AI innovation.
• Can open-source beat OpenAI? — Open-source AI models foster global collaboration and efficiency, challenging closed-source dominance through accessible innovation and diverse monetization.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Matthew Berman.