In light of rising AI infrastructure costs, Meta is seeking external partnerships and plans to sell $2 billion worth of data center assets to co-develop AI facilities.

Meanwhile, Chinese firms are leveraging open-source AI not only for market influence but also for geopolitical advantages, positioning themselves as benefactors to developing nations amid U.S. technological dominance.

Mark Zuckerberg announced that the company will be more selective about releasing AI projects as open-source, emphasizing the importance of safety and risk mitigation.

Industry experts suggest that this pullback reflects competitive pressures rather than solely safety concerns, indicating a weakening position for Meta in the AI landscape.

Meta Platforms is scaling back its open-source AI initiatives due to rapid advancements by Chinese firms in the artificial intelligence sector.

This marks a significant shift for Meta, which was previously a leader in democratizing AI access, as it now cites safety and misuse concerns regarding its Llama family of language models.

The global AI race is intensifying, with OpenAI preparing to release GPT-5, while eight of the top ten open-source models are now from Chinese companies like Alibaba and Zhipu AI.

Meta's AI offerings are reportedly falling behind in both capability and user adoption, as demonstrated by the rapid growth of Chinese models like DeepSeek's R1, which recently tripled its user base.

This strategic retreat marks a notable change from Zuckerberg's earlier advocacy for open-source AI as a key development path.

Notable AI researcher Andrew Ng highlighted the competitive nature of China's open-source ecosystem, noting that while top proprietary models are still from the U.S., most leading open models now originate from China.

Experts argue that Meta's recent policy shift may lack impact, as its open-source models are no longer at the cutting edge compared to competitors.

Additionally, Meta's capital expenditure for AI development has been significantly revised upward, highlighting the financial challenges even large tech companies face in funding AI advancements.