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“Although $52 billion is a lot of money, every US-based hyper scaler is committing more than this to AI already,” said Hyoun Park, CEO and chief analyst at Amalgam Insights. “AWS is committing roughly $100 billion to new capital expenditures next year, most of which is servers for AI-related use cases. Microsoft plans to spend $80 billion which Satya Nadella has very publicly committed to. And Google has committed roughly $75 billion this year for AI and related infrastructure.”
That said, bigger investments don’t always translate to better results. The recent DeepSeek announcement demonstrated that AI innovation is not solely dependent on raw spending power but also on strategic advancements and optimization.
Escalating trade tensions
Alibaba already faces significant hurdles in the US, where regulatory restrictions and the administration’s firm stance on China have made it difficult for businesses to adopt its services.
However, said Park, “With the European Union actively discussing their need for more autonomy from the US, this may be an opportunity for Alibaba to gain some global market share as the US is perceived to be less aligned with EU interests.”
Despite this potential opening, Alibaba is likely to encounter major restrictions on accessing the latest generation of Nvidia chips, a crucial component for advancing AI capabilities.
“There are still various opportunities to simplify and improve AI models across mathematics, model distillation, programming, and hardware strategies,” Park added. “Although the relative lack of resources prevents Alibaba from adopting the same brute-force approach to AI research as US companies, it can still explore creative methods to develop and deploy AI that could lead to more innovative outcomes.”