Ant Group, the Alibaba (BABA) affiliate that runs mobile payments app Alipay, has turned to a combination of U.S. and Chinese semiconductors to more training artificial intelligence models more efficient, according to a report citing sources close to the firm.
The approach, first reported by Bloomberg on Monday, slashes the cost and time it takes to train AI models, while also limiting reliance on a single supplier such as Nvidia (NVDA). Apparently, Ant has used a mixture of chips from Alibaba, Huawei, Nvidia and Advanced Micro Devices (AMD).
The approach of using multiple networks, known as mixture of experts (MoE), can greatly reduce computation costs during pre-training and achieve faster performance during inference time, according to IBM (IBM). This efficiency is achieved through selectively activating only the specific experts needed for a given task, rather than activating the entire neural network for every task.
In a paper published earlier this month Ant said was able to reduce computing costs by 20% when training its own MoE models. This paper expressly detailed that it was able to scale the MoE model “without premium GPUs,” referring to Nvidia’s top-of-the-range chips.
The news comes as Chinese firms are making bold advances in AI and increasingly seek to wean themselves off U.S. chips. The White House has sought to restrict Chinese firms’ access to the latest AI chips, however the indication is that this is sparking innovation to skirt the restrictions and driving China to its ultimate goal of becoming self-sufficient in AI.
Major Upgrades Announced
Also on Monday Ant announced “major upgrades” to its AI solutions for healthcare, with a rollout across seven major hospitals and healthcare institutions in Beijing, Shanghai, Hangzhou and Ningbo. The solution is built on advanced foundation models, including DeepSeek R1/V3, Alibaba’s Qwen and Ant’s self-developed BaiLing.
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On Wall Street, BABA has a Strong Buy consensus rating, based on 16 Buys assigned in the last three months. The average BABA price target of $165.61 implies about 22% upside.
