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SENSETIME-W: HK AI Industry Faces Electricity & Talent Shortages; May Expand Multilingual LLMs to Southeast Asia
SENSETIME-W (00020.HK) released the Cantonese version of its SenseNova 5.0 foundation model. Lewis Fung, General Manager of Hong Kong Business, said that the company is taking the opportunity to launch a model for Hong Kong people and enterprises as it was the 10th anniversary of the company's founding in Hong Kong.

He pointed out that there is still no conclusion on whether the future development of large language models (LLMs) will trend towards clusters of models for each small languages, or a universal model that integrates support for all languages. The cost of training for one small language is relatively high. SENSETIME currently intends to develop business in Southeast Asian countries such as Singapore, Thailand, and Malaysia, which are multilingual, but the specifics still depend on the demand.

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Asked about the regulation and risks of the artificial intelligence (AI) industry, Fung did not feel restricted in terms of computing power and chips. Considering that there should be plenty of room for the market to develop and the demand is much higher than the supply, the top priority of the company is to increase its computing power. Through the computing power synergy, the company currently plans for a nationwide computing power of 12,000 Petaflops.

In addition to the computing power network and supercomputing centres with partners such as the Science Park Corporation and Cyberport, SENSETIME may also be possible to increase its computing power through the construction of an artificial intelligence computing centre in Hong Kong, but will need to solve the problems of power, talent shortage, and the land required.

At the release event, SENSETIM signed memorandums of understanding (MoU) with Deloitte China, HKT-SS (06823.HK) and Geely IDC, a subsidiary of Geely Technology Group. Fung said he is currently in contact with enterprise customers and government departments from various vertical industries such as finance, healthcare and construction, and that many of them favour private cloud due to regulatory requirements and data security considerations.

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