Alibaba set up AI research facility with Singapore university

Alibaba Group and Nanyang Technological University (NTU) of Singapore signed a five-year agreement to establish a new research institute to develop artificial intelligence applications (AI).

Alibaba Group and Nanyang Technological University (NTU) of Singapore signed a five-year agreement to establish a new research institute to develop artificial intelligence applications (AI).

This facility will use NTU's AI technology, focusing on areas such as health, aging, homes, and communities, and integrating them with Alibaba technologies including natural language processing (NLP), machine learning and cloud computing.

Alibaba set up AI research facility with Singapore university Picture 1Alibaba set up AI research facility with Singapore university Picture 1

The research institute will start working with a group of 50 researchers from both cooperative organizations, and marks the first time Alibaba has established a research facility with a partner outside China.

According to Alibaba, the cooperation will last for the first 5 years and will cost millions of dollars each year. The two partners will seek to apply AI to improve efficiency in the housing, retail, community, urban and hospital sectors.

NTU President Subra Suresh said: " Using AI technologies, we can address basic social challenges such as aging, which is a big problem for cities with aging populations. Like Singapore, for example, AI virtual assistants can be deployed to improve productivity and smart sensors can be used to see the health of the elderly, with data stored on the crowd. clouds for continuous monitoring '.

Students and staff of the university as well as Alibaba staff will have the opportunity to exchange research programs with other institutions.

Last month, Alibaba introduced its smart AI city platform in Kuala Lumpur, Malaysia, marking the first deployment of this Chinese supplier outside the domestic market. This platform is touted to be able to analyze large volumes of data extracted from various sources in the urban environment via video, image and voice recognition. The system then uses machine learning technology to provide detailed information for city managers to improve operational efficiency and monitor security risks.

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