including consumer purchases . By integrating different types of data , such as property information ( e . g . Edge Prop , ERA , PropNex ), government information ( e . g . OneMap Open datasets , Housing Development Board ( HDB ) housing policies , National Environmental Agency ( NEA ) weather information ), mobility ( e . g . SBS Transit , BlueSG , GetGo , AnyWheel ), retail ( e . g . Sheng Shiong , UOB TMRW ) and lifestyle ( e . g . National Library Board ( NLB ), Sentosa Development Corporation TMRW ) datasets , the prototype can be extended to support different types of user queries , for example it could assist in planning a day itinerary for property viewings based on specific user preferences and recommending suitable properties for families to reside near their parents .

“ We are pleased to be part of this challenge and grateful for the opportunity ,” said Dr Ashley Fernandez , Chief Data and AI Officer at Huawei International .

“ One of the underlying complexities in bridging geospatial use cases and GPT AI models goes back to data . Geospatial data by design comprises of various formats , along with its dynamic and everchanging representation of our world in time and space . It ’ s always exciting to reimagine the entire data and GPT stack through our extensive R & D

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