If GPT-4V can accurately digitize North Carolina, underwent urban renewal, a national hand-written documents through carefully crafted program aimed at modernizing "blighted" areas prompts, it could become a valuable tool for nonexperts (Lee et al. 2017). This process, mostly impacting in transcribing historical documents on a African-American neighborhoods, displaced families, large scale. Alternatively, if it falls short, it is still businesses, and organizations for economic crucial to understand and discuss the implications and infrastructure development.

This study aims to innovatively explore adaptive applications of large language models (LLM) in urban renewal. It also aims to improve its performance and text generation quality for knowledge question-answering (QA) tasks. Based on the ChatGLM, we automatically generate QA datasets using urban renewal scientific literature corpora in a self-instruct manner and then conduct joint fine-tuning training on the model using the Prefix and LoRA fine-tuning methods to create an LLM for urban renewal. By guiding the LLM to automatically generate QA data based on prompt words and given text, it is possible to quickly obtain datasets in the urban renewal field and provide data support for the fine-tuning training of LLMs. The experimental results show that the joint fine-tuning training method proposed in this study can significantly improve the performance of LLM on the QA tasks. Compared with LoRA fine-tuning, the method improves the Bleu and Rouge metrics on the test by about 5%; compared with the model before fine-tuning, the method improves the Bleu and Rouge metrics by about 15%-20%. This study demonstrates the effectiveness and superiority of the joint fine-tuning method using Prefix and LoRA for ChatGLM in the urban renewal knowledge QA tasks. It provides a new approach for fine-tuning LLMs on urban renewal-related tasks.

Alphabet's Sidewalk Labs will develop a futuristic, billion-dollar community along a sizable swathe of Toronto's waterfront. On Wednesday, the City of Toronto and Sidewalk Labs -- which is the urban innovation arm of Google's parent company Alphabet -- announced a partnership to radically re-imagine 800 acres of the city's largely vacant, post-industrial Eastern Waterfront, and turn it into a tech-integrated neighborhood called Quayside. SEE ALSO: Balloons may be Puerto Rico's best chance for communication Sidewalk Labs released a 196-page document brimming with the company's extensive ideas, including high-speed ferries, parks that can be adapted to the seasons, and robotic waste removal vehicles. Sidewalk Lab's plan to fuse smart urban planning with technology is still just a visionary document, but if realized, would likely benefit both the company and Toronto. Sidewalk Labs doesn't get any ownership of the neighborhood, but gets a massive slab of land to deploy its innovative urban experiment.