Forecasting the Consumer Price Index (CPI) is an important yet challenging task in economics, where most existing approaches rely on low-frequency, survey-based data. With the recent advances of large language models (LLMs), there is growing potential to leverage high-frequency online text data for improved CPI prediction, an area still largely unexplored. This paper proposes LLM-CPI, an LLM-based approach for CPI prediction inference incorporating online text time series. We collect a large set of high-frequency online texts from a popularly used Chinese social network site and employ LLMs such as ChatGPT and the trained BERT models to construct continuous inflation labels for posts that are related to inflation. Online text embeddings are extracted via LDA and BERT. We develop a joint time series framework that combines monthly CPI data with LLM-generated daily CPI surrogates. The monthly model employs an ARX structure combining observed CPI data with text embeddings and macroeconomic variables, while the daily model uses a VARX structure built on LLM-generated CPI surrogates and text embeddings. We establish the asymptotic properties of the method and provide two forms of constructed prediction intervals. The finite-sample performance and practical advantages of LLM-CPI are demonstrated through both simulation and real data examples.

An always effective and satisfying way to procrastinate is to browse the housing market. I find it satisfying to stare at the property on the web and marvel at the gigantic mansions I can't afford and the tiny flats I also can't afford because, somehow, even the smallest flats cost a small fortune. Despite this, most of us undertake the strenuous journey to work for over half our life in order to own one. When making such an important choice, you are probably on the lookout for good deals. Wouldn't it be convenient if you had some sort of algorithm point you towards the biggest bargains in the market?

The U.S. property market has proven to be more resilient than you might have assumed it would be in the midst of a coronavirus pandemic, and today a startup that's built a computer vision tool to help owners assess and fix those properties more easily is announcing a significant round of funding as it sees a surge of growth in usage. Hover -- which has built a platform that uses eight basic smartphone photos to patch together a 3D image of your home that can then be used by contractors, insurance companies and others to assess a repair, price out the job and then order the parts to do the work -- has raised $60 million in new funding. The Series D values the company at $490 million post-money, and significantly, it included a number of strategic investors. Three of the biggest insurance companies in the U.S. -- Travelers, State Farm Ventures and Nationwide -- led the round, with building materials giant Standard Industries, and other unnamed building tech firms, also participating. Past financial backers Menlo Ventures, GV (formerly Google Ventures) and Alsop Louie Partners, as well as new backer Guidewire Software, were also in this round.

In the 21st century, technology has impacted the way we do things. From Artificial intelligence, digital open housing, and cryptocurrencies, these emerging trends of technology have transformed the way we know the real estate sector. The new tech has taken the industry by storm, accelerating the growth and the way we do business. Every aspect of the real estate industry has been impacted by technology. The emergence of Generation Y and millennials making up a huge percentage of homebuyers; players in the industry have been able to scale up their operations to keep up with the emerging demands.

Though Artificial Intelligence (AI) is a hot topic for businesses right now, it has so far failed to shake up the real estate industry and the use of property software in the same way it has transformed sectors such as banking and healthcare. Tom Shrive explains how the sector is ripe for AI disruption, and why this burgeoning tech will not jeopardise jobs. AI is an inescapable buzzword at the moment and has become an essential part of the technology industry. However, the emergence of Artificial Intelligence (AI) has not come without controversy, provoking polarized responses from the general public. By definition, artificial intelligence is technology that can perform human-like tasks.

THIS is part of my ongoing series on technology and real estate. The focus is on artificial intelligence (AI), which has been casting a dark shadow on the Philippine business-process outsourcing (BPO) industry. According to the Oxford dictionary, AI is "the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and translation between languages." Artificial intelligence has great potential to disrupt existing industries and traditional work practices across the world. And the Philippines is no exception.

Kevin Du is travelling to the United States this week to visit Harvard Business School. But he has other things on his mind. He plans to make a side trip to other top universities and technology companies, part of his regular day job as a headhunter, looking to rope in engineers, programmers and coders to work in China. China, already the world's largest market for automatons, e-commerce and smartphones, is also the job market for artificial intelligence, big data analytics and robotics. The Chinese government has just unveiled a road map to global dominance in AI by 2030, forecasting the industry to be worth 1 trillion yuan (US$151 billion) by then.