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Machine-Learning Wizards Vie for Zillow's $1 Million Prize

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In 1714, the British Parliament passed the Longitude Act, which offered serious money to anyone who could devise a practical method to measure longitude at sea. While the determination of longitude might seem a trivial thing in today's world of smartphones and GPS satellites, at the time it was an immense technical challenge. It took many years, but the strategy worked, leading to the development of the marine chronometer, a handheld mechanical marvel that undoubtedly saved the lives of countless sailors. Prizes have, of course, since been used to spur innovation in many other spheres. "These were typically offered by governments," says Josh Lerner of the Harvard Business School, who has studied the effectiveness of such prizes.


Zillow awards $1 million to data scientists for improving its Zestimate algorithm

ZDNet

Online real estate database Zillow this week announced the winners of Zillow Prize, the company's $1 million competition to improve the accuracy of the Zestimate home estimator. Introduced in 2006, the Zestimate is an algorithm that today estimates the market value of roughly 110 million homes in the US. While Zillow has improved the accuracy of the Zestimate algorithm considerably since its inception, average home estimates are still about $10,000 off of the actual sale price for a typical home. The goal with the AI competition -- which was hosted on Google's Kaggle platform -- was to find new machine learning techniques and statistical models that would help reduce the Zestimate's current 4.5 percent margin of error. According to Zillow, the winning team -- Team ChaNJestimate -- created an algorithm that's 13 percent more accurate than Zillow's current model.


Zillow utilizes explainer AI, data to revolutionize how people sell houses

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Join executive leaders at the Conversational AI & Intelligent AI Assistants Summit, presented by Five9. Zillow has been a big name for online home seekers. There have been more than 135 million homes listed on the platform, and the company has streamlined the real estate transaction process from home loans, title, and buying. It says AI has been at the heart of success in providing customized search functions, product offerings, and accurate home valuations -- with a claimed median error rate of less than 2%. Zillow's initial forays into AI in 2005 centered around blackbox models for prediction and accuracy, Stan Humphries, chief analytics officer at Zillow, said at VentureBeat's virtual Transform 2021 conference on Tuesday.


Hot property: How Zillow became the real estate data hub

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Today the Zillow Group is a public company with 645 million in revenue that also operates websites for mortgage and real estate professionals -- and completed the acquisition of its nearest competitor, Trulia, last year. From the start, Zillow offered the "Zestimate," its value-forecasting feature for homes in locations across the United States. Currently, Zillow claims to have Zestimates for more than 100 million homes, with 100-plus attributes tracked for each property. The technology powering Zestimates and other features has advanced steadily over the years, with open source and cloud computing playing increasingly important roles. Last week I interviewed Stan Humphries, chief analytics officer at Zillow, along with Jasjeet Thind, senior director of data science and engineering.


Real-Estate Agents Look to AI for Sales Boost

WSJ.com: WSJD - Technology

"AI can play a significant role in simplifying and automating processes where traditionally humans have been involved," said Rizwan Akhtar, chief technology officer of business technology at Realogy Holdings Corp., which owns brokerage brands including Coldwell Banker, Corcoran and Sotheby's International Realty. The Morning Download delivers daily insights and news on business technology from the CIO Journal team. Artificial-intelligence efforts in the real-estate sector are benefiting from advances in cloud computing and data analytics, as well as improvements to algorithms, according to technology leaders at Realogy, Compass Inc. and Zillow Group Inc. Realogy uses more than 25 AI models, Mr. Akhtar said, including models that can help agents predict their chances of converting a prospective client into a paying client and others that can predict the optimal percentage split between a broker and an agent on a property. The company is in the early stages of testing an AI app that aims to predict when certain milestones will be reached in the home-buying process, he said. At real-estate brokerage Compass, an AI-based tool that predicts whether people in an agent's contact database are likely to sell their homes within a year resulted in more "listing wins" for its agents, said Joseph Sirosh, the company's chief technology officer.