HOUSINGNEWS REPORT
FEATURED ARTICLE
Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type — quietly but meaningfully improving core operations.”
Jeff Bezos CEO, Amazon
explains The Economist. “Technology giants have always benefited from network effects: the more users Facebook signs up, the more attractive signing up becomes for others. With data there are extra network effects. By collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on.” • The coming data-based economy is transformative – and disruptive. A few years ago you might have hailed a cab, rented a hotel room, or paid for cable TV. Today you are likely to use Uber and Lyft to get around town, find rooms through Airbnb, and subscribe to Amazon Prime, Google’s Chromecast, Hulu and Netflix rather than a traditional cable service.
tiny bits of information known generally as data or data points. These bits have little value individually but pulled together, arranged and re-arranged, they can produce dramatic marketplace advantages. “Much of what we do with machine learning happens beneath the surface,” said Amazon CEO Jeff Bezos, in his 2016 shareholder letter. “Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type — quietly but meaningfully improving core operations.”
• Data equals power, more data equals more power, and more power equals more profits. • Traditional metrics relating financial value to physical size, revenues, and even profits may not apply in the data economy. Tesla lost money last year and produced fewer than 85,000 cars. General Motors churned out 9.8 million vehicles worldwide and had a 2016 profit of $9.43 billion. As of May 31, Tesla — which is widely perceived as a data and technology company — had a market cap of $53.64 billion versus $50.01 billion for GM, an auto producer with roots dating back more than a century. • The use of data creates a network effect. “This abundance of data changes the nature of competition,”
The basic rules for the new data economy look like this:
JUNE 2017
ATTOM DATA SOLUTIONS • P3
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