Google's AI baffles engineers, teller machines and tenants screening

Engineers working on Google's RankBrain AI unable to understand it

artificial-intelligence,ai,technology,information-technology,science,engineering,search-engine,google,singapore,bank,home,house,rent,tenant,landlord,building
Google engineers unable to understand the working of Google's Search AI?
Apparently even the engineers working on Google's RankBrain AI are unable to understand it. Paul Haahr, one of the company's top engineers working on the Google Search team said that Google's new RankBrain AI engine is actually more complex than thought before, and even some of Google's own staff is clueless how it is exactly working: "Google understands how RankBrain works but not really what it is doing." Google started working on RankBrain, an artificial intelligence system, during the past years. In October 2015, Google said that RankBrain had in fact gone live months before, only they had not informed anybody about it. Google explained that RankBrain is the company's third most important indicator, among hundreds of others, when it comes to ranking the search results that appear on your screen.
Video-conference-based teller machines in Singapore
Singapore's national bank just started rolling out the country's first-ever video-conference-based teller machines, so you can chat with a teller live. The virtual teller machines will perform regular ATM services such as cash withdrawals and balance enquiries, and they'll also be able to dispense debit cards. The machines will also be able to scan fingerprints to authenticate users. Singapore's national bank plans to install more of the video machines around the island by the end of the year.
Startup lets landlords screen tenants
You own a nice building. How do you find out the tenants you bring in are not a bunch of deadbeats? Naborly has some ideas. The startup allows landlords to create custom tenant applications that collect pertinent information from tenants. The service then creates a comprehensive dossier on the tenant, informing the landlord whether or not the tenant is a risk. "Our system instantly analyzes over 500 data points on each tenant including social media, credit, rental histories, Google, etc," a founder said. "We are now accurately able to predict stuff like late rent payments based on macroeconomic events, interpersonal conflicts between roommates based on financials, job type, etc."