Monday, April 01, 2019

Doppelgänger: What happens after rich kids bribe their way into college? I teach them

1 April Challenge to the world Google ‘MEdia Dragon’ Plus Your Birthday:
"Media Dragon July 7"

To Celebrate April Fool’s Day: A List Of Famous Literary Hoaxes


So what makes a good literary hoax? Well the world needs to be sucked into believing it of course. And that means of course that you don’t know the fraud until the deception has been revealed. Tragedy (usually for the hoaxer) ensues. Is there a common thread through these examples? – The New York Times


Doppleganger: mighty super volcano lies beneath Sydney




doppelganger from globalnews.ca
 "I saw someone who looked just like you!" You've probably heard that at least once in your lifetime. But are people who look exactly like us ...



A firm given the $14 million job of upgrading critical security at Parliament House in Canberra is in disarray with allegations of cocaine use, a sideline in an Uber-style app for escorts, debts to Russian friends and the intervention of a Morrison government minister.
Almost a year after the $75 million state-of-the art upgrade to protect MPs from acts of terrorism was due to be completed, the marble entrances of Parliament remain shrouded in scaffolding and 400 businesses across Australia are owed $21 million.

Cocaineescorts and unpaid workers: Parliament's security ...







What happens after rich kids bribe their way into college? I teach them Guardian



Human Contact Is Now a Luxury Good NYT

AOC Has Some Advice For Parents Jacobin

New York City’s Bail Success Story Marshall Project

Facial recognition can speed you through airport security, but there’s a cost CNET

Learning to Navigate in Cities Without a Map Google DeepMind: “Navigating through unstructured environments is a basic capability of intelligent creatures, and thus is of fundamental interest in the study and development of artificial intelligence. Long-range navigation is a complex cognitive task that relies on developing an internal representation of space, grounded by recognisable landmarks and robust visual processing, that can simultaneously support continuous self-localisation (“I am here”) and a representation of the goal (“I am going there”). Building upon recent research that applies deep reinforcement learning to maze navigation problems, we present an end-to-end deep reinforcement learning approach that can be applied on a city scale. Recognising that successful navigation relies on integration of general policies with locale-specific knowledge, we propose a dual pathway architecture that allows locale-specific features to be encapsulated, while still enabling transfer to multiple cities.

‘We Fear Drought More Than War,’ Say Border Villagers in Gujarat The Wire


Going Cashless Looks More and More Like a Capitalist Scam Vice


I made $3.75 an hour’: Lyft and Uber drivers push to unionize for better pay Guardian


World Happiness Report: Americans are unhappiest in years Vox