I realized we kinda lack a thread that's about general tech developments in "real world" contexts. Maybe this can be this thread. Recent news articles:
https://tech.slashdot.org/story/16/08/18/1351200/ubers-first-self-driving-fleet-arrives-in-pittsburgh-this-monthRide-hailing app Uber will introduce self-driving cars in Pittsburgh as soon as this month, Bloomberg reports citing many officials and engineers at the company. The move is the first part of a pilot program to explore the future of the technology, the report added. The company plans to test 100 Volvo XC90s outfitted to drive themselves. Still, the cars will be accompanied by two humans: an engineer who can take control of the vehicle when needed and a co-pilot who takes note. Bloomberg reports:
The Volvo deal isn't exclusive; Uber plans to partner with other automakers as it races to recruit more engineers. In July the company reached an agreement to buy Otto, a 91-employee driverless truck startup that was founded earlier this year and includes engineers from a number of high-profile tech companies attempting to bring driverless cars to market, including Google, Apple, and Tesla. Uber declined to disclose the terms of the arrangement, but a person familiar with the deal says that if targets are met, it would be worth 1percent of Uber's most recent valuation.
So, self-driving Ubers are here. My guess is that this is really going to push self-driving cars into the general consciousness. Good news for self-driving cars, maybe not so good news for
Uber drivers. It also opens up the question of what's Ubers core market advantage when all taxi services are automated? I can easily see city-specific cab companies all signing up to create their own website / app together, especially since they compete with each other much less than they compete with Uber. But Uber might have other competitor too, because ...
Airbus Details Plan To Build Flying TaxisFlying taxis, nuff said. Airbus plans to expand by turning Earth into Coruscant.
https://science.slashdot.org/story/16/08/18/2310242/satellite-images-can-map-poverty"A team from Stanford University were able to train a computer system to identify impoverished areas from satellite and survey data in five African countries. The latest study looked at daylight images that capture features such as paved roads and metal roofs -- markers that can help distinguish different levels of economic wellbeing in developing countries. They then used a sophisticated computer model to categorize the various indicators in daytime satellite images of Nigeria, Tanzania, Uganda, Rwanda and Malawi. 'If you give a computer enough data it can figure out what to look for. We trained a computer model to find things in imagery that are predictive of poverty,' said Dr Burke. 'It finds things like roads, like urban areas, like farmland, it finds waterways -- those are things we recognize. It also finds things we don't recognize. It finds patterns in imagery that to you or I don't really look like anything... but it's something the computer has figured out is predictive of where poor people are.' The researchers used imagery from countries for which survey data were available to validate the computer model's findings.
Pretty cool if we can adapt existing systems like that to give us a better understanding of third-world development without needing to rely on subjective measurements, local authorities figures, or get investigators to interfere on the ground. Doing the same analysis on photos across a time lapse would help identify areas which are missing out on development aid, regardless of politics or national borders, warfare.