Uber launches self-driving cars in a trial in Pittsburgh this week. I was in an Uber returning from the airport when this was reported on the BBC by EV subscriber, Rory Cellan Jones. My Uber driver heard the headline and leant forward to increase the volume, ears pricking up. This is the sharp end of automation. Even if you hold the reasonable belief that work isn't going to go anywhere soon, and that we'll continuously reinvent things for humans to do, the question is not about the statistics in aggregate.

Alan Turing, the British mathematician, is widely recognized as being one of the first people to come up with the idea of artificial intelligence in 1950. However the idea of a thinking machine existed as early as 2500 B.C., when the Egyptians sought mystical advice from talking statues. In the Cairo Museum, there is a bust of, Re-Harmakis, an Egyptian God, whose neck reveals the secret of his genius: an opening at the nape just big enough to hold a priest. Automata, the predecessors of today's robots, date back to ancient Egyptian figurines with movable limbs like those found in Tutankhamen's tomb. It took the invention of the Analytical Engine by Charles Babbage in 1833 to make artificial intelligence a real possibility.

Around the world, there are people who need help. But sometimes, populations of poverty-stricken people are difficult to find. That is why researches at Stanford have put together a program to find people who need help, from space. One of the many difficulties in dealing with poverty is simply not knowing where to send aid. In many poor countries, data on which areas need the most help are hard to get.

Pop culture's many takes on artificial intelligence

Pop culture's many takes on artificial intelligence New technique using artificial intelligence to read satellite images could aid efforts to eradicate ...

Poverty could be predicted by reading the satellite images using artificial intelligence. By indicating the areas where the most help is needed, these images could help eradicate global poverty. One can make an idea of a country's wealth by examining how much it shines at night. A comparison between China and South Korea's intense brightness and North Korea's dark mass could be one of the best examples found by the scientists. This kind of information could only be obtained by sending legions of survey-takers in populated rural areas.

London (ANTARA News) - A new technique using artificial intelligence to read satellite images could aid efforts to eradicate global poverty by indicating where help is needed most, a team of U.S. researchers said. The method would assist governments and charities trying to fight poverty but lacking precise and reliable information on where poor people are living and what they need, the researchers based at Stanford University in California said. Eradicating extreme poverty, measured as people living on less than 1.25 U.S. a day, by 2030 is among the sustainable development goals adopted by United Nations member states last year. A team of computer scientists and satellite experts created a self-updating world map to locate poverty, said Marshall Burke, assistant professor in Stanfords Department of Earth System Science. It uses a computer algorithm that recognizes signs of poverty through a process called machine learning, a type of artificial intelligence, he said.

New technique using artificial intelligence to read satellite images could aid efforts to eradicate ...

LONDON: A new technique using artificial intelligence to read satellite images could aid efforts to eradicate global poverty by indicating where help is needed most, a team of US researchers said on Thursday. The method would assist governments and charities trying to fight poverty but lacking precise and reliable information on where poor people are living and what they need, the researchers based at Stanford University in California said. Eradicating extreme poverty, measured as people living on less than 1.25 US a day, by 2030 is among the sustainable development goals adopted by United Nations member states last year. A team of computer scientists and satellite experts created a self-updating world map to locate poverty, said Marshall Burke, assistant professor in Stanford's Department of Earth System Science. It uses a computer algorithm that recognizes signs of poverty through a process called machine learning, a type of artificial intelligence, he said.

A team of researchers from Stanford University has developed a new algorithm model, which is considered to be better at predicting poverty than all existing methods. The model is more effective than both satellite imagery and household data independently. To eliminate poverty, it is vital to find out the regions that are most affected with it. But the current situation is such that on-the-ground economic measures are sparse. These measures might not be reliable in poorer nations, as they lack resources to collect accurate data. In this situation, satellite data has been considered to be the best solution for the problem.