Engadget: DeepMind and Oxford University researchers on how to ‘decolonize’ AI

Engadget: DeepMind and Oxford University researchers on how to ‘decolonize’ AI. “In a moment where society is collectively reckoning with just how deep the roots of racism reach, a new paper from researchers at DeepMind — the AI lab and sister company to Google — and the University of Oxford presents a vision to ‘decolonize’ artificial intelligence. The aim is to keep society’s ugly prejudices from being reproduced and amplified by today’s powerful machine learning systems.”

New York Times: The World of A.I.

New York Times: The World of A.I.. “Judging by the breathless coverage, it can seem as if the only countries developing A.I. are the United States and China. But while companies in those two countries are leading the way in cutting-edge research and products, it’s still early for the industry and other nations are working hard to become major A.I. players. Here are six that could challenge the two juggernauts.”

TechCrunch: DARPA wants to teach and test ‘common sense’ for AI

TechCrunch: DARPA wants to teach and test ‘common sense’ for AI . “It’s a funny thing, AI. It can identify objects in a fraction of a second, imitate the human voice and recommend new music, but most machine ‘intelligence’ lacks the most basic understanding of everyday objects and actions — in other words, common sense. DARPA is teaming up with the Seattle-based Allen Institute for Artificial Intelligence to see about changing that.”

New Scientist: Fatal AI mistakes could be prevented by having human teachers

New Scientist: Fatal AI mistakes could be prevented by having human teachers. “Artificial intelligence needs our help. The best AIs are quickly mastering skills from lip-reading to video games, but only by learning through repeated failure. As robots take on riskier domains, like healthcare and driving, this is no longer an acceptable approach. Fortunately, a new study suggests that with the right human oversight, it might be possible to ditch the failures.”

Using Machine Intelligence to Sort Geological Specimens

A little far afield, but that’s why I have this section: sorting geological specimens with machine intelligence. “Jller is part of an ongoing research project in the fields of industrial automation and historical geology. It is an apparatus, that sorts pebbles from a specific river by their geologic age. The stones were taken from the stream bed of the German river Jller, shortly before it merges with the Danube, close to the city of Ulm. The machine and its performance is the first manifestation of this research. A set of pebbles from the Jller are placed on the 2×4 meter platform of the machine, which automatically analyzes the stones in order to then sort them. The sorting process happens in two steps: Intermediate, pre-sorted patterns are formed first, to make space for the final, ordered alignment of stones, defined by type and age. Starting from an arbitrary set of stones, this process renders the inherent history of the river visible.”