The current rise of Machine Learning, notably Deep Learning, follows from relaxing the assumptions of what intelligence is. It’s no longer a static metaphysical entity, likely isn’t accessible given our naive abstractions of knowledge, and a human almost certainly can’t explain all the rules that define it. To practice AI today is to have evolved away from Reductionism and view the world void of structure, intimately self aware of complexity underlying all domains, and unburdened with the expectation of finding grok-able ground truth. Look at data, model data, rinse, repeat, and nothing else
Uber could be the next MySpace, some say, a company that created a market but was foiled by its own missteps and overtaken by savvier competition. Or the recent PR disasters could be more than just flesh wounds, and instead reveal an aggressiveness that has both created and masked a deeply flawed business model. Either way, a report in April said private Uber shares were trading at a discount.
A neural computing system designed to translate content from one human language into another developed its own internal language to make the task more efficient. Without being told to do so. In a matter of weeks.