[AndrewOMartin]

My point is that extrapolating error rate reduction only applies to this tightly defined task.

You can only make claims about machines being better at "general" pattern recognition when we make progress on the issue that's stopped all Cognitivist General AI projects dead, which is that of situational awareness.

Arithmetic operations, spam detection and the task described in the article have a much smaller, and static, problem space than most human activities. You can demonstrably already knock up an automated-barrier style security guard. However, I'd argue that there does not exist an algorithm or appropriately weighted n-layer network that can handle all the ambiguity, countermeasures and ill-defined or contradictory situations that human security guards, or even just their object recognition capabilities, handle largely instinctively.

[blauwbilgorgel]

Do you think that computers are better at chess than humans? If yes, how does this relate to pattern recognition. If not, what makes someone or something better at chess, while still losing against a computer? Is that a beautiful move? Tactics? Irrational sacrifices to cause confusion?

Do you think that a machine's situational awareness can not achieve or surpass the level of a human? If not, what is holding the machines back?

Why do you think that instinct works better to create more rational, consistent and correct predictions? Are 100 security guards better than a single security guard at dealing with ambiguities? Do you think an algorithm to detect fights, drug dealers, and pickpockets from street cams can not exist? What if a NN could detect these cases faster and flag this to a human security guard for action/no-action.