Mind Matters News and Analysis on Natural and Artificial Intelligence

CategoryMachine Learning

Bitcoin gold coin. Cryptocurrency concept.

A wallet you can’t feel?

Will Bitcoin change the rituals around money?
It’s tempting to assume that cryptocurrencies like Bitcoin will succeed because social media did. But digital doesn’t mean magic. Cryptocurrencies will work if the needs met are more significant to most people than the problems created are. Read More ›
Collection CT scan of brain and multiple disease

Better medicine through machine learning?

Data can be a dump or a gold mine
The biggest problem today isn’t the sheer mass of data so much as the difficulty of determining what it is worth. The answer lies, unfortunately, in the undone studies and the unreported events. Machine learning will be a much greater help when those problems are addressed. Read More ›
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AI Is Not (Yet) an Intelligent Cause

So-called “white hat” hackers who test the security of AI have found it surprisingly easy to fool.
Hutson describes one test last year where a computer scientist at UC Berkeley subtly altered a stop sign with stickers. It fooled an autonomous vehicle’s image recognition system into “thinking” it was a 45 mph speed limit sign. Humans could immediately recognize the stop sign, but the car did not. Autonomous car makers wonder, could hackers turn them into terror weapons? Read More ›
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The driverless car: A bubble soon to burst?

Author says journalists too gullible about high tech
Why do we constantly hear that driverless, autonomous vehicles will soon be sharing the road with us? Wolmar blames “gullible journalists who fail to look beyond the extravagant claims of the press releases pouring out of tech companies and auto manufacturers, hailing the imminence of major developments that never seem to materialise.” Read More ›
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GIGO alert: AI can be racist and sexist, researchers complain

Can the bias problem be addressed? Yes, but usually after someone gets upset about a specific instance.

From James Zou and Londa Ziebinger at Nature: When Google Translate converts news articles written in Spanish into English, phrases referring to women often become ‘he said’ or ‘he wrote’. Software designed to warn people using Nikon cameras when the person they are photographing seems to be blinking tends to interpret Asians as always blinking. Word embedding, a popular algorithm used to process and analyse large amounts of natural-language data, characterizes European American names as pleasant and African American ones as unpleasant. Now where, we wonder, would a mathematical formula have learned that? Maybe it was listening to the wrong instructions back when it was just a tiny bit? Seriously, machine learning, we are told, depends on  absorbing datasets of Read More ›