Google’s engineers say that “magic spells” are ruining AI research

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https://qz.com/1274131/googles-engineers-say-that-lack-of-rigor-is-ruining-ai-research/
Rahimi co-authored a paper (pdf) that says that knowledge, nominally the goal of scientific research, is currently in second place to “wins,” the practice of beating a benchmark as a way to getting recognized in the AI community. The authors go on to highlight how this may be skewing the true nature of progress in AI and contributing to wasted effort and suboptimal performance. For example, researchers showed how stripping “bells and whistles” from a translation algorithm made it work better, which highlighted how its creators didn’t know which parts of the AI were doing what. It’s not uncommon for the core of an AI to be “technically flawed.”

Malcolm Harris on Glitch Capitalism and AI LogicIn the stories…

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http://new-aesthetic.tumblr.com/post/173482376950
In the stories of algorithms gone haywire, the glitches prompt programmers to reassess what they really want from their programs, and how to get it. What we can learn from the errors of machine learning is that we do not have to live according to a set of rules that produces obviously unfair and undesirable outcomes like a bloated one percent, apartheid prisons, and the single worst person in the country as president.

The Bosses We Remember

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http://www.swiss-miss.com/2018/05/the-bosses-we-remember.html
The bosses we remember:
1 provided safe space to grow
2 opened career doors
3 defended us when we needed it
4 recognized and rewarded us
5 developed us as leaders
6 inspired us to stretch higher
7 led by example
8 told us our worked mattered
9 forgave us when we made mistakes