Skip to main content

Have You Ever Really Seen the Moon?

On a whim, Wylie Overstreet set up his telescope outside his apartment. He wanted to look at the moon. He had no idea he would, in a matter of hours, inspire awe in hundreds of strangers on the streets of Los Angeles. “It's incredible how many people have never looked through a telescope,” Alex Gorosh, a friend of Overstreet’s, told The Atlantic. “Many people thought the image wasn't real—they thought we were playing a prank on them.”


Overstreet and Gorosh were so taken by strangers’ reactions to the moon through their telescope that the friends began to set it up in different locations across the city, filming as they went. “That's when we recognized the powerful message of unity that we were capturing,” said Gorosh.


Their resulting film, A New View of the Moon, is a simple tribute to human wonder. Like last year’s total solar eclipse, Overstreet and Gorosh witnessed how a cosmic event has the power to bring people together. “It's about taking a step back and appreciating the beauty and grandeur of the natural world around us,” said Gorosh. “It sounds cheesy, but if we were able to do that more often, it would be much easier to work through the divisions that we're facing as a culture.”


The Atlantic https://ift.tt/2pSgFcA March 29, 2018 at 11:57PM

Comments

Popular posts from this blog

Explaining models with Triplot, part 1

[This article was first published on R in ResponsibleML on Medium , and kindly contributed to R-bloggers ]. (You can report issue about the content on this page here ) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Explaining models with triplot, part 1 tl;dr Explaining black box models built on correlated features may prove difficult and provide misleading results. R package triplot , part of the DrWhy.AI project, is aiming at facilitating the process of explaining the importance of the whole group of variables, thus solving the problem of correlated features. Calculating the importance of explanatory variables is one of the main tasks of explainable artificial intelligence (XAI). There are a lot of tools at our disposal that helps us with that, like Feature Importance or Shapley values, to name a few. All these methods calculate individual feature importance for each variable separately. The problem arises when features used ...

The con behind every wedding

With her marriage on the rocks, one writer struggles to reconcile her cynicism about happily-ever-after as her own children rush to tie the knot A lavish wedding, a couple in love; romance was in the air, as it should be when two people are getting married. But on the top table, the mothers of the happy pair were bonding over their imminent plans for … divorce. That story was told to me by the mother of the bride. The wedding in question was two summers ago: she is now divorced, and the bridegroom’s parents are separated. “We couldn’t but be aware of the crushing irony of the situation,” said my friend. “There we were, celebrating our children’s marriage, while plotting our own escapes from relationships that had long ago gone sour, and had probably been held together by our children. Now they were off to start their lives together, we could be off, too – on our own, or in search of new partners.” Continue reading... The Guardian http://ift.tt/2xZTguV October 07, 2017 at 09:00AM