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
Labels:

Comments

Post a Comment

Popular posts from this blog

Solving Van der Pol equation with ivp_solve

Van der Pol’s differential equation is The equation describes a system with nonlinear damping, the degree of damping given by μ. If μ = 0 the system is linear and undamped, but for positive μ the system is nonlinear and damped. We will plot the phase portrait for the solution to Van der Pol’s equation in Python using SciPy’s new ODE solver ivp_solve . The function ivp_solve does not solve second-order systems of equations directly. It solves systems of first-order equations, but a second-order differential equation can be recast as a pair of first-order equations by introducing the first derivative as a new variable. Since y is the derivative of x , the phase portrait is just the plot of ( x , y ). If μ = 0, we have a simple harmonic oscillator and the phase portrait is simply a circle. For larger values of μ the solutions enter limiting cycles, but the cycles are more complicated than just circles. Here’s the Python code that made the plot. from scipy import linspace from ...
Post a Comment
Read more

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 ...
Post a Comment
Read more