Skateboarding Visualizations V1

PewDiePie, YouTube’s biggest star, is leaning into his new, far-right following

When Felix “PewDiePie” Kjellberg, YouTube’s most lucrative, popular superstar, uploaded a video featuring a banner with the words “Death to all Jews,” along with a man dressed as Jesus saying, “Hitler did absolutely nothing wrong,” he insisted it was jokes made in bad taste. 

After losing his partnership with Disney, Kjellberg apologized, saying he was just poking fun at the “modern world.”

But attempts to distance himself from his message didn’t deter the so-called “alt-right” from accepting him as one of their own, nor did Kjellberg’s insistence that he wanted nothing to do with them.

Kjellberg may not support them, but in the few short months since his anti-Semitism scandal, far-right celebrities have become Kjellberg’s favorite new bedfellows. Read more (7/26/17)

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Holo Messenger

Developer Abhishek Singh is creating an AR recorded video messaging app with iOS ARKit that is presented in classic Sci-Fi settings (and all the recording is done with a single normal camera):

Remember Princess Leia’s classic holographic message from Star Wars? Well I built this app using ARKit and some awesome tech from Aifi.io that allows you to record and send your own. If you want to know when it becomes available, head over here: http://bit.ly/holomsngr

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CAN 2017 – Highlights and Favourites

The always-fantastic Art & Tech resource Creative Applications have put together their list of highlights from the year:

As 2017 comes to a close, we take a moment to look back at the outstanding work done this year. From spectacular performances, large scale installations, devices and tools to the new virtual spaces for artistic exploration – so many great projects are being added to the CAN archive! Here are a just few, 25 in total, that we and you enjoyed the most this year.

Have a look for yourself here

Imaginary Soundscape

Online project from Qosmo generates ambient sounds to Google Streetview panoramas through Deep Learning processes, interpreting the visuals for appropriate sounds:

“Imaginary Soundscape” is a web-based sound installation, in which viewers can freely walk around Google Street View and immerse themselves into imaginary soundscape generated with deep learning models.

… Once trained, the rest was straightforward. For a given image from Google Street View, we can find the best-matched sound file from a pre-collected sound dataset, such that the output of SoundNet with the sound input is the most similar to the output of the CNN model for the image. As the sound dataset, we collected 15000 sound files from internet published under Creative Commons license and filtered with another CNN model on spectrogram trained to distinguish environmental/ambient sound from other types of audio (music, speech, etc.). 

You can try it out for yourself here, and find more background information here

Purple stimboard for anon

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From Microscopic to Multicellular: Six Stories of Life that We See from Space

Life. It’s the one thing that, so far, makes Earth unique among the thousands of other planets we’ve discovered. Since the fall of 1997, NASA satellites have continuously and globally observed all plant life at the surface of the land and ocean. During the week of Nov. 13-17, we are sharing stories and videos about how this view of life from space is furthering knowledge of our home planet and the search for life on other worlds.

Earth is the only planet with life, as far as we know. From bacteria in the crevices of the deepest oceans to monkeys swinging between trees, Earth hosts life in all different sizes, shapes and colors. Scientists often study Earth from the ground, but some also look to our satellites to understand how life waxes and wanes on our planet.

Over the years, scientists have used this aerial view to study changes in animal habitats, track disease outbreaks, monitor forests and even help discover a new species. While this list is far from comprehensive, these visual stories of bacteria, plants, land animals, sea creatures and birds show what a view from space can reveal.

1. Monitoring the single-celled powerhouses of the sea

Known as the grass of the ocean, phytoplankton are one of the most abundant types of life in the ocean. Usually single-celled, these plant-like organisms are the base of the marine food chain. They are also responsible for the only long-term transfer of carbon dioxide from Earth’s atmosphere to the ocean. 

Even small changes in phytoplankton populations can affect carbon dioxide concentrations in the atmosphere, which could ultimately affect Earth’s global surface temperatures. Scientists have been observing global phytoplankton populations continuously since 1997 starting with the Sea-Viewing Wide Field-of View Sensor (SeaWiFS). They continue to study the small life-forms by satellite, ships and aircrafts.

2. Predicting cholera bacteria outbreaks

Found on the surface of zooplankton and in contaminated water, the bacteria that cause the infectious disease cholera — Vibrio cholerae — affect millions of people every year with severe diarrhea, sometimes leading to death. While our satellite sensors can’t detect the actual bacteria, scientists use various satellite data to look for the environmental conditions that the bacteria thrive in. 

Specifically, microbiologist Rita Colwell at the University of Maryland, College Park, and West Virginia University hydrologist Antar Jutla studied data showing air and ocean temperature, salinity, precipitation, and chlorophyllconcentrations, the latter a marker for zooplankton. Anticipating where the bacteria will bloom helps researchers to mitigate outbreaks.

Recently, Colwell and Jutla have been able to estimate cholera risk after major events, such as severe storms, by looking at satellite precipitation data, air temperature, and population maps. The two maps above show the team’s predicted cholera risk in Haiti two weeks after Hurricane Matthew hit over October 1-2, 2016 and the actual reported cholera cases in October 2016.

3. Viewing life on land

From helping preserve forests for chimpanzees to predicting deer population patterns, scientists use our satellites to study wildlife across the world. Satellites can also see the impacts of perhaps the most relatable animal to us: humans. Every day, we impact our planet in many ways including driving cars, constructing buildings and farming – all of which we can see with satellites.

Our Black Marble image provides a unique view of human activity. Looking at trends in our lights at night, scientists can study how cities develop over time, how lighting and activity changes during certain seasons and holidays, and even aid emergency responders during power outages caused by natural disasters.

4. Tracking bird populations

Scientists use our satellite data to study birds in a variety of ways, from understanding their migratory patterns, to spotting potential nests, to tracking populations. In a rather creative application, scientists used satellite imagery to track Antarctica’s emperor penguin populations by looking for their guano – or excrement.

Counting emperor penguins from the ground perspective is challenging because they breed in some of the most remote and cold places in the world, and in colonies too large to easily count manually. With their black and white coats, emperor penguins are also difficult to count from an aerial view as they sometimes blend in with shadows on the ice. Instead, Phil Trathan and his colleagues at the British Antarctic Survey looked through Landsat imagery for brown stains on the sea ice. By looking for penguin droppings, Trathan said his team identified 54 emperor penguin colonies along the Antarctic coast.

5. Parsing out plant life

Just as we see plants grow and wilt on the ground, satellites observe the changes from space. Flourishing vegetation can indicate a lively ecosystem while changes in greenery can sometimes reveal natural disasters, droughts or even agricultural practices. While satellites can observe plant life in our backyards, scientists can also use them to provide a global picture. 

Using data from satellites including SeaWiFS, and instruments including the NASA/NOAA Visible Infrared Imaging Radiometer Suite and the Moderate Resolution Imaging Spectroradiometer, scientists have the most complete view of global biology to date, covering all of the plant life on land and at the surface of the ocean.

6. Studying life under the sea

Our satellites have helped scientists study creatures living in the oceans whether it’s finding suitable waters for oysters or protecting the endangered blue whale. Scientists also use the data to learn more about one of the most vulnerable ecosystems on the planet – coral reefs.

They may look like rocks or plants on the seafloor, but corals are very much living animals. Receiving sustenance from photosynthetic plankton living within their calcium carbonate structures, coral reefs provide food and shelter for many kinds of marine life, protect shorelines from storms and waves, serve as a source for potential medicines, and operate as some of the most diverse ecosystems on the planet.

However, coral reefs are vulnerable to the warming of the ocean and human activity. Our satellites measure the surface temperature of ocean waters. These measurements have revealed rising water temperatures surrounding coral reef systems around the world, which causes a phenomenon known as “coral bleaching.” To add to the satellite data, scientists use measurements gathered by scuba divers as well as instruments flown on planes.

During the week of Nov. 13-17, check out our stories and videos about how this view of life from space is furthering knowledge of our home planet and the search for life on other worlds. Follow at www.nasa.gov/Earth.

Make sure to follow us on Tumblr for your regular dose of space: http://nasa.tumblr.com.

Sketch-RNN Demos

Project from Google’s AI Experiments is a collection of demos which can generate a doodle from a small input using neural networks:

This experiment lets you draw together with a recurrent neural network model called Sketch-RNN. We taught this neural net to draw by training it on millions of doodles collected from the Quick, Draw! game. Once you start drawing an object, Sketch-RNN will come up with many possible ways to continue drawing this object based on where you left off. The model can also mimic your drawings and produce similar doodles. It’s just another example of how you can use machine learning in fun and creative ways. 

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