The CGI Hugh Jackman In Logan

Independent study on support vector machines

Human Pose Detection - Mining Body Language from Videos

Machine Learning investigation from samim examines body language in video using recently released open-source code library OpenPose:

From Gene Kelly’s Step-Dance to Bruce Lee’s Kung-Fu — iconic movement has made history. Communicating through Body Language is an ancient art form, currently evolving in fascinating ways: Computationally detecting human body language is becoming effective and accessible. This experiment explores enabling technologies, applications & implications.

For over 20 years, Motion Capture has enabled us to record actions of humans and then use that information to animate a digital character or analyse poses. While movie makers and game developers embraced such technologies — it until recently required expensive equipment which captured only few aspects of the overall performance.

Today, a new generation of machine learning based systems is making it possible to detect human body language directly from images. A growing number of research papers and open-source libraries addresses key aspects: Body, Hand, Face, Gaze Tracking. Identity, Gender, Age, Emotion and Muscle strain Detection. Action Classification & Prediction. We now can…

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NSynth Super

Project from Google Creative Lab is an open source physical interface for their NSynth project, which generates news sounds using Machine Learning to understand them:

Building upon past research in this field, Magenta created NSynth (Neural Synthesizer). It’s a machine learning algorithm that uses a deep neural network to learn the characteristics of sounds, and then create a completely new sound based on these characteristics.

Rather than combining or blending the sounds, NSynth synthesizes an entirely new sound using the acoustic qualities of the original sounds—so you could get a sound that’s part flute and part sitar all at once.

Since the release of NSynth, Magenta have continued to experiment with different musical interfaces and tools to make the output of the NSynth algorithm more easily accessible and playable.

Using NSynth Super, musicians have the ability to explore more than 100,000 sounds generated with the NSynth algorithm.

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Bitcoin micropayments: Coming to smartphones—and toasters?—everywhere

Micropayments might not top your list of most compelling inventions, but they’re a sought-after capability. Small payments of less than a dollar, or even less than a cent, have the potential to shake up old, established business models, and open up new doors for the Internet of Everything.

Small digital payments have been tried again and again—in fact, Web inventor Tim Berners-Lee tried to embed micropayment capability into the original World Wide Web, but without success. So far, inherent transaction costs have been an unsurpassable hurdle.

Some argue that digital payment methods like bitcoin are the way forward.

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give em the ol’ razzle dazzle

Harry Potter and the Neural Network fan fiction

Or, what happens if you train a neural network on the titles and plot summaries of over 100,000 works of Harry Potter fan fiction.

In the decades since the Harry Potter books were published, fans have written literally hundreds of thousands of Harry Potter stories of their own, and shared them online. Can a neural network join in on the fun?

In a way, everything a recurrent neural network writes is fan fiction. A recurrent neural network looks at an example dataset (such as the complete Sherlock Holmes stories) and teaches itself the patterns and conventions that it sees. So, if it’s given Sherlock Holmes stories, it will become obsessed with Holmes and Watson, and if it’s given knock-knock jokes, it will spend all day telling awful knock-knock jokes of its own.

Thanks to an idea by a couple of readers, some heroic work by @b8horpet in scraping (with permission) hundreds of thousands of Harry Potter fan fiction titles and summaries from AO3, and a flexible new recurrent neural network implementation by Chen Liang, the neural network’s latest obsession is Harry Potter.

The Perfect Party by iamisaac Draco has been left alone, and Ginny confused must learn and who has his best friend. They were breathed by a love that didn’t become his grounds and the flowers begin.

This is a typical example of the neural network’s fan fiction - romantic pairings of two or more Harry Potter characters (called “ships” in fan fiction-speak). In this case, it even has chosen a plausible author: iamisaac is a real and fairly prolific fan fiction author whose works do tend to be of the “romantic” variety. 

The Garden by perverse_idyll for lexigilite Ron and Hermione move after a man party. What did her best things go and has to deal with people she loves? How many imperfect love really belonges them and needs to be a person? Or will they learn and more than the war? Mirror Thing by Queen_Elexhan “Are you there for a relationship? I was a sad future for your love.”  Harry and Ginny find out the meaning is.

Shatters by Kis [archived by TheHexFiles_archivist ] Based on the Spot Are It Falls Into A Heir by NextrangeOnTheThree Draco and Hermione share a whole indescribbening.

Again, “perverse_idyll” and “TheHexFiles_archivist” are fairly active authors. (Hi, if you’re reading! The neural network seems to like your writing, and is writing fan fiction of your fan fiction!) Those familiar with Harry Potter fan fiction will not be surprised to learn that the neural network really likes to generate ships; pretty much every combination of characters is represented (some of the more unusual combinations being “The Snow/Voldemort”, “The Ministry/Draco Malfoy”, and “Voldemort/Random Quidditch Child”).

By turning down the neural network’s creativity setting to near-zero, we arrive at its vision of what the quintessential Harry Potter fan fiction would be like - and we also learn its favorite ship:

Persuading by theladyblack Harry and Draco are still a second chance at the end of the war.  Will they be able to do with the fairy tale of the first time they were a strange stranger to the street of the war and the war is over?

It turns out the neural network is obsessed with Harry/Draco, although in a pinch, Sirius/Remus will also do.

The neural network also seems to really like stories about Professor Snape trying to do rather ordinary things:

New Moon Boys by Dungoonke for Loki_Kukaka Severus Snape comes back to a night’s politics.

In the Reason Is Blinders by LittleRoma Severus has been through his lost remote.

In The Alteri Silence by Forest_of_Holly for roscreens41 Snape receives life after plants to do by work over whether they get into. Just Hell.

A Second Chance by DarkCorgi Snape had a second thing, and that is better than anything for for the rest of his life.

Mirror by orphan_account Severus Snape tries to get a lot of dragons and that was to be more than he didn’t expect to continue. He has always been a bit of an old and a baby to stay the way he’d been the brother at Hogwarts and he keeps the chance of meeting… Deception by FlyingEyes Snape is a British Robes of interesting things and worrys like a little fun and sees the pretty battle for a while.

Another thing that happened, which is pretty much my favorite thing ever, is that the neural network apparently encountered some fan fiction stories that were not in English. As a result, it learned to do this from time to time:

The Secretary Of the World  Challenge inspired by GoF and la mating resigns de la mill colors per mereple beruit carteur la pelete el wert rardo completing and herillo intus den una a des rush sentines kelta an transoles… 

Between by Cheyangel13 A series of fivers are unexpectedly depressed and controlled by the bed, with least more from una perfemale erpensa de the maesse akai suidadium dela vida call de la los se terriuus do form en sou dies de fasurard il resisted de for dogs la sementu sein prong colors itu dee adte se sige natard…

The neural network has also learned to employ capital letters:

Les finds love by violet_quill for starstruck1986 Severus Snape wanted him to be more and she likes Draco.  The person he wants an energy to him.  WHALIDE NO GEATIRE SOURR INSPE AHARMANABLISH ALL SOME TO VERY THE RERIDE!!!!!!!

secret Quidditch by snapsleert Collapse and find the second worst and very different. See Gain and Descent motivate surprising death. Unbusing one of the months: should make more bumo.choooshots. HUGULATED

And the neural network occasionally uses content warnings, although it seems to have a rather fuzzy idea about what to warn its readers about:

Better With The Broom Complicate by Margyn_Black Tonks gets more than the best girl of creation. (Rated Maturisle, mark, a violence, contract) (slash] part of themes) ferret.

Art for the Sun a Scary by disillusionist9 A collection of warnings: characters and situations of silence.

Some of the neural network’s stories, though, are just plain weird.

Harry Potter and the Painful Eyes by dark_pook A Birthday drabble about the problems and a woman who shows up a lot less than she checks at Hogwarts in the destiny to the infamous adventure of control of the Art of The Good Boy Kings With Hermione. Harry and the Blue Special Delicious by apolavia_scg An unexpected potions messaged in the world their lives are to find friendship following the day of different pagers. James and Lily come to the summer before the war.

The Perfect Cow by alafaye Severus and Hermione start a horcruxes

Art: Let Draco roll the light of the moon, and means. by Dangelanne What happens after the war. Not drawn to Draco Malfoy jumpers. Originally written in 2008.

Birds of a Saturday by SasuNarufan13 Harry Potter is drunk and discovers he is an alternate universe.

Holly theody by yesIpxdishoftlyGrinli What would be dangerous! Side Voldemort Jones does all lord off the sunshine show.

Lily Evans and the Ravenclaw of a Christmas Surprise by ci Severus angst the truth of a frighten situation for the wink.

Persuasion by Samanthian The Sorting Hat is fighting in one of the houses.

lily’s family by sharkle Harry woke up in searching after a werewolf Sherlock’s picnic. He is furious.

As a bonus, I leave you with some fairly-plausible screennames the neural network invented, which appear not to be taken (yet):

desire_at_the_malfoy SeverelyAshed fishlingthelovely thedarklyblue phantombeers captainingthetrain siriusly_harry DarkVoldember ChildOfAtSperble all_frogs BelladonnaLeek Sneaking_UnicornWitch bluemelooppiesweatled

Robot uses deep learning and big data to write and play its own music

A marimba-playing robot with four arms and eight sticks is writing and playing its own compositions in a lab at the Georgia Institute of Technology. The pieces are generated using artificial intelligence and deep learning.

Researchers fed the robot nearly 5,000 complete songs — from Beethoven to the Beatles to Lady Gaga to Miles Davis — and more than 2 million motifs, riffs and licks of music. Aside from giving the machine a seed, or the first four measures to use as a starting point, no humans are involved in either the composition or the performance of the music.

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Kidachi

Japanese programmer has unveiled proof-of-concept effects for Augmented Reality game made with ARKit including visual filters and Predator-like optical camouflage:

ミッション1【野良アンドロイド（光学迷彩搭載機）の発見・確保】 #ARKit pic.twitter.com/7m0esEGrUt

— kidachi (@kidach1) August 19, 2017

[Bing Translation:] Mission 1 [Nora Android (optical camouflage aircraft) find & secure] #ARKit 

You can follow Kidachi on Twitter here

LASER SOCKS!

Game developed by Glen Chiaccchieri where players lose life bar when opponent’s feet is hit with a laser from a pointer, and is a proof-of-concept implementation of the computing concept ‘Hypercard in the Room’:

In the video above two people are playing Laser Socks, a game I invented in an afternoon using a research programming system, common household items, and a couple lines of code.

Players try to point a laser pointer at their opponent’s socks while dodging their opponent’s laser. Whenever they score a hit, the health meter closest to their opponent’s play area fills up with blue light. Whoever gets their opponent’s meter to fill up first wins.

In August 2015, my research group (The Communications Design Group or CDG) had a game jam — an event where participants create games together over the course of a few days. The theme was to make hybrid physical/digital games using a prototype research system Bret Victor and Robert Ochshorn had made called Hypercard in the World. This system was like an operating system for an entire room — it connected cameras, projectors, computers, databases, and laser pointers throughout the lab to let people write programs that would magically add projected graphics and interactivity to physical objects. The point of the jam was to see what playful things you could make with this kind of system. We ended up making more than a dozen new and diverse games.

I made Laser Socks, a game about jumping around and shooting a laser pointer at an opponent’s feet. It was fun, ridiculous, and simple to make. In some ways, Laser Socks became one of the highlight demonstrations of what could be done if there was a medium of expression that integrated dynamic computational elements into the physical world.

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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.