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analyticstraininghub · 2 years

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What is the Future Scope of Data Analytics in India?

Data Visualization has changed the way how we visualize data. The changing time, evolving digitization, and the Future scope of data analysts in India have caused the way complex data is handled. Visualization of complex data has brought about a revolution that surpasses the artificial intelligence intellect. The very reason that makes us humans better than algorithms, coding, and machines is the human intellect and how it evolves with exposure to make a future in Data Analytics.

Future Scope of Data Analysts in India:

India is a land of multiple opportunities and any firm trying to establish itself in the land would agree that the kind of trade in India has evolved over the past decade. Traders, businesses, and startups in India have become a lot more competitive and healthy competition is visible in the selection and hiring process and hiring process makes the Future scope of Data Analyst because it’s become need first then Demand.

But, to be able to access the insight hidden away in the mass accumulated data needs a careful analysis and representation in a simple format like a report or an interactive dashboard. So, the generated data can be queried and profitable insights might be generated to gain an edge over the vast competition in the market.

Data Analytics Skills for a Successful Career:

Data visualization is a skill learned by all but mastered only by a few. As a result, it has created a massive void in the industry that needs filling up. The void is the lack of skilled professionals in the field of data analytics. There is a rising need for more and more data analysts and that seems like good news for any fresher looking to make a career in the data analytics industry. The skill itself is not a challenging one to master, but getting a hang of being able to question the accumulated data is something of a challenge that even sometimes the most seasoned skilled professionals in this field of work tend to face.

Data Visualization:

In the context of visualization, every report should affirm directly the content. It’s got to get out of the way because it’s about the relationship with the viewer and how they reason with the content. Style and aesthetics cannot rescue failed content. If the words aren’t true, then even the most visually appealing content cannot transform false facts into truth. There are enormously beautiful visualizations, but it is proof of the truth and the authenticity of the information. The big steps in showing information began with cartography about 6,000 years ago, when the first map was scratched into a piece of stone and that is how we have wound up now with the most widely seen visualization in the world. Take the example of Google Maps, where people are using visualization to transform a flat surface called a map into a visualization.

The next big step was the development of real science. Galileo got his telescope going. He made stunning sketches of sunspots as he watched the sun for 40 days. After which he assembled the engravings of the sunspots and visualized what he had recorded and so the history of visualizing data is very substantially a history of science. Data visualization is not just some airy-fairy shenanigans but an extremely creative process, but it’s a very linear process of decision-making that you can do based on a few basic principles.

Three things that a user should keep in mind while designing a visual: –

As the designer what you have to say and what you want to communicate.

That reader is not you and they’re going to come with their context and their own biases and their assumptions and you need to account for that.

The data itself, what that has to say, and how that informs the truth.

There’s a lot of subconscious brain activity happening. We evolved for it to happen that way and to see things and make snap decisions. We have to be able to recognize patterns right away and make snap decisions on them to survive and that can be an advantage as a designer. The user may communicate a lot of information very quickly because we all have brains that are designed to recognize patterns this way. But also, there’s the emotional impact.

We as human beings tend to react to design and art and the aesthetics of a piece, just as much as we react to the information contained in it. So if the user wishes to change someone’s mind, if he/she intends to change someone’s behavior, sometimes presenting the information in a visual format is the fastest way to get them to engage with that information. Truth is one of those ambiguous things that you can’t really define and probably change and evolve is the enhanced understanding one has of the topic. Data itself is a result of research.

So, in simpler terms “data is just a clue to the end truth”. We believe that a successful infographic tells a story. It links massive and sometimes complicated data in a way that many people can understand.

The first step usually is always to dig deeply into the data yourself and find each key point and create a hierarchy and a narrative out of that story. When the user starts to merge different pieces of information and when they start to learn really what it’s all saying, the narrative becomes clear. The one key fact that everything can revolve around, is the hero of the piece which is the data visualization. There’s one single piece of data or insight that people respond to any kind of feature that encapsulates the whole vision and invites people in to see the nuances and all of the rest of the story around it. When you look at a piece, that has successfully translated data from something complicated to something simple.

The deepest curiosity lies on the edge between data and culture. There’s a revelation, which is to show us something that we’ve never seen before. Anybody can visualize data in Excel and display some bar charts. But with data visualization, it’s about showing them something in this kind of loose narrative frame that they can interpret. Part of it is leaving it open to interpretation, but part of it is also not knowing. Nobody has some miraculous masterful understanding of this system that you don’t. The user may have some ideas about how these systems might be changing and how they might be growing may be important for culture and society, to share some of those ideas with colleagues. And maybe the user can put together something that someone else wouldn’t have been able to. The general population is a lot smarter than we think. So, it’s not about knowing your audience but rather about respecting your audience and knowing the content.

Popular tools utilized for Data Visualization:

1. Tableau

The most popular visualization tool in use. Launched in 2003 and since then has been growing strong. The application has a knack for handling huge masses of data with ease.

2. Power BI

Launched by Microsoft in 2013, it has been going headstrong in the Gartner quadrant and is extremely popular with small to mid-sized businesses because of its low-cost subscription package.

3. QlikView

It is another popular visualization tool famous among analysts that helps them enhance data visualization processes. Similar to Tableau, QlikView is popular for handling big masses of data with ease. The only issue is that it is not available at a cheaper cost for more personal use.

Data Visualization salary in India: –

Salary starting at entry-level for a Data Visualization professional – INR 3.25 lakhs per year

Salary starting at mid-level for a Data Visualization professional – INR 6.35 lakhs per year

Salary starting at senior level for a Data Visualization professional – INR 8.5 lakhs per year

The grasp of the concepts for both the profiles may differ but a fresher with the relevant knowledge in the field and with sufficient years of experience and a little bit of help from Analytics Training Hub might help any seasoned professional data analyst ace an interview for a Data scientist in the future. The skills are trainable but it’s the attitude and aptitude to of adapting oneself to the knowledge and implications of data analytic tools like Tableau which may move to one’s advantage.

The brighter prospects of data analytics have already been confirmed by a business review done by Harvard University, claiming ‘Data Scientist as the sexiest job of the 21st century. Although we believe that Data Analyst and Data Scientist sound like two completely different job profiles, especially with the suffix words of both the job titles sounding or rather being the same. There’s no need to worry as the job profile of a ‘Data Analyst’ is a stepping stone or rather the first step to becoming a ‘Data Scientist. Also, the Future Scope of Data Analysts in India is in high demand. So if you are a fresher or just about to switch your profile in Data Analytics so do not worry Future Scope in Data Analyst is way more widespread than in other fields. Choose your path in Data Analytics because Salary Package is above your expectations as a fresher.

Some useful links are Below:

To Know more about Data Analyst visit - Analyticstraininghub.com

To Know more about our Data Analyst Certification courses visit - Analyticstraininghub.com

Must visit our official youtube channel - Analyticstraininghub.com

#dataanalyticscareer #datascience #futureofdataanalytics #analyticstraininghub #technology #artists on tumblr

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botter-butter · 5 years

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Earth sent them out to study space. They collected data for their creators, analyzed samples, compiled studies from the celestial bodies around them. Like their creators, they thought they were alone (of course they had their siblings and their friends and their creators there, to gather and share their findings) in the void of space. But they found others. Others like them, the rovers, the satellites and probes, with the ability to change shape, to transform, to think and feel. And they were ecstatic about the discovery.

Cybertronians. Older... Wiser... Bigger.. Intelligent...er. And they've explored space! Made stuff!

If only Cybertronians were equipped to deal with these Earthlings... both organic.... and mechanical.

Chapter 1: OAO-2 Stargazer: Origins

Word Count: 630

Characters: Stargazer (OC),

Pairings: None

Fandom: Transformers: More Than Meets the Eye/ Lost Light

Rating: G

Warnings: None

A/N:

This is an AU.

Most if, not all the OCs, use they/them and/or she/her pronouns

These OCs are based on the various space probes created and sent into space by Earth

The main cast will eventually show up

Read here on Tumblr

At first, there was warmth. An orange glow of thrusters, the breaking of the atmosphere, and burning metal. They couldn’t see, couldn’t hear, couldn’t feel the heat that was slowly making itself down to their outer plating.

There was no panic settling in when the first part of the thrusters disengaged. They did not fear the sudden weightlessness as the fuel dissipated.

Darkness. That is what they… saw. Yes. Cold. Hot. That is what they felt. Light. Pinpricks of light began to appear. To register in their systems.

Oh. It was bright! The… Sun! Yes! That was the Sun.

It’s what warmed Earth up! Earth was… is…. Earth is home! Where they were created! Yes!

Consciousness. They were beginning to recognize where they were! They’re in space! Space, yes, space! They had- no wait… have- they have a mission! Gather data! Yes.

Stargazer! That’s their name! Yes! Stargazer. They are out here, in space, to gather data. To, look at the stars. Record something… record… Ultra violet light! Yes!

They felt some shifting, their systems registering something new. Data began to pour in from their surroundings, from their instruments. The data is beginning to register, the wavelengths. Earth? Sun? Of everything?

How exciting!

How beautiful!

There is so much. Too much. Where did they have to put it? Where?

No. Who? Oh Earth! That’s where! They have to send it to Earth! Back home! Back to their creators! Yes. But how…?

There was a ping inside their systems. The data began to flow out of their many receivers, the signals being sent back (down or up?) to Earth. A ping registered in their system, a confirmation that Earth received the message.

NASA, said the ping. NASA received it.

NASA… was… familiar.

“T H A N K Y O U S T A R G A Z E R.”

“Y O U ‘ R E W E L C O M E… N A S A.”

Stargazer… started to feel giddy. Emotion? That’s what this is? Oh. Happy! Yes! They were starting to feel happy! The data’s being collected much faster, now. Coronas of stars, of the sun, a comet!

“N A S A! H I!”

“H E L L O!”

“I F O U N D S T A R S!”

“H OW DO T H EY LO OK?”

They began to think… how could they describe it? Words start coming to them. “Beautiful.” “Perfect.”

“SPEC TAC ULAR,” Stargazer sent back.

“GOO D.”

Something about that word made them feel happy… NASA was nice. NASA is nice. NASA sounds familiar, seemed familiar. Did… they know NASA? They think for a moment… Thinking… is new.

More data is coming in. From NASA this time.

Then it registers in the telescope’s mind, shortly created moments before. NASA is their creator. There are people on Earth. Humans. Homo sapiens sapiens. Creators. They want to know. They want to collect. They want to observe.

They want to learn about space!

Stargazer is a step towards that. One of the very first steps to going beyond the moon (there’s a moon!) Stars! The sun!

“NASA! THANK YOU!”

“???”

“FOR CREATING ME.”

Gratitude began to fill their systems. And something began to shift. Panels began to move, internals slowly began to rearrange themselves to settle carefully to accomodate hinges, pivots and joints. Limbs began to appear on their peripheral. They… had limbs attached to… hands? And… feet? Oh they have digits! Fingers! They wiggle them, reaching out carefully to observe them.

“HANDS.”

“YES!”

“SPECTACULAR!”

These limbs are amazing. Oh! Something moved again. Their vision changed (when did that happen?) and moved. They were turning. A head?

“I HAVE A HEAD.”

Amazing.

NASA is a good creator.

“CREATOR. THANK YOU.”

A little ping from NASA.

“NASA?

“HAPPY BIRTHDAY STARGAZER.”

#Transformers #maccadam #TF OC #TF OC: Stargazer #Buttered writing #I love them #( ͡° ͜ʖ ͡°) discord ramblings #Fic: Earthling AU

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scoutshonor56 · 5 years

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Burning Down the House

With a new year upon us, I decided to leave our pouting, petulant, and clueless “president” alone for a while. I’m at the point where I don’t want this blog to become a regular, though fun and cathartic, critique of this moron’s day to day behavior. Besides, who can keep up these days? Certainly I never intended this blog to become solely a political airing of grievances anyways, when started back in November of 2016 - but then, who would have ever envisioned the likes of Donald Trump in the White House?

So today I’m going to address an issue close to my heart; the wellspring that nourishes my spirit and is essential to the health and well-being of every living thing on our planet – the environment. You see, I’m a baby boomer who grew up in the 60’s, and was quite the impressionable 14yr old on April 22, 1970, when the first official Earth Day was proclaimed. That year also saw the creation of the EPA, and like most of us from “back then”, I still hold onto many of the ideals of an aged hippie -

Those who know me also know I later worked for NASA - another touchstone for my generation - at Johnson Space Center, inside the television/communication contract, for 14 years. During that time I got to watch the Space Station being built piece by piece, from when the first module, Zarya, went up on a Russian Proton rocket, to the first crew occupation, to its successful completion.

I still pay attention to our space program as a tax paying enthusiast, although not nearly as much, and thus I watched a fascinating show on NOVA a week or so back, entitled “To Pluto and Beyond”. It was about the continuing voyage of NASA’s New Horizons exploratory spacecraft, which is now traveling at roughly 37,000mph some 5 billion miles from our planet and still able to send back data and outstanding imagery to its home base here on Earth (taking over 4 hours to do so).

In a nutshell, when New Horizons was first launched, in January of 2006, scientists and astronomers didn’t even think much existed past what they call the Kuiper Belt (the area in space past the planet Neptune), other than insignificant, floating chunks of minerals and ice of varying size and shape – such as Pluto, now not even an officially termed “planet”.

But soon that would change as our telescopes got larger, more sophisticated, and certainly more powerful (such as the Hubble), revealing a wealth of new discoveries and vastly widening out view, and theories, about space past our solar system.

In just a little over two years after its successful flyby of Pluto and its moons, sending back stunning and never before seen imagery, project managers were able to plot a new course that would enable the probe to fly past what is now called 2014 MU69, or its more colorful nickname, Ultima Thule (which sounds much more bad-ass!)

To go into any detail about the show and this discovery would require a whole different blog, so for my purpose today, let’s just say the level of technology, engineering, and computational math involved in this exploratory endeavor is right up there with just about any other high achievement in man’s history; an incredible display of determination and shear brain power that simply boggles my mind. Sure, it was just an unmanned flyby, a probe…but successfully plotted over billions of miles, traveling at 37,000mph through orbiting planets, asteroids, and clouds of space debris, where a collision with something the size of a pea could mean instant disaster? Where the tiniest fraction of miscalculation can put the craft literally millions of miles off course? In the harshest and most unforgiving environment imaginable? You may as well try to explain quantum physics to me.

So what - what’s this got to do with a Talking Heads song... my point is this: excuse me if I don’t buy into this long running campaign of bullshit and misinformation put out by the petrochemical and carbon-based conglomerates, their money-wallowing and soulless lobbyists, and the special interest groups, who for the better part of fifty years have retained a complete stranglehold on our politicians and policy makers. They continue to control the discussion of our energy sources with fairy tales and scare tactics in support of a technology that is over 200 years old. Let’s dim the lights, roll out the boogyman, and wind him up:

“It will cost jobs!! The transition to renewable and clean energy is too expensive, the sources unable to compete in today’s economy!! The technology and infrastructure have yet to be fully worked out!! It’s much more difficult and complicated than you can possibly understand!! It’s simply going to take more time – it will be a long, slow process, and oil and gas will continue to play a dominant role in the meanwhile!!”

And on, and on, and on…

Bullshit! Germany now gets 40% of all its energy generated from renewable, clean sources. There are other countries in Europe harnessing tides to generate energy. Our planet is a hotbed for thermal energy potential. A recent study done here in Houston, at Rice University, claims Texas (who leads the nation in wind generated energy) has enough sun and wind to completely wean itself off coal within the near future.

Since when did America become the nation that couldn’t; that shied away from a challenge, technological or otherwise; that chose to follow instead of lead… was I stoned during that period? Did I miss something? Fifty-eight years ago, President John F. Kennedy stood at a podium at Rice University Stadium and declared:

“We choose to go to the Moon! We choose to go to the Moon...We choose to go to the Moon in this decade and do the other things, not because they are easy, but because they are hard; because that goal will serve to organize and measure the best of our energies and skills, because that challenge is one that we are willing to accept, one we are unwilling to postpone, and one we intend to win, and the others, too.”

To put this into context, at that time it had been just over a year since America had launched their first man into space: Alan Shepard riding a Redstone rocket 116 miles into suborbital flight, lasting fifteen minutes. Back then NASA scientists and medical professionals didn’t even know if a human could survive such a trip, or for how long. Would they retain their vision, their mental capacity? Would they lose all sense of direction? Pass out? Would they be able to endure and function during the required long duration flight to the moon and back? How would we even achieve such a feat?

OK, some might say, “Well, sure, NASA had a limitless budget - and after all, the space race was strictly for nationalistic reasons anyway, to beat the Russians to the moon…”

All true, but umm, have you looked out your window lately? Pay attention to any news? And no, Fox doesn’t count. According to a recent analysis, published in the Journal Science (see the story in the NY Times), our oceans are warming far more quickly than previously thought; like 40% faster on average than a United Nations panel estimated five years ago. Researchers now conclude that ocean temperatures have been breaking records for several years straight. Compounding the effects of our melting polar caps, warm water also takes up more volume than cold water, resulting in sea levels rising at an estimated rate of .13 inches (3.2mm) over the last 20 years. Satellite measurements tell us that over the past century the Global Mean Sea Level (GMSL) has risen by 4 to 8 inches.

Right now, over the last decade, we are seeing an increase in the number and severity of hurricanes, monsoons, tornadoes and wildfires. NEWS FLASH Gomer and Thelma Lu, this isn’t a conspiracy perpetrated by greedy and alarmist eggheads in lab coats, nor is it “fake news” or fuzzy science; and it certainly shouldn’t be considered, or treated as a political issue. It’s rock-solid, provable science that is accepted by 97% of scientists, climatologists, and geologists all around the world, who continue to ring the emergency bell. It’s happening today, all around us, and the bad news is we’re already too late; at this point, if we were to get serious this year, 2019, it will still be a game of damage control; of mitigating the consequences of our greed, ignorance, and gullibility.

In comparison, the goal and challenge of beating the Russians to the moon seems quite miniscule to that of restoring and maintaining the health of our little blue lifeboat called Earth.

“Whatever, our planet is a dynamic, ever changing thing - Earth has gone through similar climate changes before!” Yes, true – but over the span of tens of thousands of years, you moron. Man has achieved the same results in barely two hundred.

Just curious, but what part of 2.5 million pounds/second of co2 pouring into the relatively thin, fragile layer of atmosphere that protects our planet don’t you get? Too hard to think about, or conceptualize? Or is it easier for your lazy, flabby, unexercised brain to simply believe that it all just dissipates into outer space – you know, where the alien abductors that beamed you up into their mothership that weekend reside…

Make America Great Again? What a sad, short-changed, and utterly empty joke of a campaign slogan… Here, I’ve got one for you: SAVE OUR PLANET! For your children’s future and their children’s future. There simply is no option; no magical, last minute solution. No plan B. No spare planet accessible, sorry, this isn’t a movie - its real.

I simply don’t understand; why isn’t this the number one issue of concern for everyone? Could there possibly be a greater threat and more important challenge facing us all today?

Ah well, what the hell – we’ll all be fine in a couple thousand years after we evolve with gills and become aquamen and women… Although, good luck finding something to eat, as we’re also killing the entire food chain of life in the oceans, from coral reefs to the dolphins, the sharks, and the whales…I guess we could become aquacannibals – now there’s a surefire idea for a hit movie! Hmm, I wonder if we could talk Jason Momoa into that hard turn in the movie series plotline…

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scifigeneration · 6 years

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Are we alone? The question is worthy of serious scientific study

by Kevin Knuth

US F/A-18 footage of a UFO (circled in red). Creative Commons Attribution-Share Alike 4.0 International license. Parzival191919, CC BY-NC-SA

Are we alone? Unfortunately, neither of the answers feel satisfactory. To be alone in this vast universe is a lonely prospect. On the other hand, if we are not alone and there is someone or something more powerful out there, that too is terrifying.

As a NASA research scientist and now a professor of physics, I attended the 2002 NASA Contact Conference, which focused on serious speculation about extraterrestrials. During the meeting a concerned participant said loudly in a sinister tone, “You have absolutely no idea what is out there!” The silence was palpable as the truth of this statement sunk in. Humans are fearful of extraterrestrials visiting Earth. Perhaps fortunately, the distances between the stars are prohibitively vast. At least this is what we novices, who are just learning to travel into space, tell ourselves.

Cover of the October 1957 issue of pulp science fiction magazine Amazing Stories. This was a special edition devoted to ‘flying saucers,’ which became a national obsession after airline pilot Kenneth Arnold sighted a saucer-shaped flying objects in 1947.

I have always been interested in UFOs. Of course, there was the excitement that there could be aliens and other living worlds. But more exciting to me was the possibility that interstellar travel was technologically achievable. In 1988, during my second week of graduate school at Montana State University, several students and I were discussing a recent cattle mutilation that was associated with UFOs. A physics professor joined the conversation and told us that he had colleagues working at Malmstrom Air Force Base in Great Falls, Montana, where they were having problems with UFOs shutting down nuclear missiles. At the time I thought this professor was talking nonsense. But 20 years later, I was stunned to see a recording of a press conference featuring several former US Air Force personnel, with a couple from Malmstrom AFB, describing similar occurrences in the 1960s. Clearly there must be something to this.

With July 2 being World UFO Day, it is a good time for society to address the unsettling and refreshing fact we may not be alone. I believe we need to face the possibility that some of the strange flying objects that outperform the best aircraft in our inventory and defy explanation may indeed be visitors from afar – and there’s plenty of evidence to support UFO sightings.

The Fermi paradox

The nuclear physicist Enrico Fermi was famous for posing thought provoking questions. In 1950, at Los Alamos National Laboratory after discussing UFOs over lunch, Fermi asked, “Where is everybody?” He estimated there were about 300 billion stars in the galaxy, many of them billions of years older than the sun, with a large percentage of them likely to host habitable planets. Even if intelligent life developed on a very small percentage of these planets, then there should be a number of intelligent civilizations in the galaxy. Depending on the assumptions, one should expect anywhere from tens to tens of thousands of civilizations.

With the rocket-based technologies that we have developed for space travel, it would take between 5 and 50 million years for a civilization like ours to colonize our Milky Way galaxy. Since this should have happened several times already in the history of our galaxy, one should wonder where is the evidence of these civilizations? This discrepancy between the expectation that there should be evidence of alien civilizations or visitations and the presumption that no visitations have been observed has been dubbed the Fermi Paradox.

This photograph was taken in Wallonia, Belgium. J.S. Henrardi

Carl Sagan correctly summarized the situation by saying that “extraordinary claims require extraordinary evidence.” The problem is that there has been no single well-documented UFO encounter that would alone qualify as the smoking gun. The situation is exacerbated by the fact that many governments around the world have covered up and classified information about such encounters. But there are enough scraps of evidence that suggest that the problem needs to be open to scientific study.

UFOs, taboo for professional scientists

When it comes to science, the scientific method requires hypotheses to be testable so that inferences can be verified. UFO encounters are neither controllable nor repeatable, which makes their study extremely challenging. But the real problem, in my view, is that the UFO topic is taboo.

While the general public has been fascinated with UFOs for decades, our governments, scientists and media, have essentially declared that of all the UFO sightings are a result of weather phenomenon or human actions. None are actually extraterrestrial spacecraft. And no aliens have visited Earth. Essentially, we are told that the topic is nonsense. UFOs are off-limits to serious scientific study and rational discussion, which unfortunately leaves the topic in the domain of fringe and pseudoscientists, many of whom litter the field with conspiracy theories and wild speculation.

I think UFO skepticism has become something of a religion with an agenda, discounting the possibility of extraterrestrials without scientific evidence, while often providing silly hypotheses describing only one or two aspects of a UFO encounter reinforcing the popular belief that there is a conspiracy. A scientist must consider all of the possible hypotheses that explain all of the data, and since little is known, the extraterrestrial hypothesis cannot yet be ruled out. In the end, the skeptics often do science a disservice by providing a poor example of how science is to be conducted. The fact is that many of these encounters – still a very small percentage of the total – defy conventional explanation.

The media amplifies the skepticism by publishing information about UFOs when it is exciting, but always with a mocking or whimsical tone and reassuring the public that it can’t possibly be true. But there are credible witnesses and encounters.

Why don’t astronomers see UFOs?

I am often asked by friends and colleagues, “Why don’t astronomers see UFOs?” The fact is that they do. In 1977, Peter Sturrock, a professor of space science and astrophysics at Stanford University, mailed 2,611 questionnaires about UFO sightings to members of the American Astronomical Society. He received 1,356 responses from which 62 astronomers – 4.6 percent – reported witnessing or recording inexplicable aerial phenomena. This rate is similar to the approximately 5 percent of UFO sightings that are never explained.

As expected, Sturrock found that astronomers who witnessed UFOs were more likely to be night sky observers. Over 80 percent of Sturrock’s respondents were willing to study the UFO phenomenon if there was a way to do so. More than half of them felt that the topic deserves to be studied versus 20 percent who felt that it should not. The survey also revealed that younger scientists were more likely to support the study of UFOs.

UFOs have been observed through telescopes. I know of one telescope sighting by an experienced amateur astronomer in which he observed an object shaped like a guitar pick moving through the telescope’s field of view. Further sightings are documented in the book “Wonders in the Sky,” in which the authors compile numerous observations of unexplained aerial phenomena made by astronomers and published in scientific journals throughout the 1700s and 1800s.

Evidence from government and military officers

Some of the most convincing observations have come from government officials. In 1997, the Chilean government formed the organization Comité de Estudios de Fenómenos Aéreos Anómalos, or CEFAA, to study UFOs. Last year, CEFAA released footage of a UFO taken with a helicopter-mounted Wescam infrared camera.

Declassified document describing a sighting of a UFO in December 1977, in Bahia, a state in northern Brazil. Arquivo Nacional Collection

The countries of Brazil, Canada, Denmark, Ecuador, France, New Zealand, Russia, Sweden and the United Kingdom have been declassifying their UFO files since 2008. The French Committee for In-Depth Studies, or COMETA, was an unofficial UFO study group comprised of high-ranking scientists and military officials that studied UFOs in the late 1990s. They released the COMETA Report, which summarized their findings. They concluded that 5 percent of the encounters were reliable yet inexplicable: The best hypothesis available was that the observed craft were extraterrestrial. They also accused the United States of covering up evidence of UFOs. Iran has been concerned about spherical UFOs observed near nuclear power facilities that they call “CIA drones” which reportedly are about 30 feet in diameter, can achieve speeds up to Mach 10, and can leave the atmosphere. Such speeds are on par with the fastest experimental aircraft, but unthinkable for a sphere without lift surfaces or an obvious propulsion mechanism.

1948 Top Secret USAF UFO extraterrestrial document. United States Air Force

In December 2017, The New York Times broke a story about the classified Advanced Aviation Threat Identification Program, which was a $22 million program run by the former Pentagon official Luis Elizondo and aimed at studying UFOs. Elizondo resigned from running the program protesting extreme secrecy and the lack of funding and support. Following his resignation Elizondo, along with several others from the defense and intelligence community, were recruited by the To the Stars Academy of Arts & Science, which was recently founded by Tom DeLonge to study UFOs and interstellar travel. In conjunction with the launch of the academy, the Pentagon declassified and released three videos of UFO encounters taken with forward looking infrared cameras mounted on F-18 fighter jets. While there is much excitement about such disclosures, I am reminded of a quote from Retired Army Colonel John Alexander: “Disclosure has happened. … I’ve got stacks of generals, including Soviet generals, who’ve come out and said UFOs are real. My point is, how many times do senior officials need to come forward and say that this is real?”

A topic worthy of serious study

There is a great deal of evidence that a small percentage of these UFO sightings are unidentified structured craft exhibiting flight capabilities beyond any known human technology. While there is no single case for which there exists evidence that would stand up to scientific rigor, there are cases with simultaneous observations by multiple reliable witnesses, along with radar returns and photographic evidence revealing patterns of activity that are compelling.

Declassified information from covert studies is interesting, but not scientifically helpful. This is a topic worthy of open scientific inquiry, until there is a scientific consensus based on evidence rather than prior expectation or belief. If there are indeed extraterrestrial craft visiting Earth, it would greatly benefit us to know about them, their nature and their intent. Moreover, this would present a great opportunity for mankind, promising to expand and advance our knowledge and technology, as well as reshaping our understanding of our place in the universe.

Kevin Knuth is an Associate Professor of Physics at the University at Albany, State University of New York.

This article was originally published on The Conversation.

#science #astronomy #NASA #UFO #telescope #space exploration #extraterrestial life #Aliens #alien life

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archiveofprolbems · 3 years

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On Space Art by Xin Liu & Xin Wang

Xin Liu, Orbit Weaver, 2017. Production still of artist's performance during a parabolic flight. Image courtesy of the artist. Photo by Steve Boxell.

During the prolonged lockdown that defined much of 2020, the Xinjiang-born, New York-based artist and engineer Xin Liu juggled multiple roles. These included participating in a volunteering network that supplied PPE to medical workers in dire need of protection against Covid-19; designing an indie game, Sleepwalk (2020), which reflected on the conditions of confinement and hyper-connectivity; engineering a series of hypnotic sound experiences with her partner Gershon Dublon titled The Wandering Mind (2020), which guides the dreams of a sleeping audience with source materials organized by an AI system; and live-streaming an ambient soundscape recorded on Whitehead Island, off the coast of Maine, for the Camden International Film Festival.1

As the Arts Curator at MIT Media Lab’s Space Exploration Initiative and an artist who makes work for exhibition spaces, film festivals, and astronautical conferences, Liu’s ongoing fascination with space as a medium and destination for new art has seen her send a wisdom tooth into outer space, cultivate potato seeds that had travelled to the International Space Station, and imagine weightlessness as an intimate, “body-opening” condition. In this interview, we spoke about the past lives and expansive futures of Space Art, her unique mixture of academic and identitarian backgrounds, and the creative strategies of innovation and resistance while working at the juncture of art and technology.

Xin Wang: You’ve recently been referred to as a “famous space artist” in a panel discussion poster, which suggests that this is a solidified genre.

Xin Liu: It is a genre! If you google “Space Art,” there’s a Wikipedia page that defines it, though it’s very much about visual artists depicting the vision of space exploration, like images of Martian colonies, weightlessness, spaceships, etc. It was also called Astronomical Art, with notable artists such as Chesley Bonestell. These artists really tried to define the aesthetics of space, which even changed the way we would later color actual scientific images captured through different telescopes. Even now, if you look at NASA’s art programs, that’s still basically the main concept. Slowly it diverged into art in space, or art that uses space and environmental textures for creation, experimentation, and storytelling.

For me, Space Art conceptually connects more to Land Art in the seventies; the questions they were asking—regarding spatial-temporal dimensions and the way we engage with geological transformation—are more related. However, there is this jump in the Space Art medium from astronomical paintings right away to “art in space.” It is a gap in our understanding of Space Art; in my position as the Space Art curator at MIT, I have made sure to take into account Land Art, science fiction, and so on, in lectures.

XW: What questions do you want to ask with your Space Art?

XL: First of all, the duality in our perception of the world: being a human being walking, eating, sleeping, drinking, and laughing on this planet; and on the other hand, knowing that we exist on a gigantic rock spinning around another hot rock in endless space. The epistemological jump is exciting but also problematic when we distance one from the other. People talk about science versus culture as if they are the polar opposites. I’m trying to reconcile the two views of the world and find places to live in-between. My other interest has more to do with the body, our sensations, our death, and the cycles of life and materials.

XW: Your works have always struck me as poetic—you sent one of your wisdom teeth into space in Living Distance (2019), which was inspired by childhood folktales and executed with robust engineering. But the whole debate around the idea that culture and science are antithetical has a long history. Susan Sontag wrote about it in the sixties, for example; what are you seeing in terms of new manifestations of, and challenges to, that tension?

XL: The philosopher Yuk Hui has proposed the concept of cosmotechnics, which argues that science and technology aren’t objective but are born of human cultures. One of my current projects, Unearthing Futures, is a collaboration with the Peruvian artist Lucia Monge, the International Potato Center in Lima, and the International Space Station (ISS).2 We are interested in potato history as human history; native to Peru, the potato’s journey becoming one of the most widely grown crops in the world mirrors colonial history. As we set foot and grow crops beyond the earth bond, one option here is to engineer the perfect potato that survives all conditions, while the other is to trust the possibilities of biodiversity, where a consortium of diverse species that are mutually dependent yields a higher chance of survival in extreme environments. Both are questions of science and technology, but at the same time they reflect philosophies—ones about how we survive.

We selected six varieties of native Peruvian potatoes with different characteristics, sent the potato seeds to the ISS to spend a month in microgravity, and exposed them to environment stressors such as radiation. The project has not grown potatoes in space, but it’s a significant step to understanding how environmental stressors affect thesis seeds. Having harvested the first generation in our respective studios, we plan to grow multiple generations and increase the numbers that we can process. Maybe in the fourth or fifth generation we can cook them and use them in workshops that involve the general public (we are working with public elementary schools in Portland) to think about the possibilities of food and agriculture in space exploration. Space potatoes are the protagonists in our stories and would facilitate these dialogues.

XW: When we were reviewing proposals for Sojourner 2020, an open call for artworks to be sent into low earth orbit by the MIT Media Lab Space Exploration Initiative, there were equally visible tendencies to flatten the crossover between art and technology into very gimmicky projects. In your position as both curator and artist working in this increasingly hyped juncture of art and tech, what are some of your goals and challenges?

XL: With the dropping costs of space launches and privatization, we are entering the New Space Age. Space Art is truly at the frontier now (no pun intended). There are many amazing art practitioners I’ve been able to invite to MIT and imagine together what this practice can be. The artist Agnes Meyer-Brandis, for example, created The Moon Goose Colony, where she trained geese on planetary science and different flight patterns to prepare them for the Moon.3 She even incubated and hatched the eggs herself. In 42-The Large Meteor T-R-A-P (2014), she uses electronic magnetic devices to guide the movement of meteorites, which can be viewed as a planetary defense system. In fact, the first planetary defense systems launched by NASA (the Double Asteroid Redirection Test) this past year also had to do with devices latching onto the meteorites to change their course of movement. I really like projects that are ambitious, beautifully executed, and which explore scientific possibilities as well as artistic ones. Unapologetically inserting yourself into other domains is also something I’m passionate about.

XW: What are some examples of such insertions?

XL: I recently had a conversation with the researcher Weng Jia, who looked into the detailed history of weather satellites beyond the pragmatics of weather forecast—itself a form of weather control that generates state power. It’s important to understand that history, but at the same time we can ask, as cultural producers, what now? We can either involve public engagement and sign petitions to request open access, or we can learn from the hackers—there are so many amateur enthusiasts who eavesdrop on state-owned radio signals, and through listening we are able to understand so much already. During the pandemic, my partner Gershon Dublon and I have tinkered with software-defined radio. Using just a tiny, 20-dollar USB dongle with an antenna we built from our clothing wires, we could receive the signals from retired National Oceanic and Atmospheric Administration (NOAA) weather satellites as they pass through the sky.

Even before the pandemic, my partner was looking into personal monitoring of air traffic, as most aircrafts have to broadcast their locations after reaching 18,000 ft. This was a fun plane-tracking activity at home. But later on we were put in touch with the Standing Rock Sioux tribe, who were protesting the Dakota Access Pipeline encroaching their territories. They were being illegally harassed and even sprayed with unknown chemicals by aircraft flying over their encampment, but couldn’t track the perpetrators. We helped them set up the aforementioned system using a computer, a 20-dollar dongle, and electrical metal wires, with which they were actually able to “see,” ID, and track the aircraft. Using that data and US Freedom of Information Act (FOIA) requests, the water protectors were able to pursue their harassers and hold them accountable. Is it art practice? I think it’s important and exciting to examine the “wall”; there’s no wall that’s perfect—there are always cracks. You can find things between the breaks and slowly percolate, and, in a way, take back those powers—I found those processes most exciting.

XW: I think this is a powerful approach that counters the general pessimism towards big tech, technocratic states, and surveillance to the point that people don’t even want to think about the possibilities of cracks.

XL: But that’s a facade, and I don’t know who marvelously crafted it. A lot of these things, such as the radio, are not so complicated. Given a week and the internet, most people can figure it out; it’s not rocket science. You know who is most interested in amateur radio nowadays? The fifty-plus generation, sometimes grandpas. There is a big community in Staten Island in New York. However, in the arts, these systems and disciplines are rendered unfathomable, which prohibits further investigation. That’s the problem.

XW: When you were speaking about “the cracks in the wall” earlier, I had a very dark thought—in the future, planetary warfare will look drastically different and be much more deadly than the wars currently taking place on Earth.

XL: Future wars may not be quite so physical as we imagine—the virus is a powerful model for what could happen. It shows how fragile and resilient humans are; cyberattack, trade wars, geoengineering manipulation of nature—these are all struggles on different planetary scales, and we have to constantly self-educate as citizens and decode what the decision makers are actually saying.

XW: You received your undergraduate training at Tsinghua University, which is known for its rigorous focus on scientific training and as a place that has groomed many of China’s top technocratic leaders. It’s also considered the Chinese counterpart of MIT, where you completed a graduate program. How do those experiences compare and inform your trajectory?

XL: When I was in Tsinghua, I studied mathematics, physics, and mechanical engineering; my degree was in precision instruments. Nowadays I still practice them in my sculpture in its manufacturing and fabricating processes. It’s a craft. I later went to Rhode Island School of Design (RISD), not because I wanted to be an artist, but out of a sad realization. In China, we separated art and science education since high school, and my liberal arts education was limited.

It was a selfish desire to study fine arts after college just to become a “complete” human being. I am very grateful that my parents didn’t disapprove this decision. At the time I told myself that I’d probably still end up working for Google and Microsoft; I had interned at both places during graduate school, thinking that’s how I would make a living eventually. But those two years were transformative and gave me an absolutely new way of looking at the world. Even graduating with an MFA from RISD, I still couldn’t commit a hundred percent to being a professional artist, as it is really difficult financially. I’m a practical immigrant. I had to figure out a way to stay in the country and feed myself. Then I went to MIT, because it was fully funded and I had the luxury to do research; after another two years in school, I decided that I wanted to work freely, and “artist” is the title that offers the most freedom.

XW: Do you still believe that?

XL: I do. If you tell people you are an artist, whatever you do doesn’t surprise them as much. It’s harder to talk about sending a tooth to space as a physicist.

XW: I’m struck by the way you describe gravity as a “momentum of feelings” on your website.

XL: That’s something I was thinking about when I first experienced weightlessness in 2017, during a parabolic flight. The plane literally free-falls in the sky, and in reference to the cabin, everything inside the plane is weightless. I had a bit of a performance background in dance. The experience was shocking: there was no “free from gravity”—gravity is always there. It was just everything falling together. The experience was less about me floating or flying than about the ground beneath me dropping. It’s not liberating in the way that you are accelerating and going up, which is what we associate with space exploration probably, but rather a kind of letting-go and descending. It was an eye-opening—body-opening—experience for me, and a bitter-sweet moment as well.

XW: Speaking of bodies and embodiment, do you find this excessive attention to—often performances of—an artist’s identity shows up more or less or differently for you, given the curious juncture of disciplines and identities you inhabit?

XL: It depends on who is seeing me. The tech aspect of me can seem alarming to people who are used to traditional practices, and in the so-called media/tech/science art world, gender might manifest more. The audience decides who I am. My name reads as gender-neutral in both English and Chinese. Sometimes people assume I’m a man initially, because I’m working with technology; but a bit more engagement with the work might compel one to realize that I could be a woman, because of the way I deal with technology. Still deeper into it, you might realize I’m Asian.

Another interesting aspect comes from the fact that I don’t just participate in art events; I also present my works at the International Astronautical Congress (IAC), where it’s just pleasing to see my portrait—that of a young Asian woman—next to attendees that are largely from different demographics. And I enjoy that—inserting myself in different systems. It’s not just gender, but also geographic. I am an outlier in many ways—I went to a military-affiliated high school, so the instinct to fit in was strong growing up. But here, as people of color and women, we naturally stand out and have more identities. It could be tiring but it’s also our power—meaning that we can potentially empathize with more people. People like you and me—when we talk about America in a positive light in China or criticize the Chinese government, we are perceived as brainwashed by Western liberalism; but when we talk about Chinese companies like WeChat positively here, or the effective Covid-19 responses and technological innovations in China, we’d be considered brainwashed in the other direction too.

XW: I always feel that exposure to different systems of brainwash leads to utmost clarity. What do you think the future of space art will be, or what you hope it could be like?

XL: I think it will mature like digital art, bio art, internet art, AR/VR art—all these sub-domains. I read extensively on space policies, which obviously figure prominently on many nation states’ agendas. At the IAC conference in 2020, eight national space agencies just signed the Artemis Accords, which is an international agreement on the principles for corporations and civil explorations for the moon, Mars, comets, and asteroids. Particularly notable is the encouragement and protection for private entities to participate in the future of space exploration, and its effect on commercial activities will be significant; even the ISS is going through a commercialization process already. Space will become more commercial and privatized; it will engender more conversations and force us to be involved and investigate the industry.

XW: What’s your favorite Space Art piece?

XL: I was struck by Ilya Kabakov’s The Man Who Flew Into Space From His Apartment (1985) when I first knew about it. I have been (and am still) confined in my apartment due to the pandemic. It is the absolute desire to break the ceiling and get out. Though both are heading towards outer space, the Soviet campaign in space exploration and a personal desire to leave, to be free, cannot be more different. In fact, one is defeating the other.

_____________________

Xin Liu (b. 1991, Xinjiang/China) is an artist and engineer. She is the Arts Curator in the Space Exploration Initiative in MIT Media Lab, a member of New INC in New Museum, and a studio resident in Queens Museum. She is also an artist-in-residence in SETI Institute and the recipient of numerous awards and residencies.

Xin Wang is a curator and art historian based in New York. She is currently planning an exhibition that explores Asian Futurisms for The Museum of Chinese in America, New York. While pursuing her PhD in art history at the Institute of Fine Arts, New York University, she’s also been conducting a series of public zoom webinars on topics of technology, new media, and Asian American perspectives for the Whitney Museum of American Art since spring 2020.

Source: https://www.art-agenda.com/features/372727/on-space-art

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shirlleycoyle · 3 years

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The Cosmologist Working to Preserve the Night Sky for the Future

As 2020 draws to a close, Dr. Aparna Venkatesan is struck by how her personal experience of grief—set against a year of collective mourning—has changed something fundamental in her life: the way she looks at the Moon.

Venkatesan, a cosmologist at the University of San Francisco, lost her father in March; a man she described as “my lifelong best friend” and “one of my greatest allies” in a call.

“I think all girls should have a dad like that,” she said.

With international borders locked down in response to the pandemic, Venkatesan was not able to mourn her father alongside his community in India, where she grew up bouncing from city to city as the only child of enterprising parents. But though the wound is deep, she has found solace in the lunar cycle, which she calls her “grief calendar.”

“My father passed at New Moon,” she said. “As somebody who is a pretty rational scientist, the Moon cycles have become enormously important this year for me. Every time there's a New Moon, it’s like: ‘I'm eight lunar cycles past when I lost this beloved friend; I'm nine lunar cycles past.’ It's become huge.”

“The Hindu death rites happen monthly in the first year after they pass away—it's a lunar calendar,” she added. “In a way, that's brought me back to my culture.”

For Venkatesan, the human relationship to the Moon—and to the night sky as a whole—is enriched by the cross-cultural diversity of perspectives on the meaning and value of the expanse beyond Earth. Though she is an expert in the otherworldly phenomena of the early universe, an era that is distant in time and space, Venkatesan also wants to protect our collective bond with the skies close to home.

To the dismay of many astronomers and skywatchers worldwide, the deployment of satellites in mega-constellations, such as SpaceX’s Starlink, creates bright scars across the night sky due to the sunlit glare of the spacecraft. In addition to this light pollution in orbit, the Moon is getting more visitors: NASA hopes to land humans there this decade as part of its Artemis program; China has placed three missions on the lunar surface since 2013, and India and Israel recently attempted Moon landings that ended in crashes.

“By 2025, near-Earth space, the night skies, and the Moon will be permanently altered in my opinion,” Venkatesan said.

This is profoundly troubling to her not only from a scientific point of view, but because she is an ardent defender of marginalized communities, especially Indigenous peoples, whose astronomical traditions are at risk from busier skies. In an article published in Nature Astronomy last month, Venkatesan and her colleagues propose that we need “a radical shift” towards “the view of space as an ancestral global commons that contains the heritage and future of humanity’s scientific and cultural practices.”

For Venkatesan, the idea of space as an ancestral realm has a special relevance this year, as she looks at the New Moon in a new way. But it is also a natural progression of her fascination with, and respect for, the codes and secrets of the universe, which was sparked in childhood.

“I always loved math, as the universal language,” she said. “I also really loved the night skies, despite growing up in extremely congested, polluted, major cities in the tropics.”

As a teenager, Venkatesan applied to Cornell University to pursue her budding love of space, and remembers the suspense as she waited for the response (her acceptance letter was eventually delivered by telegram). The adjustment to life in small-town New York had some initial rough patches—Venkatesan missed her parents, and wished she’d listened more to her mother’s cooking tips—but she cherished the overall experience and her family’s pride when she became the first woman to receive an undergraduate degree in astronomy at the university.

“When my father came to my graduation at Cornell, he cried,” Venkatesan recalled. “He was like: ‘Look, I could spend years in these libraries.’ He loved Cornell's libraries. I had very encouraging parents and I really commend them, given what a conservative society we are.”

Under the guidance of her advisor Steve Squyres, a prolific planetary scientist, Venkatesan spent much of that first degree combing through observations of Venus taken by NASA’s Magellan orbiter, which studied the planet from 1989 to 1994. The work was thrilling, as sometimes she would be the first human ever to behold a part of Venus as new data flowed in on her overnight shifts.

When she arrived at the University of Chicago as a graduate student, she shifted gears to focus on big cosmological questions: When were the first stars born? What is dark matter? What is the precise source of all the elements?

“I was eager to work in cosmology because I had gone to Cornell to do that, but ended up, you know, working on literally the nearest planet,” Venkatesan said. “It was time to go back to the other end of the universe.”

With the help of dedicated mentors like astronomer Jim Truran, who she said taught her an “integrative approach” to cosmology, she learned to appreciate the whole spectrum of evidence about our cosmic origins, from the light of long-dead stars to the elements that make up our bodies.

“There are some lovely puzzles in lithium, calcium, carbon, and titanium that we don't understand, when we look at the element abundances in the oldest stars in our galaxy, or even just in galaxies,” Venkatesan said.

“Look, I'm never going to get tired of looking at ancient light,” she continued. “It is a visceral thrill to say: ‘Oh, my God, when light left this galaxy, cyanobacteria hadn't even begun on Earth or the oceans, or maybe the Earth wasn't even around.’ I'm never gonna get tired of that. But the elements are here, in a very real way. We are the evidence.”

After earning her PhD in Chicago, Venkatesan served as a research associate at the University of Colorado, Boulder, for a few years, before becoming the first female professor of physics at the University of San Francisco. Since 2012, she has also participated in the Arecibo Legacy Fast ALFA (ALFALFA) collaboration, which involved accompanying students to study at Puerto Rico’s Arecibo Observatory.

Venkatesan under Arecibo’s dish. Image: Aparna Venkatesan

Like so many people who loved Arecibo, Venkatesan was heartbroken when it collapsed earlier this month after multiple cable malfunctions. She has countless fond memories of the iconic observatory: celebrating the 21st birthday of a student during an observation shift, listening to nocturnal frog calls in the dense misty foliage under the dish, or watching the Southern Cross constellation illuminate the Caribbean skies in the crepuscular hours before dawn.

“The science of working there is just unparalleled and I loved the people of Puerto Rico, both the observatory staff and the people beyond the observatory,” Venkatesan said. “I also really loved the scientists who live there year round. I mean, these people were on-the-ground geniuses: they could listen to the hum of the telescope and tell you which panel or receiver was off.”

“All observatories have this magical mystical side to them—you can't help but feel it, being out under this glowing sky, taking data—but Arecibo had it more than most,” she added.

For Venkatesan, Arecibo is one of many beloved elders that we lost this year. As a busy mother of two teenagers, she is juggling new school and work challenges like so many during the pandemic, but she has managed to find moments to work through the grief by remembering loved ones lost, and cherishing those who remain.

During our call, she talks about many of her mentors and inspirations over the years, heaping praise and gratitude on these bright stars in a dark night. The list includes her parents, her professors, the Moon, Arecibo, and the redwood forests of California.

But an elder that sticks out in particular, at the nadir of 2020, is blues musician Blind Willie Johnson, who suffered racism, poverty, and illness until his death in 1945. Venkatesan has an eclectic musical taste and a passion for singing across genres, but she is particularly keen on Johnson, whose haunting voice reverberates with the transcendent sorrow that shaped his life.

As she often tells her students, Johnson’s song “Dark Was the Night” is on the Voyager Golden Record, a repository of sounds and images from Earth carried by NASA’s twin Voyager probes, which have passed into interstellar space. On this Monday, the winter solstice and the darkest day of a harrowing year, the song has special resonance.

“The blues is so beautiful,” Venkatesan said, “it's actually left the solar system.”

The Cosmologist Working to Preserve the Night Sky for the Future syndicated from https://triviaqaweb.wordpress.com/feed/

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evermist-coop · 7 years

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Portishead - Dummy

So I’m going to start by saying this review is long overdue. Not just from a production standpoint but from a personal one. There’s very little over the course of my life that hasn’t changed. Things I used to hold near and dear to my heart and got bored of, or things that I despised in my youth that now I begrudingly accept or even enjoy.

Except for Dummy.

I’ve been born in this magical age where the loss of data, and most importantly music is nigh impossible, every song made over the course of my life that has ever existed in digital media has been shared, and will continue to be shared for what is hopefully the rest of time. Dummy is my induction to this era. I have fragments of memory from my earliest days of this album being played to put me to sleep. Whether to drown out the ambient city noises or parents fighting or laughing in the next room it didn’t matter. Dummy was there to soothe me, encompass me in it’s presence and lay me to rest. Now it is time to share Dummy. Human inspiration doesn’t come from answers. Answers satisfy, their existence means that they can be accepted. What drives us to push new ground is questions, about ourselves, the world around us, the meaning of things. Listening to it from so young meant I never needed to know the name of this album. I’d just ask my dad to play the bedtime one and he had the answer to my question. As I got older and stopped needing the music to sleep I forgot about the album. Until life became more difficult in different ways, and I begged for something to put me to sleep again. Rediscovering this album began the process of discovering myself, and settling into someone I can be proud of again. It wasn’t listening to this that fueled my love of music, but trying to find the answer to a long forgotten question.

In order to explain the album I feel I have to talk about the genre as a hole. Trip-hop is not just ambience, it can’t be explained by a focus on certain instruments or vocals or a time signature. Trip hop is by nature encompassing. It’s the electrifying sensation of a gentle caress, the smallest existence of space on your flesh becomes the entirety of your focus. Dummy isn’t an album that you turn on while you work, do dishes, walk, or fuck. It’s the centerpiece. No matter the backdrop the sheer depth of the album requires telescopic attention to detail, a disconnect from the rest of reality while the beating of it’s heart occupies your head space. It could have been a sweet little pop number that you listen while the world beats around you. Instead it lingers like a half remembered dream. If any genre could claim to have an encompassing ideal, a single entry point that could be universal, where anyone could take their own journey down it’s Roads with a single unified entry point, I would call Portishead’s Dummy that ideal for triphop. In digressing from my usual reviews, there is no single song on this album that I could say with any degree of legitimacy is better than the rest. No Wandering Stars that are worth the listen to while you power through an hour of entertainment. It is a beast that must be tackled from beginning. As you sit and listen, ponder each one, listen for details over the course of it, and see if you come out of the end feeling the same way about music. It’s a Fire provoked by thought, that changes the way you feel about music as a whole. Come into the experience blind, and walk out of it seeing light anew. Even after 20+ years of listening to this, and knowing it as intimately as I know myself, I still find details that I didn’t notice before. This is, and always will be, my album of all time. If I would ever let myself be forced to only listen to one song off the album ever again, it would be Roads, but I’m taking death before that. ((For bonus, check out the Roseland City Live recordings of some of these songs, because you can never go wrong with adding an entire orchestra for accompaniment.))

https://open.spotify.com/album/3539EbNgIdEDGBKkUf4wno

#portishead #Jedi Song Tricks #Album #review #music #love #Dummy #I could talk about it for weeks

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pagelangston8-blog · 5 years

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shenzhenblog · 5 years

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IBM's AI loses debate to a human, but it's got worlds to conquer

The tech was “surprisingly charming and human-sounding,” and it’s about to head out into the real world.

The subject under debate was whether the government should subsidize preschools. But the real question was whether a machine called IBM Debater could out-argue a top-ranked human debater.

The answer, on Monday night, was no.

Harish Natarajan, the grand finalist at the 2016 World Debating Championships, swayed more among an audience of hundreds toward his point of view than the AI-powered IBM Debater did toward its. Humans, at least those equipped with degrees from Oxford and Cambridge universities, can still prevail when it comes to the subtleties of knowledge, persuasion and argument.

It wasn’t a momentous headline victory like we saw when IBM’s Deep Blue computers beat the best human chess player in 1997 or Google’s AlphaGo vanquish the world’s best human players of the ancient game of Go in 2017. But IBM still showed that artificial intelligence can be useful in situations where there’s ambiguity and debate, not just a simple score to judge who won a game.

“What really struck me is the potential value of IBM Debater when [combined] with a human being,” Natarajan said after the debate. IBM’s AI was able to dig through mountains of information and offer useful context for that knowledge, he said.

It was the second time IBM Debater took on humans in public, though it’s taken part in dozens of debates behind Big Blue’s walls. In the first IBM Debater competition, the AI defeated one human debater soundly while losing a closer competition with another. This time, though, the human opponent was tougher — indeed, IBM researchers involved in the years-long project expected their AI would lose.

Computer persuasion

IBM Debater lost, but there’s no question it won in a way: Listening to it, you evaluate what it’s saying, not just that it’s a computer saying something. The machine marshaled its argument, broke that down into a few points and backed them up with data from various studies. It wasn’t perfect, but it was on point.

And, weirdly for an AI, it told us how Homo sapiens ought to behave.

“Giving opportunities to the less fortunate should be a moral obligation for any human being,” IBM Debater said.

In the debate, each side had 15 minutes to prepare — though only IBM Debater has the advantage of being able to draw upon 10 billion sentences’ worth of publications from news articles and academic research. Each side took turns making its case, rebutting the other and then presenting a closing argument.

The debate is scored based on how many people change their minds. Before the debate, 79 percent agreed with the position in favor of preschool subsidies, the stance IBM Debater argued for. But afterward, the audience support dropped to 62 percent.

In an age in which Apple’s Siri, Amazon’s Alexa and the Google Assistant listen to our questions and answer in human-sounding voices, it’s easy to forget how remarkable it is that we can converse with computers. IBM Debater goes a step beyond, speaking for minutes.

“She was surprisingly charming and human-sounding,” said John Donvan, host of the debate moderator of Intelligence Squared Debates, which runs debates and broadcasts them through a radio show.

Don’t expect to run something like Project Debater on your laptop anytime soon. It ran mainly on a powerful server with 28 processing cores and a whopping 768GB of memory — roughly 50 times that of a high-end laptop. It was supported by a quartet of servers, each with 64GB of memory and 2-terabyte hard drives packed with text.

Preschool subsidies

IBM Debater argued in favor of the view that we should subsidize preschools, and Natarajan argued against it.

In Debater’s view, preschools “carry benefits for society as a whole. It is our duty to support them.” Good preschools mean kids — especially poor kids — do better in life.

Natarajan countered that preschool subsidies are “little more than a politically motivated giveaway to members of the middle class … and not to the individuals who are most underprivileged.” He also poked holes in Debater’s assumptions, for example that a subsidy will meaningfully improve education for the poor.

Debater showed improvements over its 2018 debate. One new trick up its sleeve was the ability to offer a parallel argument — in this case that subsidizing health care can be beneficial. Another was improved rebuttal skills. After Natarajan argued that some kids might not benefit from immersion into the potentially competitive world of preschool at age 3 or 4, IBM grasped that view and took issue with it: “My opponent argued that preschools are harmful,” it said.

“We were working very hard since June to improve the system,” said Noam Slonim, the Project Debater principal investigator at IBM Research. Debater’s source material — academic publications and news articles — also have been expanded with another year’s worth of data to the end of 2018.

Most challenging contest so far

The competition was the most challenging yet for IBM’s AI.

Natarajan “is at a different level compared to the debaters we faced so far,” said Ranit Aharonov, IBM’s manager of Project Debater. “He’s the most decorated debater in the history of university debate competitions with the world record in the number of victories.”

The event, at IBM’s Think conference in San Francisco, is IBM Debater’s last big debate. “Debater is nice, and it’s good to showcase, but we should be focusing on how to take that technology and make something that’s commercially viable,” Aharonov said. “We are at the stage where we’ll finalize the first use case we’ll work on.”

That could be something like helping a company understand the views of its employees or customers, or helping the news media or governments engage people in discussion about contested issues, she said.

That’s because the technology behind Project Debater is all about the messiness and nuance of the real world we humans live in, not the black-and-white realm of games.

“We are going out of the comfort zone of AI into territory which is more gray,” Slonim said.

Facebook acquires AI startup: GrokStyle is here to help you shop.

CNET Magazine: Check out a sample of the stories in CNET’s newsstand edition.

Here’s the magnificent last view NASA’s Kepler Space Telescope ever saw: The prolific planet finder went to sleep for good last year, but captured one final view before saying goodnight.

ESA Mars rover named after Rosalind Franklin, brilliant DNA pioneer: Franklin, who died in 1958, helped us understand the molecular makeup of DNA and RNA.

IBM’s AI loses debate to a human, but it’s got worlds to conquer was originally published on Shenzhen Blog

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ntrending · 6 years

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In the hunt for aliens, satellites may light the way

New Post has been published on https://nexcraft.co/in-the-hunt-for-aliens-satellites-may-light-the-way/

In the hunt for aliens, satellites may light the way

The Earth is expanding, satellite by satellite, every rocket launch carrying a piece of the planet’s crust into orbit. Should this incidental geoengineering venture continue, it will reshape our planet’s profile as seen across even interstellar distances—giving our smooth sphere a noticeable bulge.

If we’re puffing up our planet, other civilizations could be doing the same to theirs, producing a ring of satellites that we might be able to spot with telescopes we have today. That’s according to Hector Socas-Navarro, an astrophysicist at the Instituto de Astrofísica de Canarias in Spain, who gave a talk on the topic at NASA’s Technosignatures Workshop in Houston last week. Scientists have long speculated that fantastical sun-sized structures might betray the presence of technological aliens, but while a mega-solar panel blocking a distant star is theoretically easy to spot, such notions remain squarely in the realm of science fiction. Thought experiments like Socas-Navarro’s, however, show that now, equipped with better telescopes than their predecessors, researchers are taking searches for planet-level changes more seriously.

Socas-Navarro realized that one planet-scale project in particular should have a specific and visible effect. Imagine a world something like Earth but a few hundred years ahead, technologically speaking. In this world, the alien military has launched GPS satellites to help with navigation. Alien NASA and alien Google have also launched countless weather and mapping satellites to deliver real-time feeds of the entire planet. Many of these satellites sit in special spots, geosynchronous and geostationary orbits, where they move in lockstep with their planet, letting them monitor the same area all the time. Fill in those special orbits and you get a thin cylinder ringing the planet, one that, when it passes between its star and an observer (like us), casts a slightly different shadow out into space than the naked planet would alone. When that shadow sweeps by the Earth, planet-hunting satellites like the aging Kepler and newly functional TESS could witness the alien star dimming in a specific way.

Socas-Navarro published preliminary simulations in The Astrophysical Journal in March showing what that dimming would look like to modern telescopes if we were to watch such an Earthlike planet about ten light-years away. A satellite ring as thin as ours would be too sparse to see, he concluded, but Kepler could spot one about a billion times denser—a radical, but not impossible change that we could pull off in 200 years if launches continue to grow at current rates.

Plenty of people are already studying these stellar flickers, searching for something similar: a planet with natural rings. “It makes for a tricky transit, a tricky shadow,” says Masataka Aizawa, a graduate student at the University of Tokyo who found one possible Saturn cousin in 2017. He agrees that the dimming from a dense satellite belt should look unique. Natural rings spread out equatorially like a record while geosynchronous orbits form a north to south tin-can shape with vanishingly thin walls (ours currently measures just 450 feet thick), and the two geometries should cast two distinct shadows. But he still considers the paper’s suggestion, which he calls “science fictional,” a long shot. “I saw almost all of the [dimming] curves in the Kepler data, and there is no such evidence in my study,” he said.

Whether satellite-loving aliens are out there or not, running more detailed simulations of how the dimming patterns of moons differ from those of rings and satellite swarms helps all exoplanet researchers, Socas-Navarro points out. “We have to make sure we don’t misinterpret something as interesting as aliens, that we don’t mistake [them] with a natural ring or a natural moon,” he says. “If you look deeply they are different.”

While the technosignatures workshop focused on listening, not talking, Socas-Navarro’s ideas also suggest a sweeping conclusion about the nature of the first contact between two species. For decades our radio receivers and telescopes have restricted our potential pen pals to what he colorfully dubs “big brothers”—civilizations with unthinkably advanced technology. These species would be capable of engineering feats such as literally moving stars around, but recent surveys for traces of “astroengineering” have come up short.

As humanity’s capacity to observe advances, the type of civilization we can detect grows closer in nature to our own. Socas-Navarro’s satellite ring is the mark of a moderately advanced civilization just centuries ahead of us, rather than millennia. And he’s not the only one thinking along those lines. Others have proposed looking for orbital mirrors that could warm or cool a planet, something we humans have recently discussed as a potential solution to our own changing climate.

Any thought experiment about alien civilizations has to start with the only civilization we know, and compared with the technologists of the 1960s, climate change has burdened modern researchers with a more nuanced understanding of how technology can destabilize a civilization. “We are facing global problems that we didn’t have before, like global warming,” Socas-Navarro says, “so there is motivation to start global scale projects.” Based on our current experience, it’s not a big jump to wonder whether other civilizations, if they exist, have faced similar challenges—and found technological solutions.

Over the last seventy years, our machines have developed from being able to observe a civilization that controls stars to one that controls merely its own planet. And in the not too distant future, Socas-Navarro predicts, the synthesis of next-gen telescopes with the developing field of astrobiology will bring us to another tipping point. “We are not far from the transition,” he told an interdisciplinary audience of astronomers, archeologists, and anthropologists in Houston on Thursday. “In the next few decades we will be able to see ourselves at interstellar distances, and then we will become big brothers.”

Since little brothers can most easily detect big brothers, the hypothesis suggests that contact will tend to occur between species with a sizeable technology gap. Such contact between human civilizations has not turned out well for the little brother historically, but Socas-Navarro sees one potential reason for optimism.

Based on humanity’s experience with rapid development, researchers speculate that a “sustainability filter” may stop more violent species from reaching technological maturity. Expansionists that fail to check their aggressive impulses may quickly overrun their environment, triggering a technology-resetting crash, or even outright extinction.

Our current struggle to find a balance with our ecosystem suggests we could be facing just such a filter. Climate change threatens to render swaths of the planet uninhabitable by the end of the century, a blow that would derail economic and technological development. Clearing this hurdle, and finding a way for seven to ten billion people to live comfortably yet sustainably, will require that we take an active hand in managing the planet’s climate and resources. Should we reach that point, we’d be able to keep launching satellites and engage in other planet-shaping activities that could be seen from afar. By the same logic, other highly visible civilizations are also more likely to be active curators of their planets.

“They will implement changes to their planet just as a gardener will change his garden,” Socas-Navarro says.

In such a universe, most instances of first contact would be between mature gardeners and those grappling with their own unruly gardens. The likely outcome of such contact, one hopes, would be a gardening lesson.

Written By Charlie Wood

#Space

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technato · 6 years

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The IceCube Neutrino Detector at the South Pole Hits Paydirt

A single subatomic collision has opened a new door in astronomy

After 3.9 billion years of hurtling unhindered through the vast reaches of the universe, a ghostly neutrino particle died on 22 September 2017. It was annihilated when it collided with an atom in the frozen darkness two kilometers beneath the surface of the south polar ice cap.

But this subatomic particle’s death did not go unmarked. It was announced today in Science that its moment of passing—labelled neutrino event 170922A—triggered a world-wide cascade of astronomical observations using a raft of varied technologies. And these led to the first ever identification of the birthplace of a neutrino from outside our galaxy: in this case, the unimaginably violent cosmic forge of a blazar.

Blazars are incredibly bright natural sources of radio waves. They form when some of the swirling material falling into a supermassive black hole is converted into a hot radiating soup of elementary particles and then gets blasted back out into space in the form of twin jets moving at close to the speed of light. Tracing the 170922A neutrino back to a blazar known as TXS 0506+056, located billions of light years away in the Orion constellation, required the rapid coordinated response of a network of observatories around the world and in orbit above it.

The initial observation that kicked this so-called multimessenger observation campaign off was made by the IceCube detector at the South Pole. IceCube was created by using pressurized hot water to melt 86 shafts into the polar ice over a square kilometer. Before the shafts refroze, cables strung with 60 digital optical modules apiece were lowered down so that the modules sit evenly spaced every 17 meters between 1450 and 2450 meters deep. The result is a detector that encompasses a cubic kilometer of solid ice. The optical modules are sealed into basketball-sized spheres of borosilicate glass to withstand the crushing pressure, and are designed to spot the signature flashes of light that occur when a neutrino smashes into an atom in the clear ice.

Illustration: Emily Cooper

When a neutrino collides with any atom, sometimes a muon is produced—a particle that’s essentially a heavier version of an electron. When this happens in ice, the muon travels faster than the local speed of light. (Nothing can travel faster than light in a vacuum, but in ice the speed of light is about 24 percent slower, so a fast particle can outpace it.) When something goes faster than local light speed, a shockwave of photons forms, much like the way that a sonic boom is produced when a plane breaks through the sound barrier. This shockwave creates an eerie blue light known as Cherenkov radiation, and measuring the direction and intensity of the light reveals how much energy the original neutrino possessed, and where in the sky it came from.

Neutrino collisions are exceedingly rare—trillions of neutrinos from the sun stream through your body every second without so much as wobbling an electron—so IceCube has to be big for it to have a statistical chance of catching a collision before the researchers die of old age (IceCube is even bigger than it seems: as long as the resulting muon passes through the detector array, it can spot neutrino collisions that occur in the surrounding ice cap up to about 10 kilometers away). And IceCube has to be deep beneath the surface because only there is the pressure intense enough—700 times normal atmospheric pressure—to squeeze all the air bubbles out of the ice. The bubbles have to be eliminated because they would otherwise scatter the Cherenkov radiation that the detectors are looking for. For a comprehensive description of IceCube’s design, right down to the FPGAs used in the optical modules, you can read the comprehensive account that team member Spencer Klein wrote for IEEE Spectrum in 2011. That article is still au courant: since it was published “there haven’t been any major changes,” says Klein, “The optical modules are buried under a mile and a half of ice, so there’s no way to really access the hardware. There have been some very minor firmware updates.”

The biggest change since, says Klein, has been in the creation of an automated alert system. This system broadcast an alert to astronomers working around the world just 43 seconds after the 170922A event occurred. IceCube detects muon shockwaves all the time, but these are generally due to low-energy muons that are produced in the Earth’s atmosphere by cosmic rays. These background muons have a different shockwave signature than those produced by high-energy extragalactic neutrinos, but filtering them out automatically requires a detailed model of the optical properties of the specific ice sheet in which IceCube is embedded.

In particular, the ice is slightly contaminated by dust. The dust comes from two sources, accumulated over tens of thousands of years as the sheet slowly formed from surface snowfalls. One is “volcanic eruptions which produce very, very thin, but relatively dense, layers” that run throughout the ice, says Klein. The other source is regular atmospheric dust which isn’t as dense, but occurs throughout the ice: “If there’s dust in the atmosphere, some of that dust will get dragged down with the snow. That does change with time somewhat, so we have a picture of the dust content in Antarctica over the last 70,000 years.”

With experience gained from several years of operation, the IceCube team has considerably improved their understanding of their patch of ice and how the detector behaves in response. Consequently, they spun up the automated system in April 2016. “The detectors and the computer systems at the south pole look for interesting events and can automatically send out an alert when it sees that something interesting has happened. It takes a fair amount of confidence to get to that point,” says Klein. “It used to be that [a candidate event for an alert] would go to a human being, who would look at it and then send out the alert. That takes time. This alert went out in under a minute.”

The 170922A event alert, with its estimated coordinates of the neutrino’s origin in the sky, went out to astronomers running instruments which can detect gamma rays, such as those onboard the orbiting Swift observatory. Swift quickly spotted that the 170922A event coordinates matched with those of known blazar TXS 0506+056, and that the blazar was flaring in brightness. “Thanks to the automated trigger … Swift was observing within four hours of the neutrino detection,” said Jamie Kennea, science operation team lead for Swift in a press release.

As the next 14 days rolled on, more and more instruments were brought to bear on TXS 0506+056, allowing it to be monitored across a range of wavelengths from radio, through optical, all the way to x-ray. The 170922A event coincided with a period of heightened activity of TXS 0506+056, and researchers have concluded that it’s 99.7 percent likely that the detected neutrino originated in the flaring blazar. “The fact that we could tie gamma rays and neutrinos together tells us very exciting things about the particle jet,” said Regina Caputo, analysis coordinator for the satellite-based Fermi-LAT gamma ray telescope, at an NSF press conference today.

With the evidence pointing to TXS 0506+056 in hand, the IceCube researchers also checked through their complete records and found that there were between 8 and 18 previous neutrino events that hadn’t met the threshold required for sending an alert, but which likely were also produced by neutrinos streaming from the blazar.

“It’s a pretty amazing finding,” says Klein. “but more data is needed. The multimessenger campaign was based on one neutrino. It’s great to know about one [extragalactic source] but we have a ways to go before we have a systemic understanding.” The IceCube team hopes to get more data by building a next-generation array by spreading out a similar number of digital optical modules over a larger area, and adding seven more closely-spaced strings to the original IceCube array. The seven strings in particular “would allow us to do a much better job of understanding the optical properties of the ice,” says Klein, which would let them pinpoint the sources of neutrinos with even greater accuracy.

The IceCube Neutrino Detector at the South Pole Hits Paydirt syndicated from https://jiohowweb.blogspot.com

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scifigeneration · 7 years

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Cartography of the Cosmos

There are hundreds of billions of stars in our own Milky Way galaxy. Estimates indicate a similar number of galaxies in the observable universe, each with its own large assemblage of stars, many with their own planetary systems. Beyond and between these stars and galaxies are all manner of matter in various phases, such as gas and dust. Another form of matter, dark matter, exists in a very different and mysterious form, announcing its presence indirectly only through its gravitational effects.

This is the universe Salman Habib is trying to reconstruct, structure by structure, using precise observations from telescope surveys combined with next-generation data analysis and simulation techniques currently being primed for exascale computing.

"We're simulating all the processes in the structure and formation of the universe. It's like solving a very large physics puzzle," said Habib, a senior physicist and computational scientist with the High Energy Physics and Mathematics and Computer Science divisions of the U.S. Department of Energy's (DOE) Argonne National Laboratory.

Habib leads the "Computing the Sky at Extreme Scales" project, or "ExaSky," one of the first projects funded by the recently established Exascale Computing Project (ECP), a collaborative effort between DOE's Office of Science and its National Nuclear Security Administration.

From determining the initial cause of primordial fluctuations to measuring the sum of all neutrino masses, this project's science objectives represent a laundry list of the biggest questions, mysteries, and challenges currently confounding cosmologists.

There is the question of dark energy, the potential cause of the accelerated expansion of the universe, called inflation. Another question is the nature and distribution of dark matter in the universe.

These are immense questions that demand equally expansive computational power to answer. The ECP is readying science codes for exascale systems, the new workhorses of computational and big data science.

Initiated to drive the development of an "exascale ecosystem" of cutting-edge, high-performance architectures, codes and frameworks, the ECP will allow researchers to tackle data and computationally intensive challenges such as the ExaSky simulations of the known universe.

In addition to the magnitude of their computational demands, ECP projects are selected based on whether they meet specific strategic areas, ranging from energy and economic security to scientific discovery and healthcare.

"Salman's research certainly looks at important and fundamental scientific questions, but it has societal benefits, too," said Paul Messina, Argonne Distinguished Fellow. "Human beings tend to wonder where they came from, and that curiosity is very deep."

HACC'ing the night sky

For Habib, the ECP presents a two-fold challenge -- how do you conduct cutting-edge science on cutting-edge machines?

The cross-divisional Argonne team has been working on the science through a multi-year effort at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science User Facility. The team is running cosmological simulations for large-scale sky surveys on the facility's 10-petaflop high-performance computer, Mira. The simulations are designed to work with observational data collected from specialized survey telescopes, like the forthcoming Dark Energy Spectroscopic Instrument (DESI) and the Large Synoptic Survey Telescope (LSST).

Survey telescopes look at much larger areas of the sky -- up to half the sky, at any point -- than does the Hubble Space Telescope, for instance, which focuses more on individual objects. One night concentrating on one patch, the next night another, survey instruments systematically examine the sky to develop a cartographic record of the cosmos, as Habib describes it.

Working in partnership with Los Alamos and Lawrence Berkeley National Laboratories, the Argonne team is readying itself to chart the rest of the course.

Their primary code, which Habib helped develop, is already among the fastest science production codes in use. Called HACC (Hardware/Hybrid Accelerated Cosmology Code), this particle-based cosmology framework supports a variety of programming models and algorithms.

Unique among codes used in other exascale computing projects, it can run on all current and prototype architectures, from the basic X86 chip used in most home PCs, to graphics processing units, to the newest Knights Landing chip found in Theta, the ALCF's latest supercomputing system.

As robust as the code is already, the HACC team continues to develop it further, adding significant new capabilities, such as hydrodynamics and associated subgrid models.

"When you run very large simulations of the universe, you can't possibly do everything, because it's just too detailed," Habib explained. "For example, if we're running a simulation where we literally have tens to hundreds of billions of galaxies, we cannot follow each galaxy in full detail. So we come up with approximate approaches, referred to as subgrid models."

Even with these improvements and its successes, the HACC code still will need to increase its performance and memory to be able to work in an exascale framework. In addition to HACC, the ExaSky project employs the adaptive mesh refinement code Nyx, developed at Lawrence Berkeley. HACC and Nyx complement each other with different areas of specialization. The synergy between the two is an important element of the ExaSky team's approach.

A cosmological simulation approach that melds multiple approaches allows the verification of difficult-to-resolve cosmological processes involving gravitational evolution, gas dynamics and astrophysical effects at very high dynamic ranges. New computational methods like machine learning will help scientists to quickly and systematically recognize features in both the observational and simulation data that represent unique events.

A trillion particles of light

The work produced under the ECP will serve several purposes, benefitting both the future of cosmological modeling and the development of successful exascale platforms.

On the modeling end, the computer can generate many universes with different parameters, allowing researchers to compare their models with observations to determine which models fit the data most accurately. Alternatively, the models can make predictions for observations yet to be made.

Models also can produce extremely realistic pictures of the sky, which is essential when planning large observational campaigns, such as those by DESI and LSST.

"Before you spend the money to build a telescope, it's important to also produce extremely good simulated data so that people can optimize observational campaigns to meet their data challenges," said Habib.

But the cost of realism is expensive. Simulations can range in the trillion-particle realm and produce several petabytes -- quadrillions of bytes -- of data in a single run. As exascale becomes prevalent, these simulations will produce 10 to 100 times as much data.

The work that the ExaSky team is doing, along with that of the other ECP research teams, will help address these challenges and those faced by computer manufacturers and software developers as they create coherent, functional exascale platforms to meet the needs of large-scale science. By working with their own codes on pre-exascale machines, the ECP research team can help guide vendors in chip design, I/O bandwidth and memory requirements and other features.

"All of these things can help the ECP community optimize their systems," noted Habib. "That's the fundamental reason why the ECP science teams were chosen. We will take the lessons we learn in dealing with this architecture back to the rest of the science community and say, 'We have found a solution.'"

#science #astronomy #space #the galaxy...ad infinitum

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tommie-suber · 6 years

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Facebook Scandal

By Jennifer Cobbe

Allegations emerged surrounding the use of Facebook user data by a data analytics firm called Cambridge Analytica. But while they have allegedly broken Facebook’s rules, the real problem is Facebook’s business model. And it’s a model that isn't unique to Facebook. It originated with Google, which realized that the data gathered as people used its search engine could be analyzed to predict what they wanted and deliver targeted advertising, and it’s also employed by most ‘free’ online services.

This isn't just a problem with Facebook. It's a problem with the internet as it exists today.

‘Surveillance capitalism’ was the term coined in 2015 by Harvard academic Shoshanna Zuboff to describe this large-scale surveillance and modification of human behavior for profit. It involves predictive analysis of big datasets describing the lives and behaviors of tens or hundreds of millions of people, allowing correlations and patterns to be identified, information about individuals inferred, and future behavior to be predicted. Attempts are then made to influence this behavior through personalized and dynamic targeted advertizing. This is refined by testing numerous variations of adverts on different demographics to see what works best. Every time you use the internet you are likely the unwitting subject of dozens of experiments trying to figure out how to most effectively extract money from you.

Surveillance capitalism monetizes our lives for their profit, turning everything that we do into data points to be packaged together as a profile describing us in great detail. Access to that data profile is sold on the advertizing market. But it isn’t just access to our data profile that is being sold – it’s access to the powerful behavioral modification tools developed by these corporations, to their knowledge about our psychological vulnerabilities, honed through experimentation over many years. In effect, through their pervasive surveillance apparatus they build up intricate knowledge of the daily lives and behaviors of hundreds of millions of people and then charge other companies to use this knowledge against us for their benefit.

And, as increasing numbers of people are realizing, surveillance capitalism doesn't just benefit corporations. It benefits political organisations as well – shadowy ones like Cambridge Analytica, yes, but also the mainstream political parties and candidates. The Obama campaign of 2008 is often described as the first ‘big data’ campaign, but it was in 2012 that his team truly innovated. The Obama team’s operations were sophisticated enough that they were able to target voters that the Romney campaign, by their own admission, didn’t even know existed. Their use of analytics-driven microtargeting allowed them to run a highly effective digital campaign and set an example which has been followed repeatedly since.

Today, tools like Facebook’s Custom Audiences and Lookalike Audiences, which allow advertisers – including political organisations �� to upload lists of people, match them with their Facebook profile, filter in the profiles of similar people who aren’t on their list, and target them all, mean that political campaigns can greatly extend the reach of their carefully-crafted messaging.

As Zeynep Tufekci, a professor of sociology at the University of North Carolina, says, if twentieth century political targeted campaigns had magnifying glasses and baseball bats, those of the twenty–first century have acquired telescopes, microscopes and scalpels in the shape of algorithms and analytics. Campaigns can deliver different arguments to different groups of voters, so no two people may ever see the same set of adverts or arguments. This takes political campaigning from being a public process to being a private, personalised affair, helped along by access to the apparatus of surveillance capitalism.

Facebook has conducted its own research on the effectiveness of targeted political messaging using its platform. In the 2010 US midterms it found that it was able to increase a user’s likelihood of voting by around 0.4% per cent by telling them that their friends had voted and encouraging them to do the same. It repeated the experiment in 2012 with similar results. That might not sound like much, but on a national scale it translates to around 340,000 extra votes. George Bush won the 2000 election by a few hundred votes in Florida. Donald Trump won in part because he managed to gain 100,000 key votes in the rust belt.

And in countries like the UK, where elections are often decided by relatively few marginal constituencies in which political parties focus their efforts, small numbers matter – one study of last year’s election suggest that the Conservative Party was just 401 votes short of an overall majority. Accordingly, in 2013 the Conservatives hired Obama’s 2012 campaign manager, and both the Vote Leave campaign and the Labor Party have boasted about their data operations. The Information Commissioner’s Office, which oversees data protection and privacy regulation in the UK, is investigating the use of these practices here. The new EU General Data Protection Regulation, when it comes into force in May, promises to provide something of a brake.

But there's also a third group who benefits from the troves of data that surveillance capitalism corporations have gathered about the minutiae of the daily lives of billions of people – the state. The Snowden revelations in 2013 about GCHQ (UK's Government Communications Headquarters) and the (US National Security Agency) NSA’s activities made headlines around the world. Much of the focus was on programmes which involved, among other things, weakening encryption standards, installing backdoors in otherwise secure networking equipment, and placing interceptors on internet backbone cables so as to siphon off the data passing through. These programmes rake in billions of records every day, with GCHQ’s stated aim being to compile a profile of the internet habits of every user on the web.

There was, however, another element that was largely overlooked – data sharing between surveillance capitalism and state security and intelligence agencies. In the US, tech companies have long been forced to hand over data about their users to the NSA. When Yahoo refused, they were threatened with a $250,000 fine, every day, with the fine doubling every week that their non-compliance continued. Faced with financial ruin, they acquiesced. In the UK, the Investigatory Powers Act, commonly known as the “snooper’s charter”, grants the security and intelligence agencies legal authority to acquire personal datasets from technology companies in bulk, and the Government is exploring an agreement with the US that would give British intelligence agencies better access to these databases.

These are concerning surveillance practices that raise difficult questions about the relationship between the citizen and the state. And since 2013 these questions have been articulated by many – not least by the European Court of Justice (ECJ), which ruled in 2016 that indiscriminate communications data retention is incompatible with a free and democratic society. This led to the Government's recent consultation on revisions to the parts of the Investigatory Powers Act that allow the Government to require ISPs to retain records of the browsing history of every user in the UK and provide them to security and intelligence agencies, police, and a range of other public authorities upon request and without a warrant or other direct judicial oversight. A challenge brought by Privacy International to the bulk personal dataset powers contained in the Investigatory Powers Act was referred to the ECJ in September

Surveillance capitalism – with smartphones, laptops, and the increasing numbers of ‘internet of things’ devices making up its physical infrastructure, watching and tracking everything we do, and the public as willing participants – increases the capacity of corporations, political organisations, and the state to track, influence, and control populations at scale. This is of benefit to those corporations, political organisations, and state agencies economically, politically, and in pursuit of the increasingly nebulous demands of ‘security’. This is how the internet of today has been built. Not for us – for them. This is the future that we've sleepwalked into. We need to look beyond Cambridge Analytica and Facebook. It’s time for a wider debate about the role of surveillance in our increasingly digital society.

[Jennifer Cobbe is the co-ordinator of Cambridge University's Trustworthy Technologies strategic research initiative, which researches trust, computer and internet technologies.]

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shirlleycoyle · 5 years

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Satellites Are Quietly, Constantly Watching Us

Ziya Tong is the author of ‘The Reality Bubble,’ a groundbreaking and wonder-filled look at the hidden things that shape our lives in unexpected and sometimes dangerous ways. This is excerpted from that book.

It was obvious that the dot on the map had stopped moving, but it was some time before people realized that the dot on the map had died. That dot was Michael Hall, a cyclist in a 5,500- kilometer endurance race being watched online by a community of “dot watchers,” fans who kept track of the cyclists along their thirteen-day route from Fremantle to Sydney, Australia.

Each dot had an athlete’s nametag, and it wasn’t unusual for them to pause here and there, when the athletes stopped to rest, take meal breaks, or go to the bathroom. The GPS live trackers were on board the bikes to ensure that cyclists didn’t cheat, while also providing the fans with live coverage of the riders they were following.

Over the course of the race, people began to warm up to the little dots moving about the screen. As Belinda Hoare, one of the online trackers, said, “You’d go from checking maybe once or twice a day, to checking a couple of times a day, to checking hourly, and then you’d have the map open constantly … you really did feel like you got to know these people.”

On March 18, 2017, Hall’s dot was in second place, when at 6:22 a.m. it suddenly stopped moving near the intersection of the Monaro Highway and Williamsdale Road. It was the final day of the race, and puzzled fans began to wonder why Hall had paused at this critical point. What they did not yet know was that he had been struck by a car and killed. By GPS, they had witnessed his death.

In a few short decades, GPS has become so ubiquitous and indispensable it has entered almost every sphere of our lives. The moment you step outside with your smartphone in hand, you too are a moving dot. And though you cannot see it, the world has been overlaid with a time-and-space grid. All of us are synchronized to it and can be traced by our coordinates. We are largely unaware of the role satellites play in our lives, but stock markets, telecommunications, jogging routes, drone strikes, local weather forecasts, ATM machines, traffic lights, and food deliveries all rely on this public infrastructure that orbits silently high above us.

The signals are controlled by the U.S. Air Force and used by about a billion people daily. At night, you might occasionally see one of these GPS satellites twinkling in the sky like an artificial star as it reflects the sun. Each satellite weighs around two metric tons, and with their solar panels stretched out, the largest have wingspans of about 35 meters, or the length of two tractor-trailers. Orbiting at an altitude of 20,200 kilometers above Earth, each satellite belongs to a constellation of 24-31 GPS satellites at any given time, that zip around the planet at speeds of more than 11,000 kilometers an hour.

In their book GPS Declassified, Eric Frazier and Richard Easton imagine what Captain Cook, who navigated with real stars, might think of this modern technology.

Cook: What use are invisible stars?

Commander: We don’t need to see them. The satellites transmit electromagnetic frequencies … radio signals that our equipment uses to determine our position. Radio signals are very rapid vibrations that our instruments detect with their antennas, which for them are like our ears, but these are not sounds anyone can hear.

Cook: You steer your ship with sounds you cannot hear from stars you cannot see?

That is exactly what we do. Humans can hear sound at a range of 20 hertz to 20 kilohertz, but GPS radio signals are much higher than that. Operating at bands of 1,227.6 megahertz and 1,575.42 megahertz, these radio waves, when they reach the ground, aren’t audible to any animal on Earth. Radio signals are incredibly faint. As Carl Sagan once said, “The total energy picked up by all the radio telescopes on the entire planet in all of history is less than the energy of a single snowflake hitting the ground.” That statement was made when he recorded the television show Cosmos in 1980. According to astronomer Frank Drake, who made the original calculation, with the additional radio waves beaming down to Earth since then, the amount might now be equal to “two snowflakes … maybe three.”

Using receivers, however, we are able to pick up the faint waves of these signals as they wash over us. And it’s not just the US complement of satellites we can choose from either. Russia has its GLONASS satellites, the EU has Galileo, and China has its BeiDou system of navigation satellites. Pulling in signals from one or more of these systems, along with a base station at a known position for reference, today’s civilian GPS receivers can now pinpoint your location within 1.5 meters (it had been within an area about the size of a football field in the 1990s).

Of course, GPS satellites, which operate at medium Earth orbit (MEO) and circle the planet twice a day, are not the only eyes in the sky. At low Earth orbit (LEO), or an altitude of two 2,000 kilometers and below, you’ll find the majority of Earth observation satellites. Circling Earth every 90 minutes, these satellites are close to the planet’s surface and are frequently used for meteorology, map-making, and environmental monitoring. Zooming up much higher, to an altitude of 35,786 kilometers is where you’ll find the satellites operating at geosynchronous orbit (GSO) and geostationary Earth orbit (GEO). These satellites are synchronized with the rotational period of the planet and are primarily used for telecommunications, where the signals can be constantly and reliably accessed from the same spot on Earth. As artist and geographer Trevor Paglen points out, geostationary satellites are “thousands of times further away” and “remain locked as man-made moons in perpetual orbit long after their operational lifetimes.” Because they are too far away to bring back down and burn up in the atmosphere, instead, when these satellites reach the end of their lives, operators on Earth use on-board propellant to bump them up three hundred kilometers into what’s known as a graveyard orbit. Paglen notes that here they will stay circling Earth, outlasting the pyramids as remnants of our civilization. Archaeologists of the future will not just dig the earth; they will likely uncover much about the twenty-first-century human record by examining our well-preserved machines looming high up in our space cemeteries.

Beyond LEO, MEO, and GEO, however, there are still other orbits that for security reasons have no published schedules. These are the secret paths of the spy satellites. The CIA has been launching “Keyhole” (KH) class reconnaissance satellites since the 1960s. They have powerful lenses that can zoom in on the tiniest details on Earth and yet remain invisible to the general public. As was the case with GPS, the capabilities of civilian craft are several years behind what the military can do. In April 2018, Surrey Satellite Technology Ltd. announced that the United Kingdom’s Carbonite-2 satellite was able to record full-color HD video from 505 kilometers away. By stacking the frames in much the same way macro photographers do, experts can use the data to resolve an image from space down to sixty centimeters. And this is a civilian craft. With some US government restrictions relaxed, commercial imaging satellites like the ones Google uses will now be able to show images at 25 centimeters of resolution. That’s the ability to see your face—from space.

The latest spy satellites are even more powerful. Keyhole electro-optical imaging satellites of the KH-12 class are said to have a primary mirror on board that is 2.4 meters in diameter. That’s the same size as the mirror used on the Hubble Space Telescope, which is used to image objects 10-15 billion kilometers away. We can only imagine the resolution this class of reconnaissance satellites has when its lenses are turned not on outer space but on Earth. Not much is revealed about the Keyhole satellites, but we do know that launches are managed by the National Reconnaissance Office with a heavily funded budget of an estimated $10 billion a year. The satellites usually follow polar elliptical orbits, allowing them to scan all of Earth from pole to pole, passing over the equator at a different longitude each time as the planet beneath spins from day to night.

Even declassified documents about spy satellites are heavily redacted, so what we know about their locations comes largely from hobbyists who track their trajectories from Earth. These amateur astronomers have their eyes trained on the top secret machines. They are, in essence, the only eyes that watch the watchers. Communicating through a mailing list called SeeSat-L, this small group of observers from around the world uses stop-watches, telescopes, and cameras to monitor the orbital planes of approximately four hundred military satellites. As one member of the group, Marco Langbroek, described in Popular Science, “Just like the Earth has a coordinate grid, with latitude and longitude, the sky has a coordinate grid, and every star has a coordinate within that grid. And by using stars as a reference point you can determine the coordinates of a satellite in the sky.”

For most of us, these satellites are out of sight and out of mind, but the reality is there are thousands of highly advanced commercial, scientific, and military eyes that hover and swoop in the skies above us performing duties that are critical to the functioning of modern society. As geostrategist Nayef Al-Rodhan writes:

Any accidental interruption or deliberate severance of space- based services would cause immense financial losses and other disruptions. Indeed, a single day without access to space would have disastrous consequences worldwide. Approximately $1.5 trillion worth of financial market transactions per day would be stifled, throwing global markets into disarray. According to statistics provided by the International Air Transport Association, over 100,000 commercial flights crisscross the planet daily. Evidently such flights would be interrupted by communication disruptions, and deliveries of emergency health services would be severely hampered. Additionally, coordinating effective responses to crises would become nearly impossible. Due to the fundamentally transnational nature of almost all outer space activities, any conflict in outer space—even a limited one—would have disastrous consequences for the large amount of civilians globally who depend on the provision of outer space services. Contemporary strategists warn that command and control structures of modern militaries are also becoming critically dependent on space-based assets for communication, coordination, reconnaissance, surveillance, high-precision targeting and other critical military activities. This increasing indispensability of space for modern military activities makes satellites ideal targets in future conflicts.

The targeting of satellites makes everyone on Earth—especially the most developed and technologically advanced nations—exceptionally vulnerable. One incident in particular has shown the potential for serious disruption in space. On January 11, 2007, China launched a ballistic missile from Xichang Space Center. Its target was innocuous, the Fengyun-1C, an old Chinese weather satellite traveling at around 27,000 kilometers an hour. The missile carried a kinetic kill vehicle, which it released toward the weather satellite, coming in from the opposite direction at a relative velocity of 32,400 kilometers an hour. The head-on impact destroyed the satellite instantly, shattering it into a cloud of debris that sent over 35,000 shards into orbit, where they still circle like a ring of daggers around the planet. The threat of the space debris to other orbiting satellites is certainly dangerous, but the mission made something else crystal clear. While ostensibly China was decommissioning an aging satellite, it also proved to the world it had the capacity to destroy a satellite in orbit and blind another nation’s eyes.

Satellites Are Quietly, Constantly Watching Us syndicated from https://triviaqaweb.wordpress.com/feed/

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mthrynn · 7 years

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Deep learning is enjoying unprecedented success in a variety of commercial applications, but it is also beginning to find its footing in science. Just a decade ago, few practitioners could have predicted that deep learning-powered systems would surpass human-level performance in computer vision and speech recognition tasks.

These tools are now poised to help scientists contend with some of the most challenging data analytics problems in a number of domains. For example, extreme weather events pose great potential risk on ecosystem, infrastructure and human health. Analyzing extreme weather data from satellites and weather stations and characterizing changes in extremes in simulations is an important task. Similarly, upcoming astronomical sky surveys will obtain measurements of tens of billions of galaxies, enabling precision measurements of the parameters that describe the nature of dark energy. But in each case, analyzing the mountains of resulting data poses a daunting challenge.

Prabhat, NERSC

A growing number of scientists are already employing HPC systems for data analytics, and many are now beginning to apply deep learning and other types of machine learning to their large datasets. Toward this end, in 2016 the U.S. Department of Energy’s National Energy Research Scientific Computing Center (NERSC) expanded its support for deep learning and began forming hands-on collaborations with scientists and industry. NERSC users from science domains such as geosciences, high energy physics, earth systems modeling, fusion and astrophysics are now working with NERSC staff, software tools and services to explore how deep learning can improve their ability to solve challenging science problems.

In this Q&A with Prabhat, who leads the Data and Analytics Services Group at NERSC, he talks about the history of deep learning and machine learning and the unique challenges of applying these data analytics tools to science. Prabhat is also an author on two related technical papers being presented at SC17, “Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data” and “Galactos: Computing the 3-pt Anisotropic Correlation for 2 Billion Galaxies,” and is conducting two deep learning roundtables in the DOE Booth (#613) at SC17. He is also giving a plenary talk on deep learning for science on Sunday, November 12 at the Intel HPC Developer Conference held in conjunction with SC17.

How do you define deep learning, and how does it differ from machine learning?

At the Department of Energy, we tackle inference problems across numerous domains. Given a noisy observation, you would like to infer properties of the object of interest. The discipline of statistics is ideally suited to solve inference problems. The discipline of Machine Learning lies at the intersection of statistics and computer science, wherein core statistical methods were employed by computer scientists to solve applied problems in computer vision and speech recognition. Machine learning has been around for more than 40 years, and there have been a number of different techniques that have fallen in and out of favor: linear regression, k-means, support vector machines and random forests. Neural networks have always been part of machine learning – they were developed at MIT starting in the 1960s – there was the major development of the back-propagation algorithm in the mid-1980s, but they never really picked up until 2012. That is when the new flavor of neural networks – that is, deep learning – really gained prominence and finally started working. So the way I think of deep learning is as a subset of machine learning, which in turn is closely related to the field of statistics, and all of them have to do with solving inference problems of one kind or another.

What technological changes occurred that enabled deep learning to finally start working?

Three important trends have happened over the last 20 years or so. First, thanks to the internet, “big Data,” or large archives of labeled and unlabeled datasets, has become readily accessible. Second, thanks to Moore’s Law, computers have become extremely powerful. A laptop featuring a GPU and a CPU is more capable than supercomputers from previous decades. These two trends were prerequisites for enabling the third wave of modern neural nets, deep learning, to take off. The basic machinery and algorithms have been in existence for three decades, but it is only the unique confluence of large datasets and massive computational horsepower that enabled us to explore the expressive capabilities of Deep Networks.

What are some of the leading types of deep learning methods used today for scientific applications?

As we’ve gone about systematically exploring the application of deep learning to scientific problems over the last four years, what we have found is that there are two dominant architectures that are relevant to science problems. The first is called the convolutional network. This architecture is widely applicable because a lot of the data that we obtain from experimental and observational sources (telescopes and microscopes) and simulations – tend to be in the form of a grid or an image. Similar to commodity cameras, we have 2D images, but we also typically deal with 3D, 4D and multi-channel images. Supervised pattern classification is a common task shared across commercial and scientific use cases; applications include face detection, face recognition, object detection and object classification.

The second approach is more sophisticated and has to do with the recurrent neural network: the long short-term memory (LSTM) architecture. In commercial applications, LSTMs are used for translating speech by learning the sequence-to-sequence mapping between one language and another. In our science cases, we also have sequence-to-sequence mapping problems, such as gene sequencing, for example, or in earth systems modeling, where you are tracking storms in space and time. There are also problems in neuroscience that take recordings from the brain and use LSTM to predict speech. So broadly those two flavors of architectures – convolutional networks and LSTMs – are the dominant deep learning methodologies for science today.

In recent years, we have also explored auto-encoder architectures, which can be used for unsupervised clustering of datasets. We have had some success in applying such methods for analysis of galaxy images in astronomy, and Data Bay sensor data for neutrino discovery. The latest trend in deep learning is the generative adversarial network (GAN). This architecture can be used for creating synthetic data. You can feed in examples from a certain domain, say cosmology images or Large Hadron Collider (LHC) images, and the network will essentially learn a process that can explain these images. Then you can ask that same network to produce more synthetic data that is consistent with other images it has seen. We have empirical evidence that you can use GANs to produce synthetic cosmology or synthetic LHC data without resorting to expensive computational simulations.

What is driving NERSC’s growing deep learning efforts, and how did you come to lead these efforts?

I have a long-standing interest in image processing and computer vision. During my undergrad at IIT Delhi, and grad studies at Brown, I was intrigued by object recognition problems, which seemed to be fairly hard to solve. There was incremental progress in the field through the 1990s and 2000s, and then suddenly in 2012 and 2013 you see this breakthrough performance in solving real problems on real datasets. At that point, the MANTISSA collaboration – a research project originally begun when I was part of Berkeley Lab’s Computational Research Division – was exploring similar pattern detection problems, and it was natural for us to explore whether deep learning could be applied to science problems. We spent the next three to four years exploring applications in earth systems modeling, neuroscience, astronomy and high energy physics.

When a new method/technology comes along, one has to make a judgment call on how long you want to wait before investing time and energy in exploring the possibilities. I think the DAS group at NERSC was one of the early adopters. We recognized the importance of this technique and demonstrated that it could work for science. In the experimental and observational data community, there are a lot of examples of domain scientists who have been struggling with pattern recognition problems for a long time. And now the broader science community is waking up to the possibilities of machine learning to help them solve these problems.

What is NERSC’s current strategy for bringing deep learning capabilities to its users?

Since NERSC is a DOE Office of Science national user facility, we listen to our users, track their emerging requirements and respond to their needs. Our users are telling us that they would like to explore machine learning/deep learning and see what it can do for them. We currently have about 70 users who are actively using deep learning software at NERSC, and we want to make sure that our software, hardware, policies and documentation are all up to speed. Over the past two years, we have worked with the vendor community and identified a few popular deep learning frameworks (TensorFlow, Caffe, Theano and Torch) and have deployed them on Cori. In addition to making the software available, we have documentation and case studies in place. We also have in-depth collaborations in about a dozen areas where NERSC staff, mostly from the DAS group, have worked with scientists to help them explore the application of deep learning. And we are forming strategic relationships with commercial vendors and other research partners in the community to explore the frontier of deep learning for science.

Do certain areas of scientific research lend themselves more than others to applying deep learning?

Right now our success stories span research sponsored by several DOE Office of Science program offices, including BER, HEP and NP. In earth systems modeling, we have shown that convolutional architectures can extract extreme weather patterns in large simulations datasets. In cosmology, we have shown that CNNs can predict cosmological constants, and GANs can be potentially used to supplement existing cosmology simulations. In astronomy, the Celeste project has effectively used auto-encoders for modeling galaxy shapes. In high energy physics, we are using convolutional architectures for discriminating between different models of particle physics, exploring LSTM architectures for particle tracking. We’ve also shown that deep learning can be used for clustering and classifying various event types at the Daya Bay experiment.

So the big takeaway here is that for the tasks involving pattern classification, regression and creating fast simulators, deep learning seems to do a good job – IF you can find training data. That’s the big catch – if you have labeled data, you can employ deep learning. But it can be a challenge to find training data in some domain sciences.

Looking ahead, what are some of the challenges in developing deep learning tools for science and applying them to research projects at NERSC and other scientific supercomputing facilities?

We can see a range of short-term and long-term challenges in deep learning for science. The short-term challenges are mostly pragmatic issues pertaining to development, enhancement and deployment of tools. These include handling complex data; scientific data tends to be very diverse (compared to images and speech), we are working with 2D, 3D, even 4D data and the datasets can be sparse or dense and defined over a regular, or irregular grid. Deep learning frameworks will need to account for this diversity going forward. Performance and scaling are also barriers. Our current networks can take several days to converge on O(10) GB datasets, but several scientific domains would like to apply deep learning to 10TB-100TB datasets. Thankfully, this problem is right up our alley at HPC centers.

Another important challenge faced by domain scientists is hyper-parameter tuning: Which network architecture do you start with? How do you choose an optimization algorithm? How do you get the network to converge? Unfortunately, only a few deep learning experts know how to address this problem; we need automated strategies/tools. Finally, once scientific communities realize that deep learning can work for them, and access to labeled datasets is the key barrier to entry, they will need to self-organize and conduct labeling campaigns.

The longer-term challenges for deep learning in science are harder, by definition, and include a lack of theory, interpretability, uncertainty quantification and the need for a formal protocol. I believe it’s very early days in the application of deep learning to scientific problems. There’s a lot of low-hanging fruit in publishing easy papers that demonstrate state-of-the-art accuracy for classification, regression and clustering problems. But in order to ensure that the domain science community truly embraces the power of deep learning methods, we have to keep the longer term, harder challenges in mind.

About the Author

Kathy Kincade is a science & technology writer and editor with the Berkeley Lab Computing Sciences Communications Group.

The post Deep Learning for Science: A Q&A with NERSC’s Prabhat appeared first on HPCwire.

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