Felipe Pantone, a graffiti artist based in Valencia, Spain, does these amazing, cyberspace-is-everting murals, skinning buildings and even cars all around the world. (
via JWZ)
An interesting-looking new machine translation technique that takes grammar into consideration by Ehsaneddin Asgari and Hinrich Schütze. Excerpt from a summary on Technology Review:
This data set is not big enough for the kind of industrial machine learning that Google and others perform. So Asgari and Schutze have come up with another approach based on the way tenses appear in different languages.
Most languages use specific words or letter combinations to signify tenses. So the new trick is to manually identify these signals in several languages and then use data-mining techniques to hunt through other translations looking for words or strings of letters that play the same role.
For example, in English the present tense is signified by the word “is,” the future tense by the word “will,” and the past tense by the word “was.” Of course, there are other signifiers too.
Asgari and Schutze’s idea is to find all these words in the English translation of the Bible along with other examples from a handful other language translations. Then look for words or letters strings that play the same role in other languages. For example, the letter string “-ed” also signifies the past tense in English.
But there is a twist. Asgari and Schutze do not start with English because it is a relatively old language with many exceptions to the rule, which makes it hard to learn.
Instead, they start with a set of Creole languages that have developed from a mixture of other languages. Because they are younger, Creole languages have had less time to develop these linguistic idiosyncrasies. And that means they generally contain better markers of linguistic features such as tense. “Our rationale is that Creole languages are more regular than other languages because they are young and have not accumulated ‘historical baggage’ that may make computational analysis more difficult,” they say.
One of these languages is Seychelles Creole, which uses the word “ti” to signify the past tense. For example, “mon travay” means “I work” in this language, while “mon ti travay” means “I worked” and “mon ti pe travay” means “I was working.” So “ti” is a good signifier of past tense.
Asgari and Schutze compile a list of past tense signifiers in 10 other languages and then mine the Parallel Bible Corpus for other words and letter strings that perform the same function. They repeat this for the present tense and future tense.
The results make for interesting reading. The technique reveals linguistics constructions related to tense in common languages such as “-ed” in English and “-te” in German, as well as the words and phrases that perform the same functions in much less common languages such as the past tense signifier “den” in the Gourmanchema language from Burkino Faso, and “yi” in Yalunka, spoken in Mali, and so on.
This work allows the researchers to create maps showing how languages using similar tense constructions are related (see diagram).
That’s interesting work. Asgari and Schutze have developed a computational method to analyze the way people use the past, present, and future tense in over 1,000 languages. This is the largest cross-language computational study ever undertaken. Indeed, the number of languages involved is an order of magnitude greater than in other studies.
Tribes solves the inaccuracies and other significant flaws in other recommendation systems such as inference engines and collaborative filtering. Tribes solves the problems inherent in existing recommendation systems for “products of taste.” It does this by recognizing that the only relevant information is a single datum: a personal preference expressed in terms of future intentions. Products of personal taste include wine, books, movies, music, cheese, and restaurants and more. Wine is a good example of why current systems fail. It’s nearly impossible for a retail consumer to reliable choose a good bottle that they will like enough for a subsequent purchase. Many retail purchases are so disliked that they get poured down the kitchen sink.
The new kind of neural networks are an evolution of the initial feed-forward model of LeNet5 / AlexNet and derivatives, and include more sophisticated by-pass schemes than ResNet / Inception. These feedforward neural networks are also called encoders, as they compress and encode images into smaller representation vectors. The new wave of neural networks have two important new features:
generative branches: also called decoders, as they project a representation vector back into the input space
recurrent layers: that combine representations from previous time steps with the inputs and representations of the current time step
The practice of using people’s outer appearance to infer inner character is called physiognomy. While today it is understood to be pseudoscience, the folk belief that there are inferior “types” of people, identifiable by their facial features and body measurements, has at various times been codified into country-wide law, providing a basis to acquire land, block immigration, justify slavery, and permit genocide. When put into practice, the pseudoscience of physiognomy becomes the pseudoscience of scientific racism.
Rapid developments in artificial intelligence and machine learning have enabled scientific racism to enter a new era, in which machine-learned models embed biases present in the human behavior used for model development. Whether intentional or not, this “laundering” of human prejudice through computer algorithms can make those biases appear to be justified objectively.
The taxonomy is from the essay ‘The Analytical Language of John Wilkins’ by Jorge Luis Borges where he discusses arbitrarities of John Wilkins and writes “it is clear that there is no classification of the Universe not being arbitrary and full of conjectures. The reason for this is very simple: we do not know what thing the universe is.” It is referred as another example of faulty human schemes.
Most of the current AI systems are basically classifiers, and they learn and work based on the classifications provided by humans, thus inevitably imperfect.
The Thwaites Glacier. This is the glacier that frightens the climate scientists and other scientists who study the ice shelves and glaciers in Antarctica. This Rolling Stone article tells about Thwaites, and the increasing instability of the ice in Antarctica and the effects on coastal areas if that instability results in glaciers leaving the continent of Antarctica to fall into the ocean. And what happens when those things happen in conjunction with continued melting in Greenland?
Excerpt:
The trouble with Thwaites, which is one of the largest glaciers on the planet, is that it’s also what scientists call “a threshold system.” That means instead of melting slowly like an ice cube on a summer day, it is more like a house of cards: It’s stable until it is pushed too far, then it collapses. When a chunk of ice the size of Pennsylvania falls apart, that’s a big problem. It won’t happen overnight, but if we don’t slow the warming of the planet, it could happen within decades. And its loss will destabilize the rest of the West Antarctic ice, and that will go too. Seas will rise about 10 feet in many parts of the world; in New York and Boston, because of the way gravity pushes water around the planet, the waters will rise even higher, as much as 13 feet. “West Antarctica could do to the coastlines of the world what Hurricane Sandy did in a few hours to New York City,” explains Richard Alley, a geologist at Penn State University and arguably the most respected ice scientist in the world. “Except when the water comes in, it doesn’t go away in a few hours – it stays.”
With 10 to 13 feet of sea-level rise, most of South Florida is an underwater theme park, including Miami, Fort Lauderdale, Tampa and Mar-a-Lago, President Trump’s winter White House in West Palm Beach. In downtown Boston, about the only thing that’s not underwater are those nice old houses up on Beacon Hill. In the Bay Area, everything below Highway 101 is gone, including the Googleplex; the Oakland and San Francisco airports are submerged, as is much of downtown below Montgomery Street and the Marina District. Even places that don’t seem like they would be in trouble, such as Sacramento, smack in the middle of California, will be partially flooded by the Pacific Ocean swelling up into the Sacramento River. Galveston, Texas; Norfolk, Virginia; and New Orleans will be lost. In Washington, D.C., the shoreline will be just a few hundred yards from the White House.
Seventy percent of the Earth’s fresh water is frozen here in ice sheets that can be nearly three miles thick. The continent is roughly divided by the Transantarctic Mountains; East Antarctica is bigger and colder than West Antarctica, which is far more vulnerable to melting, in part because the bases of many glaciers in West Antarctica lie below sea level, making them susceptible to small changes in ocean temperatures.
I used videos recorded from trains windows, with landscapes that moves from right to left and trained a Machine Learning (ML) algorithm with it. First, it learns how to predict the next frame of the videos, by analyzing examples. Then it produces a frame from a first picture, then another frame from the one just generated, etc. The output becomes the input of the next calculation step. So, excepting the first one that I chose, all the other frames were generated by the algorithm. The results are low resolution, blurry, and not realistic most of the time. But it resonates with the feeling I have when I travel in a train. It means that the algorithm learned the patterns needed to create this feeling. Unlike classical computer generated content, these patterns are not chosen or written by a software engineer. In this video, nobody made explicit that the foreground should move faster than the background: thanks to Machine Learning, the algorithm figured that itself. The algorithm can find patterns that a software engineer may haven’t noticed, and is able to reproduce them in a way that would be difficult or impossible to code.
To put it simply, Chaos Engineering is one particular approach to “breaking things on purpose” that aims at teaching us something new about systems by performing experiments on them. Ultimately, our goal is to identify hidden problems that could arise in production. Only then will we be able to address systemic weaknesses and make our systems fault-tolerant. Chaos Engineering goes beyond traditional (failure) testing in that it’s not only about verifying assumptions. It also helps us explore the many unpredictable things that could happen and discover new properties of our inherently chaotic systems.
“We keep inventing jobs because of this false idea that everybody has to be employed at some kind of drudgery because, according to Malthusian Darwinian theory he must justify his right to exist. So we have inspectors of inspectors and people making instruments for inspectors to inspect inspectors. The true business of people should be to go back to school and think about whatever it was they were thinking about before somebody came along and told them they had to earn a living.”
“The idea that we live life in a straight line, like a story, seems to me to be increasingly absurd and, more than anything, a kind of intellectual convenience […] I feel that the events in our lives are like a series of bells being struck and the vibrations spread outwards, affecting everything, our present, and our futures, of course, but our past as well. Everything is changing and vibrating and in flux.”
I read the article published in Scientific American, and most of the report described in the article. The report is entitled, “Snow, Water, Ice, and Permafrost in the Arctic.”It is an assessment compiled every few years by the Arctic Monitoring and Assessment Programme, the scientific body that reports to the governments that make up the Arctic Council, a forum for issues affecting the region. The last assessment came out in 2011. Here’s the link to the report if you want to read it.
My concern is obvious: the echo chamber. Those of us who are worried about climate change, including scientists and some politicians, will be concerned. Those who can take policy actions to address the causes of this problem, particularly in the US, will continue ignoring, avoiding or denying the problem. And Nero will keep on fiddling and the emperor has no clothes. Right?
Excerpt:
The Arctic is warming more than twice as fast as the rest of the planet, suggests a huge assessment of the region. The warming is hastening the melting of Arctic ice and boosting sea-level rise.
The report, compiled by more than 90 scientists, documents the myriad changes already under way across the Arctic because of climate change—from declining sea ice and melting glaciers to shifting ecosystems and weather patterns. From 2011 to 2015, the assessment finds, the Arctic was warmer than at any time since records began around 1900 (see ’Arctic warming’).
Sea ice continues to decline, and the extent of snow cover across the Arctic regions of North America and Eurasia each June has halved as compared to observations before 2000.
“The take-home message is that the Arctic is unravelling,” says Rafe Pomerance, who chairs a network of conservation groups called Arctic 21 and was a deputy assistant secretary of state for environment and development under US President Bill Clinton. “The fate of the Arctic has to be moved out of the world of scientific observation and into the world of government policy.”
The report increases projections for global sea-level rise, which takes into account all sources of melting including the Arctic. Their new minimum estimates are now almost double those issued by the Intergovernmental Panel on Climate Change (IPCC) in 2013 for some emissions scenarios. In fact, the latest calculations suggest that the IPCC’s middle estimates for sea-level rise should now be considered minimum estimates.
In one scenario, which assumes that carbon emissions rise slightly above the goals set by the 2015 Paris climate agreement—but still see a considerable reduction—sea levels would increase by at least 0.52 metres by 2100, compared with 2006, the Arctic report says. Under a business-as-usual scenario, the minimum increase would be 0.74 metres.
“The dominant culture tolerates parasitic counter-cultures as more or less innocuous deviations, but it cannot accept critical manifestations which call it [the dominant culture] into question. Counter-culture comes about when those who transform the culture in which they live become critically conscious of what they are doing and elaborate a theory of their deviation from the dominant model, offering a model that is capable of sustaining itself.”
this is a deeper phenonemon called the “tar-baby” principle and is basically:
You are attached to what you attack. In academic parlance, the idea is that the currently reigning powers define the space and the terms of engagement. Both the definition of “culture” and “counter-culture” are part of a “hegemonic discourse” (Antonio Gramsci).
Solarpunk is a movement in speculative fiction, art, fashion and activism that seeks to answer and embody the question “what does a sustainable civilization look like, and how can we get there?” The aesthetics of solarpunk merge the practical with the beautiful, the well-designed with the green and wild, the bright and colorful with the earthy and solid. Solarpunk can be utopian, just optimistic, or concerned with the struggles en route to a better world — but never dystopian. As our world roils with calamity, we need solutions, not warnings. Solutions to live comfortably without fossil fuels, to equitably manage scarcity and share abundance, to be kinder to each other and to the planet we share. At once a vision of the future, a thoughtful provocation, and an achievable lifestyle. In progress…
History is largely peace punctuated by wars, rather than wars punctuated by peace. When you read historical accounts, you are under the illusion that history is mostly wars, that states like to fight as a default condition, whenever they have the chance, and that the only coordination between entities takes place when two countries have a “strategic” alliance against a common danger.[…] We will be fed by tomes of histories of wars. […] Reading a history book offers a similar bias to reading an account of life in New York seen from an emergency room employee at Bellevue Hospital.
But, in truth, it’s not that difficult to understand Ethereum, blockchains, Bitcoin and all the rest — at least the implications for people just going about their daily business, living their lives. Even a programmer who wants a clear picture can get a good enough model of how it all fits together fairly easily. Blockchain explainers usually focus on some very clever low-level details like mining, but that stuff really doesn’t help people (other than implementers) understand what is going on. Rather, let’s look at how the blockchains fit into the more general story about how computers impact society.
“Some say why waste your time believing in God when there is so much natural beauty and awesomeness around us. Some say that there is more beauty and wonder looking at a butterfly and I agree, butterflies are beautiful things, but if you get a human being to look closely at a butterfly, to look very closely and get some more human beings to look at that butterfly so that there is a collective of people all peering intently at the butterfly they will ultimately fall to their knees and worship that butterfly. It’s the way humans are put together. I don’t think that makes them stupid. I think it’s kind of sweet. Until someone says well my butterfly is the true butterfly and yours is not and flies a plane into the twin towers.”
In a world which is rapidly being decentralized — there also needs to be a decentralized way to ensure adequate payment for those who provide us with the infrastructure. We have found a way to get there and now we will present an evolutionary path towards it. For the last month we have been examining existing technology and its potential, to perform POC (Proof Of Concept) experiments — with the goal of understanding how to build a decentralized VPN service and how to provide monetization to people running this network — VPN node operators.
“Over the course of his or her life, a typical member of a modern affluent society will own several million artefacts – from cars and houses to disposable nappies and milk cartons. There’s hardly an activity, a belief, or even an emotion that is not mediated by objects of our own devising.”
–Harari, Yuval Noah.
Sapiens: A Brief History of Humankind. 2015. (viacarvalhais)
Skellig Michael is an island located roughly seven miles west of the Iveragh Peninsula in County Kerry, Ireland. Between the 6th and 8th century a Celtic Christian monastery was established here and was occupied until the 12th century. You may also recognize it as the secret island from the seventh Star Wars movie where Luke Skywalker hides out.
51.771130, -10.539963
Instagram: http://bit.ly/2qjkSnh Source imagery: DigitalGlobe
Large area WAC mosaic illustrating reflectance differences due to 30° change in view angle from the center of a WAC frame to each edge (no photometric correction). Mosaic composed of ~30 WAC orbital image strips [NASA/GSFC/Arizona State University].
“An early set of notes proposed a “service equipped to advise on all problems of design”, addressing the needs of “the State, Municipal Authorities, Industry or Commerce.” They anticipated a post-war demand for technical expertise and a need for “the reconditioning and re-designing public utility services” recommending “contact… with the railway companies, motor coach lines and so on.“”
A huge payoff from the longevity of the LRO mission is the repeat coverage obtained by the LROC Wide Angle Camera (WAC). The WAC has a very wide field-of-view (FOV), 90° in monochrome mode and 60° in multispectral mode, hence its name. On the one hand, the wide FOV enables orbit-to-orbit stereo, which allowed LROC team members at the DLR to create the unprecedented 100 meter scale near-global (0° to 360° longitude and 80°S to 80°N latitude) topographic map of the Moon (the GLD100)!
Vainio’s influence on ambient and industrial electronic music was somewhat unspoken in his lifetime. He was not a figurehead of a scene, but pretty much all booming palettes of mechanical sound being made today nod in some way to Vainio and his work with Pan Sonic […] Vainio’s beats weren’t beats at all, they were the sound and feeling of a black hole opening up in the centre of your chest.[…] like “flares, vapour trails, LEDs, neon tubes close to death, heart murmurs, apertures opening and closing in cement walls, tiny mechanised guillotines snipping the heads from tin soldiers, sheets of led unfurling in underground car parks”.
Estonia is Europe’s leading catcher of Vladimir Putin’s spies as well as Europe’s leading unmasker of his manifold agents of influence. It is uncharacteristically unafraid to advertise its own national security threats by naming and shaming its yearly haul of enemy operatives, at least in comparison to other Western NATO democracies, which tend to hush up such bilateral embarrassments, preferring the discreet expulsion of spooks or “PNGing” of diplomats who glad-hand by day and engage in dead-letter drops by night.
The workshops also highlighted a major blind spot in thinking about AI. Autonomous systems are already deployed in our most crucial social institutions, from hospitals to courtrooms. Yet there are no agreed methods to assess the sustained effects of such applications on human populations.
Recent years have brought extraordinary advances in the technical domains of AI. Alongside such efforts, designers and researchers from a range of disciplines need to conduct what we call social-systems analyses of AI. They need to assess the impact of technologies on their social, cultural and political settings.
A social-systems approach could investigate, for instance, how the app AiCure — which tracks patients’ adherence to taking prescribed medication and transmits records to physicians — is changing the doctor–patient relationship. Such an approach could also explore whether the use of historical data to predict where crimes will happen is driving overpolicing of marginalized communities. Or it could investigate why high-rolling investors are given the right to understand the financial decisions made on their behalf by humans and algorithms, whereas low-income loan seekers are often left to wonder why their requests have been rejected.
“People worry that computers will get too smart and take over the world, but the real problem is that they’re too stupid and they’ve already taken over the world.” This is how computer scientist Pedro Domingos sums up the issue in his 2015 book The Master Algorithm1. Even the many researchers who reject the prospect of a ‘technological singularity’ — saying the field is too young — support the introduction of relatively untested AI systems into social institutions.
“Seeing that I cannot choose any subject of great utility or pleasure, because my predecessors have already taken as their own all useful and necessary themes, I will do like one who, because of his poverty, is the last to arrive at the fair, and not being able otherwise to provide for himself, chooses all the things which others have already looked over and not taken, but refused as being of little value. With these despised and rejected wares — the leavings of many buyers — I will load my modest pack, and therewith take my course, distributing, not indeed amid the great cities, but among the mean hamlets, and taking such reward as befits the things I offer.”
–Da Vinci, Codice Atlantico 119 v. a, in
The Notebooks of Leonardo Da Vinci, Edward MacCurdy (trans.), Vol 1, Oxford: Jonathan Cape, 1945, p. 61 (viadearyesno)
“Beaches today are where we turn our backs not just on the world at large but also on our inland selves. They are a sanctuary, groomed to remove all distractions, sometimes including the other creatures that once made them their home. Beaches are thought of as a place where time stands still, devoid of a troubling past but also of an ever pressing future.”
–John R. Gillis, Life and Death of the Beach, New York Times (June 30, 2012)
“We have never had to deal with problems of the scale facing today’s globally interconnected society. No one knows for sure what will work, so it is important to build a system that can evolve and adapt rapidly.”
Once you’re boarded, united may not take your seat for overbooking reasons. You are not obligated to follow any unreasonable or illegal crewmember instruction. The police should not enforce civil contracts without a court order, and they took United’s side when clearly they were in the wrong. Aviation is a special case in many ways, but we don’t abdicate our rights or reason when we decide to fly. Everyone at united — from the CEO on down — has demonstrated a marked lack of thought, compassion and contrition. They deserve the maximum punishment that is possible.
The Ukrainian government has announced a plan to turn the area surrounding Chernobyl - the site of one of the worst nuclear meltdowns in history - into a solar energy farm, by constructing a series of solar panels inside the exclusion zone.
Not only would this plan - which is currently seeking investment - allow the country to use a giant chunk of radioactive land that’s unfit for human settlement, it would also provide a cheaper source of reusable energy that might decrease the country’s reliance on Russia.
“The Chernobyl site has really good potential for renewable energy,” Ukraine’s environment minister Ostap Semerak said in an interview in London. “We already have high-voltage transmission lines that were previously used for the nuclear stations, the land is very cheap and we have many people trained to work at power plants.”
