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Why East Germany is a map zombie
Three decades after the demise of the GDR, its familiar contours keep coming back from the dead.
- East Germany has been dead for a little more than three decades.
- But the former GDR just keeps popping up on all kinds of maps.
- It's a sign that life in the east of Germany is still very different from the west.
Forgotten, but not gone
The Berlin Wall in 1986, seen from West Berlin.
Credit: Noir, CC BY-SA 3.0
The GDR may be forgotten, but it's not gone. Apart from a shrinking handful of diehard nostalgics, nobody mourns the passing of the German Democratic Republic, as communist East Germany (1949-1990) was officially known.
It became such an exemplar of the chasm between the high ideals and grim reality of Soviet-style socialism that the regime literally had to fence in its citizens to keep them from running away. Up until the building of the Berlin Wall (1961), hundreds of East Germans each day 'voted with their feet', defecting to West Germany – decadent and capitalist, yes; hence also a lot more fun.
Inevitably, the fall of the Wall in 1989 was the death-knell for East Germany. We've just passed the 30th anniversary of German reunification, which came into effect on October 3, 1990. But after three decades of painful economic, political, and cultural adjustments, the ghost of East Germany lingers on the map.
Like secret messages that become visible under UV light, the contours of the GDR come out when you apply the right data filters. And not just once or twice. Again and again, we see the old (and to some, familiar) borders emerge. In other words, the German Democratic Republic is a map zombie. That's because life continues to be different in former East Germany – even if it's now just the east of Germany.
Below are some examples, selected from the Facebook group with the self-explanatory name: East Germany is discernibly visible on this relatable map.
The unhappy east
Happiness map of Germany. Can you spot the GDR?
Credit: Facebook / ARD, infratest / welt.de
East Germans are less happy than their western compatriots. Out of a maximum of 10 on the happiness scale, most of the former GDR colors red (below 7.2), the rest orange (between 7.2 and 7.4).
In the west, few areas are orange and none are red. Most areas are yellow-happy (7.4 to 7.6), and light-green-happy (7.6 to 7.7). Southern Bavaria (dark green; 7.7 and up) is the happiest corner of Germany.
Too bourgeois for the GDR?
Game, set and match!
Credit: Facebook / Laura Edelbacher
In the old Soviet bloc, sports were a propaganda tool, and athletic excellence a way to prove the regime's supremacy on the world stage.
But apparently, tennis was not the right vehicle – perhaps the East German communists thought it too bourgeois. That would explain why there is such a marked difference between east and west when it comes to the distribution of tennis courts.
The average wage in Wolfsburg is double that as in the adjacent area in the former GDR.
Credit: Facebook / Katapult
Thirty years after reunification, Germany's economy remains unbalanced along familiar lines. This map shows the averages for gross monthly wages: below €3000 in red areas (below €2500 in dark red zones). Almost all of the light red areas are in the east, none of the dark red ones are in the west.
Tantalizingly, Germany's highest-earning area (Wolfsburg, €5089) is right on the former East German border, next to an area with half the average wages. Car aficionados will recognize the name of the city as the home of Volkswagen HQ and the world's largest car plant.
Too many Ronnies
Democratic Republic of Ronnyland.
Older British TV viewers will remember a comic duo called "The Two Ronnies." If they had been German comedians, their names would have immediately pegged them as Ossis (eastern Germans).
'Ronny' is as popular in the east as it isn't in the west. In the eastern German state of Saxony-Anhalt (the dark-blue area on the map), between 66 and 78 out of 10,000 Facebook users carry that first name. In the rest of the former GDR (the middle-blue area), it's 54 to 66. In almost all of western Germany, the rate is below 18.
More public childcare
In the east, more than half the kids under three attend publicly-funded daycare.
The legacy of the communist past isn't all bad, it seems. Some collectivist traditions and provisions survive. Like more public childcare. This map shows the share of under-threes going to publicly-funded daycare centers: over 50 percent in most of the former GDR.
Mosques vs. hazelnut spread
Like twins separated at birth, east and west developed fascinating differences.
Like one of those sets of twins separated at birth, East and West Germany are a fascinating study in similarities and differences – some large, some small. The economic powerhouse that West Germany became needed foreign workers. Many came from Turkey, as evidenced by this map of mosques in Germany: only a handful are in the east.
In its decades alone, East Germany developed a range of household products, often barely disguised copies of western consumer goods. Many are on display in Berlin's DDR Museum. Nudossi, often dismissively called 'Ost-Nutella', is one of the rare brands that survived reunification. Perhaps that's because the spread contains 36 percent hazelnuts, almost three times the amount of actual Nutella (13 percent). Still, Wessis (western Germans) are clearly less keen on the stuff.
Far left, far right
Voting patterns in the east tend to be more eccentric in the east.
Credit: Facebook / GeoCurrents
Voting patterns in the east tend to be more eccentric in the east. The map on the left shows the results for the 2013 federal elections of Die Linke (the Left Party), which positions itself firmly to the left of the SPD, the mainstream social-democratic party. Die Linke garnered between 20 percent and a quarter of the votes right across the former GDR, and was nowhere near as successful anywhere else in Germany.
More recently, the right-wing populists of Alternative für Deutschland (AfD) have found a lot of support in the east. The undated map shows voting intentions for recent upcoming state elections. AfD is particularly strong in the south of the former GDR (26 percent in Saxony, 22 percent in Thuringia). Its highest score in the west is 11.6 percent in Baden-Württemberg.
Catholic, Protestant and None
'Nones' are the majority throughout East Germany.
Confessionally, Germany also remains a divided nation. This map shows which religion dominates where. Catholics predominate in the south and west (dark red: majority, light red: plurality). Protestants are a majority in the north and middle (dark blue), a plurality in the southwest (light blue).
East Germany is easily discernible: it's the part where the main religious affiliation is 'none'. That also includes the whole of Berlin (including the western half), plus the western cities of Hamburg and Frankfurt.
Poor overall, but not poorest overall
The western state of North Rhine-Westphalia has an ever higher poverty rate than the former GDR.
Credit: Facebook / Tagesschau
The former GDR has a consistently high poverty rate: an average of 17.5 percent throughout all six Länder (states). But there's a silver lining, of sorts: the poverty rate is even higher in the western state of North Rhine-Westphalia (18.1 percent), which contains the Ruhrgebiet, a.k.a. Germany's Rust Belt.
The R1a haplogroup is a genetic marker associated with Slavic populations.
The former border between East and West Germany mirrors a much older one: the western extent of the Slavic zone around the year 1000. This map shows the spread of the R1a haplogroup among locals.
This genetic marker is associated with Slavic populations. It is prevalent throughout the former GDR, particularly the south – and in eastern Austria, by the way. R1a 'islands' further west may be the result of more recent immigration waves, by Polish guest workers for example.
Streetcars and streetlights
In Berlin, the past is never dead. In fact, it's not even past.
And finally, two images that zoom in on Berlin. Now the reunified capital of a reunified country, before 1990 it was as divided as Germany itself. And that is still visible, if you know where to look.
At the map of Berlin's streetcars (top), for example. West Berlin never took the step to restore the pre-war streetcar network on its territory. East Berlin did. And that's still the case – with one exception: a single line was extended from the east to the west, a rare example of the west adopting anything 'eastern'.
When night falls, the division between east and west can still be seen from the sky. In the east, street lights use sodium vapor lamps, providing a warm orange glow. In the west, the lamps are fluorescent, resulting in a brighter yellow light.
All maps taken from the Facebook group East Germany is clearly visible on this relatable map. Where possible, credit was given to the original content provider.
Strange Maps #1063
Got a strange map? Let me know at firstname.lastname@example.org.
Inventions with revolutionary potential made by a mysterious aerospace engineer for the U.S. Navy come to light.
- U.S. Navy holds patents for enigmatic inventions by aerospace engineer Dr. Salvatore Pais.
- Pais came up with technology that can "engineer" reality, devising an ultrafast craft, a fusion reactor, and more.
- While mostly theoretical at this point, the inventions could transform energy, space, and military sectors.
The U.S. Navy controls patents for some futuristic and outlandish technologies, some of which, dubbed "the UFO patents," came to life recently. Of particular note are inventions by the somewhat mysterious Dr. Salvatore Cezar Pais, whose tech claims to be able to "engineer reality." His slate of highly-ambitious, borderline sci-fi designs meant for use by the U.S. government range from gravitational wave generators and compact fusion reactors to next-gen hybrid aerospace-underwater crafts with revolutionary propulsion systems, and beyond.
Of course, the existence of patents does not mean these technologies have actually been created, but there is evidence that some demonstrations of operability have been successfully carried out. As investigated and reported by The War Zone, a possible reason why some of the patents may have been taken on by the Navy is that the Chinese military may also be developing similar advanced gadgets.
Among Dr. Pais's patents are designs, approved in 2018, for an aerospace-underwater craft of incredible speed and maneuverability. This cone-shaped vehicle can potentially fly just as well anywhere it may be, whether air, water or space, without leaving any heat signatures. It can achieve this by creating a quantum vacuum around itself with a very dense polarized energy field. This vacuum would allow it to repel any molecule the craft comes in contact with, no matter the medium. Manipulating "quantum field fluctuations in the local vacuum energy state," would help reduce the craft's inertia. The polarized vacuum would dramatically decrease any elemental resistance and lead to "extreme speeds," claims the paper.
Not only that, if the vacuum-creating technology can be engineered, we'd also be able to "engineer the fabric of our reality at the most fundamental level," states the patent. This would lead to major advancements in aerospace propulsion and generating power. Not to mention other reality-changing outcomes that come to mind.
Among Pais's other patents are inventions that stem from similar thinking, outlining pieces of technology necessary to make his creations come to fruition. His paper presented in 2019, titled "Room Temperature Superconducting System for Use on a Hybrid Aerospace Undersea Craft," proposes a system that can achieve superconductivity at room temperatures. This would become "a highly disruptive technology, capable of a total paradigm change in Science and Technology," conveys Pais.
High frequency gravitational wave generator.
Credit: Dr. Salvatore Pais
Another invention devised by Pais is an electromagnetic field generator that could generate "an impenetrable defensive shield to sea and land as well as space-based military and civilian assets." This shield could protect from threats like anti-ship ballistic missiles, cruise missiles that evade radar, coronal mass ejections, military satellites, and even asteroids.
Dr. Pais's ideas center around the phenomenon he dubbed "The Pais Effect". He referred to it in his writings as the "controlled motion of electrically charged matter (from solid to plasma) via accelerated spin and/or accelerated vibration under rapid (yet smooth) acceleration-deceleration-acceleration transients." In less jargon-heavy terms, Pais claims to have figured out how to spin electromagnetic fields in order to contain a fusion reaction – an accomplishment that would lead to a tremendous change in power consumption and an abundance of energy.
According to his bio in a recently published paper on a new Plasma Compression Fusion Device, which could transform energy production, Dr. Pais is a mechanical and aerospace engineer working at the Naval Air Warfare Center Aircraft Division (NAWCAD), which is headquartered in Patuxent River, Maryland. Holding a Ph.D. from Case Western Reserve University in Cleveland, Ohio, Pais was a NASA Research Fellow and worked with Northrop Grumman Aerospace Systems. His current Department of Defense work involves his "advanced knowledge of theory, analysis, and modern experimental and computational methods in aerodynamics, along with an understanding of air-vehicle and missile design, especially in the domain of hypersonic power plant and vehicle design." He also has expert knowledge of electrooptics, emerging quantum technologies (laser power generation in particular), high-energy electromagnetic field generation, and the "breakthrough field of room temperature superconductivity, as related to advanced field propulsion."
Suffice it to say, with such a list of research credentials that would make Nikola Tesla proud, Dr. Pais seems well-positioned to carry out groundbreaking work.
A craft using an inertial mass reduction device.
Credit: Salvatore Pais
The patents won't necessarily lead to these technologies ever seeing the light of day. The research has its share of detractors and nonbelievers among other scientists, who think the amount of energy required for the fields described by Pais and his ideas on electromagnetic propulsions are well beyond the scope of current tech and are nearly impossible. Yet investigators at The War Zone found comments from Navy officials that indicate the inventions are being looked at seriously enough, and some tests are taking place.
If you'd like to read through Pais's patents yourself, check them out here.
Laser Augmented Turbojet Propulsion System
Credit: Dr. Salvatore Pais
- The history of AI shows boom periods (AI summers) followed by busts (AI winters).
- The cyclical nature of AI funding is due to hype and promises not fulfilling expectations.
- This time, we might enter something resembling an AI autumn rather than an AI winter, but fundamental questions remain if true AI is even possible.
The dream of building a machine that can think like a human stretches back to the origins of electronic computers. But ever since research into artificial intelligence (AI) began in earnest after World War II, the field has gone through a series of boom and bust cycles called "AI summers" and "AI winters."
Each cycle begins with optimistic claims that a fully, generally intelligent machine is just a decade or so away. Funding pours in and progress seems swift. Then, a decade or so later, progress stalls and funding dries up. Over the last ten years, we've clearly been in an AI summer as vast improvements in computing power and new techniques like deep learning have led to remarkable advances. But now, as we enter the third decade of the 21st century, some who follow AI feel the cold winds at their back leading them to ask, "Is Winter Coming?" If so, what went wrong this time?
How to build an A.I. brain that can conceive of itself | Joscha Bach | Big Think www.youtube.com
A brief history of AI
To see if the winds of winter are really coming for AI, it is useful to look at the field's history. The first real summer can be pegged to 1956 and the famous Dartmouth University Workshop where one of the field's pioneers, John McCarthy, coined the term "artificial intelligence." The conference was attended by scientists like Marvin Minsky and H. A. Simon, whose names would go on to become synonymous with the field. For those researchers, the task ahead was clear: capture the processes of human reasoning through the manipulation of symbolic systems (i.e., computer programs).
Unless we are talking about very specific tasks, any 6-year-old is infinitely more flexible and general in his or her intelligence than the "smartest" Amazon robot.
Throughout the 1960s, progress seemed to come swiftly as researchers developed computer systems that could play chess, deduce mathematical theorems, and even engage in simple discussions with a person. Government funding flowed generously. Optimism was so high that, in 1970, Minsky famously proclaimed, "In three to eight years we will have a machine with the general intelligence of a human being."
By the mid 1970s, however, it was clear that Minsky's optimism was unwarranted. Progress stalled as many of the innovations of the previous decade proved too narrow in their applicability, seeming more like toys than steps toward a general version of artificial intelligence. Funding dried up so completely that researchers soon took pains not to refer to their work as AI, as the term carried a stink that killed proposals.
The cycle repeated itself in the 1980s with the rise of expert systems and the renewed interest in what we now call neural networks (i.e., programs based on connectivity architectures that mimic neurons in the brain). Once again, there was wild optimism and big increases in funding. What was novel in this cycle was the addition of significant private funding as more companies began to rely on computers as essential components of their business. But, once again, the big promises were never realized, and funding dried up again.
AI: Hype vs. reality
The AI summer we're currently experiencing began sometime in the first decade of the new millennium. Vast increases in both computing speed and storage ushered in the era of deep learning and big data. Deep learning methods use stacked layers of neural networks that pass information to each other to solve complex problems like facial recognition. Big data provides these systems with vast oceans of examples (like images of faces) to train on. The applications of this progress are all around us: Google Maps give you near-perfect directions; you can talk with Siri anytime you want; IBM's Deep Think computer beat Jeopardy's greatest human champions.
In response, the hype rose again. True AI, we were told, must be just around the corner. In 2015, for example, The Guardian reported that self-driving cars, the killer app of modern AI, was close at hand. Readers were told, "By 2020 you will become a permanent backseat driver." And just two years ago, Elon Musk claimed that by 2020 "we'd have over a million cars with full self-driving software."
The general intelligence — i.e., the understanding — we humans exhibit may be inseparable from our experiencing. If that's true, then our physical embodiment, enmeshed in a context-rich world, may be difficult if not impossible to capture in symbolic processing systems.
By now, it's obvious that a world of fully self-driving cars is still years away. Likewise, in spite of the remarkable progress we've made in machine learning, we're still far from creating systems that possess general intelligence. The emphasis is on the term general because that's what AI really has been promising all these years: a machine that's flexible in dealing with any situation as it comes up. Instead, what researchers have found is that, despite all their remarkable progress, the systems they've built remain brittle, which is a technical term meaning "they do very wrong things when given unexpected inputs." Try asking Siri to find "restaurants that aren't McDonald's." You won't like the results.
Unless we are talking about very specific tasks, any 6-year-old is infinitely more flexible and general in his or her intelligence than the "smartest" Amazon robot.
Even more important is the sense that, as remarkable as they are, none of the systems we've built understand anything about what they are doing. As philosopher Alva Noe said of Deep Think's famous Jeopardy! victory, "Watson answered no questions. It participated in no competition. It didn't do anything. All the doing was on our side. We played Jeapordy! with Watson." Considering this fact, some researchers claim that the general intelligence — i.e., the understanding — we humans exhibit may be inseparable from our experiencing. If that's true, then our physical embodiment, enmeshed in a context-rich world, may be difficult if not impossible to capture in symbolic processing systems.
Not the (AI) winter of our discontent
Thus, talk a of a new AI winter is popping up again. Given the importance of deep learning and big data in technology, it's hard to imagine funding for these domains drying up any time soon. What we may be seeing, however, is a kind of AI autumn when researchers wisely recalibrate their expectations and perhaps rethink their perspectives.
A new study explores how investors' behavior is affected by participating in online communities, like Reddit's WallStreetBets.
- The study found evidence that "hype" over assets is psychologically contagious among investors in online communities.
- This hype is self-perpetuating: A small group of investors hypes an asset, bringing in new investors, until growth becomes unsteady and a price crash ensues.
- The researchers suggested that these new kinds of self-organized, social media-driven investment behaviors are unlikely to disappear anytime soon.
Social media has reshaped human behavior in ways we're only starting to understand. The proliferation of online communities has helped spawn novel strategies for promoting political causes, conducting business, finding sex and love, and transforming culture.
Could online communities also transform behavior in the financial world?
That's one of the key questions explored in a new study published on the preprint server arXiv. Titled "Reddit's self-organised bull runs: Social contagion and asset prices," the study used discussion data from the subreddit WallStreetBets to analyze relationships between the price of stocks and "hype" among online retail investors.
Hype is nothing new in the investing world. But the researchers noted that there seems to be something novel about the short squeeze of GameStop's stock in January, when the price of the stock rose tenfold, thanks largely to self-organized retail investors from WallStreetBets.
"As academics and regulators alike grapple with the implications, many wonder whether large-scale coordination among retail investors is the new 'modus operandi,' or a one-off fluke," the researchers wrote. "We argue that this is a new manifestation of a well-established global phenomenon."
To better understand how online hype is associated with stock prices, the researchers focused on two social components of hype: contagion and consensus. Contagion refers to investors spreading interest in an asset among each other, while consensus refers to their ability to agree on whether to buy or sell an asset.
The analysis found empirical evidence that both contagion and consensus emerge in online communities like WallStreetBets. In other words, investors spread sentiments about future stock performance to other investors, and then they cohere around investment strategies.
Popularity over fundamentals
The findings suggest that an asset's popularity, not its fundamentals, is paramount to many investors.
"Our results consistently show that investors become interested in discussing an asset, not because of fundamentals, but because other users discuss it," the researchers wrote. "Subsequently, this paper tests whether an individual's sentiment about future asset performance [is] affected by those of others. We find that this is the case: people look to their peers to form an opinion about an asset's potential."
To find evidence for social contagion among online investors, the researchers compiled a large dataset of posts and comments submitted to WallStreetBets. The goal was to analyze whether investors' past comments or posts about a given stock, such as Tesla, had a predictable effect on future discussions of that asset within WallStreetBets.
After conducting a regression analysis, the results suggest that hype is socially contagious and cyclical. The cycle usually plays out like this: A small group of investors hypes an asset. This attracts a larger group of investors who join the discussions.
But eventually, too many investors have joined the discussion, and fewer new investors are buying into the hype. As investors lose interest, they spend less time discussing (or "spreading") the asset on the forum, and they turn to new opportunities. The process is similar to a virus: As enough people become infected, they reach herd immunity, and the virus (hype) dies out.
So, does this process affect the stock price, and if so, how? The researchers said it was difficult to establish causality between hype and actual market activity. After all, they didn't have access to the trading records of subscribers to WallStreetBets.
But their model did show that activity on WallStreetBets was able to explain "significant variance" in trading volumes for the most-discussed assets on the forum. This suggests that when social contagion is strong for a given asset, consensus is strong too.
On the stock chart, consensus may start off bullish (or positively): As hype spreads, there's a slow, steady run-up in price. But the growth eventually becomes unstable and is followed by a crash and a period of volatility.
"The price crash stems from panic selling, as investors turn nervous in the face of volatility," the researchers wrote.
Bad news spreads faster than good news
Interestingly, the analysis found that bearish (or negative) sentiments were significantly more contagious on WallStreetBets.
"The data demonstrates that authors who previously commented on a bearish post are 47.7% more likely to express bearish over neutral sentiments, and 18.1% less likely to express bullish sentiments over neutral sentiments. Similarly, but less markedly, authors who previously commented on at least one bullish submission are 9.4% more likely to write a bullish submission, yet 11.3% less likely to write a bearish one."
The researchers said that the changing investing climate and widely available online data offers "promising opportunities for future research."
"As social media galvanizes a larger pool of retail investors with the potential for exciting stock market gambles, it is crucial to understand how social dynamics can impact asset prices," the researchers wrote. "With the first publicly acclaimed victory of Main Street over Wall Street, in the form of the GameStop short squeeze, it is unlikely that socially-driven asset volatility will simply disappear."
A 19th-century surveying mistake kept lumberjacks away from what is now Minnesota's largest patch of old-growth trees.