Category Archives: Web Article Review

It’s 1984 in Russia

I like these explainer type articles in The Week. This one makes two interesting claims about Russia and Putin, the first of which I had kind of arrive at myself and the second of which I don’t recall ever hearing before, although it seems important.

First, Russia is a desperately poor country and Putin is diverting its extremely limited resources to military adventures in an attempt to look strong to the domestic population.

Putin has sought to bolster Russia’s power against the encroachment of the West, picking fights with nearby Georgia and Ukraine and intervening in Syria as a show of strength. His proud nationalism has made him very popular among Russians, although the international sanctions brought on by his seizure of Crimea — combined with a sharp downturn in oil prices — have badly damaged Russia’s fragile economy. Russia’s gross domestic product tumbled from $2.2 trillion in 2013 to $1.3 trillion in 2015 — lower than that of Italy, Brazil, or Canada. Only 27 percent of Russians have any savings at all, and the average Russian now spends half his or her money on food. Few Russians, however, complain.

Second, Putin, who is a KGB agent trained in East Germany, came to power through a KGB-orchestrated false flag operation that killed hundreds of Russian citizens and was used to justify a war.

How did he come to power?
Through the work of the FSB, successor to the Soviet KGB. Putin was an unknown FSB operative when the agency strong-armed an ailing President Boris Yeltsin into picking him as prime minister in August 1999. Putin had spent five years as a spy in East Germany. Just a month after he took office, a series of apartment bombings shattered Moscow, killing about 300 people. The FSB blamed Chechen extremists, although there is strong evidence the spy agency planted the bombs itself; the carnage served as pretext for a second ruthless war to put down the restive Muslim province of Chechnya. Putin became the face of the battle, vowing in his characteristically crude language to eliminate all the terrorists, “wherever they hide, even on the crapper.” By the end of the year, Chechnya had been laid waste, thousands of Chechen civilians were dead, and Yeltsin had named the now popular Putin as his successor as president…

Alexander Litvinenko, an FSB whistleblower who described how the agency staged the Moscow bombings to bring Putin to power, was poisoned with polonium in London; a British inquiry found that Putin likely personally ordered the hit.

are you smarter than Einstein?

It seems to me that spending your life trying to disprove Einstein is a path to likely disappointment and failure. Nonetheless there are brave souls who dare to challenge (well, tweak maybe…) his theories.

FOR 80 YEARS, scientists have puzzled over the way galaxies and other cosmic structures appear to gravitate toward something they cannot see. This hypothetical “dark matter” seems to outweigh all visible matter by a startling ratio of five to one, suggesting that we barely know our own universe. Thousands of physicists are doggedly searching for these invisible particles.

But the dark matter hypothesis assumes scientists know how matter in the sky ought to move in the first place. At the end of 2016, a series of developments has revived a long-disfavored argument that dark matter doesn’t exist after all. In this view, no missing matter is needed to explain the errant motions of the heavenly bodies; rather, on cosmic scales, gravity itself works in a different way than either Isaac Newton or Albert Einstein predicted.

The latest attempt to explain away dark matter is a much-discussed proposal by Erik Verlinde, a theoretical physicist at the University of Amsterdam who is known for bold and prescient, if sometimes imperfect, ideas. In a dense 51-page paper posted online on Nov. 7, Verlinde casts gravity as a byproduct of quantum interactions and suggests that the extra gravity attributed to dark matter is an effect of “dark energy”—the background energy woven into the space-time fabric of the universe.

Tech vs. Telecom

Are the big telecom companies like AT&T, Comcast, and Verizon tech companies? Or are they giant, lumbering change-averse utilities of yesteryear? Well, they’re sort of in-between. I would like to see Comcast succeed because they are a major employer and providing support to local startups in my city. And yet, I have had awful experiences with them and just dropped them in favor of Verizon. I’ll be happy with Verizon until my introductory promotion runs out.

These companies are not good enough. They are not providing the kind of internet we need at a price we can afford. This article in Wired says Apple, Google, and Facebook will end up eating them alive, by accident.

These tech titans didn’t plan to take down the telcos. But they depend upon you having fast, reliable internet, so they’re bringing everything in-house. This promises to make things drastically better for you as a consumer, so if you hate big telecoms, you’ll feel schadenfreude at their demise. But you might end up with more of the same as the new guard becomes the old guard…

You’ve probably heard about Google Fiber and its shift toward wireless Internet over fiber-optic cables. Google Fi mobile service could be even more radical. Instead of building cell towers, Google resells access to Sprint and T-Mobile networks. Companies like Cricket and TracFone do this too, but Google-Fi lets your phone use the best signal available at any moment…

As new technologies and expanded access to the wireless spectrum drive down the cost of operating cell services, Google and other wireless brokers will be able to create nationwide–even worldwide–networks. That would make wireless service a commodity and shift the balance of power from incumbents like AT&T to companies like Google.

I wonder what major industry will be the next to go down. Will it be the fossil fuel industry challenged by renewables (the coal industry is already close to collapse), the finance industry challenged by upstart new financial tech companies (if they don’t shoot themselves in the foot again first), or the traditional telecoms falling to the new tech giants?

Magic Leap

According to this article in Wired, the “world’s hottest startup” is virtual reality company Magic Leap.

Virtual reality overlaid on the real world in this manner is called mixed reality, or MR. (The goggles are semitransparent, allowing you to see your actual surroundings.) It is more difficult to achieve than the classic fully immersive virtual reality, or VR, where all you see are synthetic images, and in many ways MR is the more powerful of the two technologies.

Magic Leap is not the only company creating mixed-reality technology, but right now the quality of its virtual visions exceeds all others. Because of this lead, money is pouring into this Florida office park. Google was one of the first to invest. Andreessen Horowitz, Kleiner Perkins, and others followed. In the past year, executives from most major media and tech companies have made the pilgrimage to Magic Leap’s office park to experience for themselves its futuristic synthetic reality. At the beginning of this year, the company completed what may be the largest C-round of financing in history: $793.5 million. To date, investors have funneled $1.4 billion into it.

That astounding sum is especially noteworthy because Magic Leap has not released a beta version of its product, not even to developers. Aside from potential investors and advisers, few people have been allowed to see the gear in action, and the combination of funding and mystery has fueled rampant curiosity. But to really understand what’s happening at Magic Leap, you need to also understand the tidal wave surging through the entire tech industry. All the major players—Facebook, Google, Apple, Amazon, Microsoft, Sony, Samsung—have whole groups dedicated to artificial reality, and they’re hiring more engineers daily. Facebook alone has over 400 people working on VR. Then there are some 230 other companies, such as Meta, the Void, Atheer, Lytro, and 8i, working furiously on hardware and content for this new platform.

you can sue your city for unsafe streets

According to Streetsblog NYC:

The Court of Appeals, New York’s highest court, ruled that New York City and other municipalities can be held liable for failing to redesign streets with a history of traffic injuries and reckless driving…

“This decision is a game-changer,” says Steve Vaccaro, an attorney who represents traffic crash victims. “The court held that departments of transportation can be held liable for harm caused by speeding drivers, where the DOT fails to install traffic-calming measures even though it is aware of dangerous speeding, unless the DOT has specifically undertaken a study and determined that traffic calming is not required…”

Vaccaro said the decision “will create an affirmative obligation on the DOT’s part to — at the very least — conduct studies to determine whether infrastructure can reduce traffic violence, and unless such studies indicate otherwise, to install the infrastructure.”

Lawsuits are not the ideal way to do urban planning or protect public safety. They are a last resort. But I support them as one tool in the toolbox when engineers, planners, and public officials are ignoring their ethical obligation to protect the public when they know (or, if they don’t know, are ignorant of knowledge they are ethically obligated to acquire to be a competent professional in their chosen field) there are better, proven alternatives out there.

ride pooling can (maybe) reduce traffic by a lot

Here’s a new study from MIT that says ride sharing and pooling algorithms could theoretically reduce Manhattan rush hour traffic drastically.

On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment

Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. These services present enormous potential for positive societal impacts with respect to pollution, energy consumption, congestion, etc. Current mathematical models, however, do not fully address the potential of ride-sharing. Recently, a large-scale study highlighted some of the benefits of car pooling but was limited to static routes with two riders per vehicle (optimally) or three (with heuristics). We present a more general mathematical model for real-time high-capacity ride-sharing that (i) scales to large numbers of passengers and trips and (ii) dynamically generates optimal routes with respect to online demand and vehicle locations. The algorithm starts from a greedy assignment and improves it through a constrained optimization, quickly returning solutions of good quality and converging to the optimal assignment over time. We quantify experimentally the tradeoff between fleet size, capacity, waiting time, travel delay, and operational costs for low- to medium-capacity vehicles, such as taxis and van shuttles. The algorithm is validated with ∼3 million rides extracted from the New York City taxicab public dataset. Our experimental study considers ride-sharing with rider capacity of up to 10 simultaneous passengers per vehicle. The algorithm applies to fleets of autonomous vehicles and also incorporates rebalancing of idling vehicles to areas of high demand. This framework is general and can be used for many real-time multivehicle, multitask assignment problems.

There are plenty of criticisms of this type of study. The major one is that if you make a particular transportation option faster and/or cheaper, economics dictates that people will automatically switch to it from other options over time, eventually making it less fast and/or less cheap until the various modes are balanced again. The study above (based on my quick skim of the abstract) probably took data from one or a few Manhattan rush hours and asked how it could be rerouted in the most efficient possible way. I don’t fault them for doing the study, which is really interesting. The economics and human behavioral feedback loops that happen over longer periods of time just need to be studied too before policy decisions are made based on results like these.

I don’t necessarily want UberPool to be the answer to all our infrastructure problems. I love the idea of subway and above-ground rail and bus rapid transit as much as the next person. But as the opening of the most recent segment of New York subway recently showed us, these projects are taking decades to build in the U.S. and costing enormous amounts of money. Europe and Asia are doing much better than us, so maybe we could learn some lessons from them, but our recent political challenges shed some doubt on the idea that we can improve any time soon. (Europe generally manages to do somewhat better with high-wage union labor, while some Asian countries build extremely cost-effectively by issuing temporary work visas to low-wage labor from developing countries. There are political and moral issues on both ends of this spectrum, obviously, but the point is the U.S. doesn’t do either approach well. Much like our health care system, we spend 2 or 3 or 5 times more than everyone else and get worse results.)

If the criticism of the study I mentioned above is that demand projections made before the new infrastructure options or technologies are in place are not going to be accurate, that criticism certainly applies to a subway system that takes decades to build. The entire population, land use, and employment pattern of the area served could change in that time, not to mention that whatever technology is chosen is almost guaranteed to be obsolete the day operation begins. With the ride-sharing algorithms, even if the projections are wrong at first at least you have a system that should be easy to adapt and tweak over time. I don’t see why public bus systems and bus rapid transit can’t be integrated into a system like this. And if people want a vehicle to themselves for some trips sometimes, the algorithms and pricing schemes should be able to accommodate that. You could even imagine an algorithm managing passenger vehicles, freight and delivery vehicles in urban areas so they are less in conflict with other at various times of day and night. The algorithms could be run by government or non-profit entities if we are really afraid of private control, or private algorithms and entities could be forced to communicate and coordinate with one another.

supersonic jets coming back soon

Virgin has a prototype commercial supersonic jet that it plans to test soon. One thing on my bucket list has always been to take a trans-Atlantic cruise to Europe and then a supersonic jet back.

The manufacturing team for Branson’s Virgin Galactic company is working with Boom Supersonic to test a prototype next year of a passenger plane that can fly at Mach 2.2, more than twice the speed of a typical commercial jet…

Instead of spending seven hours and paying up to $5,500 for a flight from New York to London on a Boeing 747, travelers can spend about $2,500 for a three-hour flight to cross the Atlantic on a supersonic jet, according to Boom.

election hacking

Looking for the declassified report on Russian election hacking. Look no further. Here are a couple juicy phrases from the whopping 25 page report:

We assess Russian President Vladimir Putin ordered an influence campaign in 2016 aimed at the US presidential election. Russia’s goals were to undermine public faith in the US democratic process, denigrate Secretary Clinton, and harm her electability and potential presidency. We further assess Putin and the Russian Government developed a clear preference for President-elect Trump. We have high confidence in these judgments.

We also assess Putin and the Russian Government aspired to help President-elect Trump’s election chances when possible by discrediting Secretary Clinton and publicly contrasting her unfavorably to him. All three agencies agree with this judgment. CIA and FBI have high confidence in this judgment; NSA has moderate confidence…

Russian intelligence obtained and maintained access to elements of multiple US state or local electoral boards. DHS assesses that the types of systems Russian actors targeted or compromised were not involved in vote tallying.

I agree with Trump on virtually nothing, but I agree with him on one thing. These are the same people who brought us weapons of mass destruction. Which will always undermine their credibility in my eyes, along with the President, the State Department, Congress and the New York Times. I was a naive, trusting, patriotic young adult when I figured out that I had been lied to by basically all the branches of government and the media I trusted to keep an eye on them. And that was long before I read Legacy of Ashes and realized just how pathetic the CIA is and just how good the KGB is and always has been. And of course, that is who we are dealing with here.

Meddling in another sovereign country’s elections is one the worst things a country could do, right? Certainly the greatest democracy in the world, let alone the greatest democracy in the history of the world, would never do that, right? Well, the CIA isn’t good at spying, which is why the U.S. lost the Korean War, the Vietnam War, the Afghanistan War, and the Iraq War. They never really understood the motivations of the Soviet Union because they had no real intelligence on it whatsoever, whereas the KGB infiltrated the U.S. government at the highest levels all along. But the CIA was always actually pretty good at influencing elections and they have done it often, sometimes with and sometimes without the knowledge of the President and Congress.

Here’s an article about the U.S. and Russia meddling in elections around the world. So I don’t like the fact that the Russians meddled in our election, and I hate the outcome of the election, but there is some element of hypocrisy in our government expressing such moral outrage about it.

Partisan electoral interventions by the great powers: Introducing the PEIG Dataset

Six decades of rigorous scholarship have greatly increased our knowledge about the causes and effects of various military and non-military forms of foreign interventions.

One blind spot in the international relations (IR) literature on interventions has been interventions designed to affect election results in foreign countries; i.e. as most famously occurred in Italy’s 1948 parliamentary election and more recently in the 2009 Afghan presidential elections. Despite a few, very recent exceptions (Corstange and Marinov, 2012; Levin, 2016; Shulman and Bloom, 2012), such interventions have not been studied by quantitative IR scholars who have preferred to focus on more violent or usually more overt types of interventions.2

However by not studying partisan electoral interventions, quantitative IR scholars miss an important, common form of intervention. Between 1946 and 2000, the US and the Soviet Union/Russia have intervened in about one of every nine competitive national-level executive elections. Partisan electoral interventions have been found to have had significant effects on election results, frequently determining the identity of the winner (Levin, 2016). Overt interventions of this kind have also been found to have significant effects on the views of the target public toward the intervener (Corstange and Marinov, 2012). Some qualitative scholars who have studied particular cases of electoral interventions at times credit, or blame, them with playing an important role in the subsequent nature of the regime in the target country and influencing the direction of its domestic and foreign policies (Rabe, 2006: chap. 5; Trachtenberg, 1999: 128–132). With the growing realization among IR scholars of the importance of regime type (Huth and Allee, 2002; Park, 2013 Ray, 1995; Reiter and Stam, 1998; Russett, 1993) and, more recently, the nature of the leader in power (Chiozza and Choi, 2003; Colgan, 2013; Horowitz, 2014; Keller and Foster, 2010; Potter, 2007) for their countries’ foreign and domestic policies, electoral interventions are a factor that cannot be ignored.

EIA Annual Energy Outlook 2017

The U.S. Energy Information Administration has released its annual energy outlook 2017. In their economic modeling exercises, some of the interesting things that happen are that oil demand stays relatively flat, natural gas demand continues to grow, coal continues to fall, and renewables continue to grow through 2040 although they don’t reach a higher share of the total supply than natural gas or oil. Carbon emissions fall or stay relatively flat in most scenarios, which is interesting but remember that flat emissions that are still too high will cause atmospheric greenhouse gases to continue growing at a steady rate. Some of the most interesting graphs are emissions intensity per dollar of economic output and emissions per unit of energy used, which both fall over time but again this does not guarantee that the atmosphere is healing itself, only becoming sicker at a slower rate.

Thomas More’s utopia

Here’s an interesting article on Thomas More’s utopia from the 1500s. He envisioned a series of economically specialized medium-scale cities (a couple hundred thousand people, keeping in mind a million-person city was enormous at the time and there were only a few in the world) separated by farm and natural lands and connected by transportation links.