A plan to offshore

Tuesday, February 17th, 2009

David Cook and Roger Green have a plan to offshore IT jobs — just 3 miles out — which might have made more sense a few years ago:

Roger Green is a software entrepreneur. David Cook was once a supertanker skipper who spent 15 years hauling crude oil through the world’s sea lanes. Now the two men have announced a remarkable venture called SeaCode, a company that plans to hire 600 superb software designers from every corner of the world and house them in a luxury cruise ship just out of reach of US immigration law — but close enough to bid on multimillion-dollar US software contracts.

How Not To Sort By Rating

Monday, February 16th, 2009

Even Miller explains how not to sort by rating:

Wrong Solution 1
Score = (Positive ratings) – (Negative ratings)

Why it is wrong: Suppose one item has 600 positive ratings and 400 negative ratings: 60% positive. Suppose item two has 5,500 positive ratings and 4,500 negative ratings: 55% positive. This algorithm puts item two (score = 1000, but only 55% positive) above item one (score = 200, and 60% positive). WRONG.

Sites that make this mistake: Urban Dictionary

Wrong Solution 2
Score = Average rating = (Positive ratings) / (Total ratings)

Why it is wrong: Average rating works fine if you always have a ton of ratings, but suppose item 1 has 2 positive ratings and 0 negative ratings. Suppose item 2 has 100 positive ratings and 1 negative rating. This algorithm puts item two (tons of positive ratings) below item one (very few positive ratings). WRONG.

Sites that make this mistake: Amazon.com

So, what’s the right way?

Correct Solution
Score = Lower bound of Wilson score confidence interval for a Bernoulli parameter

Say what: We need to balance the proportion of positive ratings with the uncertainty of a small number of observations. Fortunately, the math for this was worked out in 1927 by Edwin B. Wilson. What we want to ask is: Given the ratings I have, there is a 95% chance that the “real” fraction of positive ratings is at least what? Wilson gives the answer. Considering only positive and negative ratings (i.e. not a 5-star scale), the lower bound on the proportion of positive ratings is given by:


(For a lower bound use minus where it says plus/minus.) Here p is the observed fraction of positive ratings, z?/2 is the (1-?/2) quantile of the standard normal distribution, and n is the total number of ratings.

Google PowerMeter is far more strategic than Google is letting-on

Monday, February 16th, 2009

Cringely claims that Google PowerMeter is far more strategic than Google is letting-on:

So this is Google doing its bit for the environment in exchange for which they learn even more about our behavior, right?
Wrong. It’s much more than that.

Google’s PowerMeter is a Trojan horse — a way to become a de facto Internet Service Provider for potentially millions of homes.

Several years ago Google made a $100 million investment in a suburban Washington, DC company called Current Technologies, which is America’s leading provider of both smart electric metering services (that’s what the Google PowerMeter is supposed to be) and power line Internet service based in part on the HomePlug networking standard.

Current’s business model was simple. They’d give participating utilities a way to both measure and control local power consumption pretty much as described above. Oh and, by the way, the meter connection could also be used to provide Internet service, potentially to 100 percent of a neighborhood since pretty much everyone buys electric power. Throw Internet on the power bill, then maybe digital cable service, too. Eventually the power companies would take on the cable and telephone companies to fight for broadband hegemony.

Only it isn’t really happening that way. Current is doing deals with utilities, but most of those utilities aren’t going so far as to offer broadband Internet. They are just reading meters, thank you, which isn’t bad unless your profit is supposed to come from the Internet and cable competitor side. So Current Technologies is struggling somewhat and Google’s investment in that company hasn’t grown as much as either company would like.

Enter the Google PowerMeter, which is both an intelligent power meter and an Internet gateway, just like the original vision at Current Technologies.

Electric utilities are enthusiastically installing backbone capability to serve these smart meters. And contrary to popular belief, the network on the power company’s side of that medium-voltage transformer on your telephone pole is usually optical fiber,not Broadband over Power Lines (BPL) which amateur radio operators hate so much. The fact is that BPL has real distance limitations and it is just easier to string fiber alongside the medium and high-voltage lines.

So the utilities partner with Google to install these boxes, ideally in every home. They install enough fiber for gigabit service to the medium voltage transformer with HomePlug or WiFi into the home. And the whole thing interfaces to Google at the power company’s data center where Google will install proxy servers and routers and connect to the Internet backbone.
Eventually Google — not the electric utility — throws the switch on consumer Internet access, IP TV, and VoIP phones, which the electric companies could have done — should have done — on their own but generally couldn’t be bothered to.

Ideally Google lights the whole town with Internet with the utility happily picking-up most of the infrastructure costs yet with Google becoming the ISP.

Now that’s a heck of a deal.

The No-Stats All-Star

Monday, February 16th, 2009

Michael Lewis (Moneyball) calls Shane Battier the no-stats all-star:

It was, and is, far easier to spot what Battier doesn’t do than what he does. His conventional statistics are unremarkable: he doesn’t score many points, snag many rebounds, block many shots, steal many balls or dish out many assists. On top of that, it is easy to see what he can never do: what points he scores tend to come from jump shots taken immediately after receiving a pass. “That’s the telltale sign of someone who can’t ramp up his offense,” Morey says. “Because you can guard that shot with one player. And until you can’t guard someone with one player, you really haven’t created an offensive situation. Shane can’t create an offensive situation. He needs to be open.” For fun, Morey shows me video of a few rare instances of Battier scoring when he hasn’t ­exactly been open. Some large percentage of them came when he was being guarded by an inferior defender — whereupon Battier backed him down and tossed in a left jump-hook. “This is probably, to be honest with you, his only offensive move,” Morey says. “But look, see how he pump fakes.” Battier indeed pump faked, several times, before he shot over a defender. “He does that because he’s worried about his shot being blocked.” Battier’s weaknesses arise from physical limitations. Or, as Morey puts it, “He can’t dribble, he’s slow and hasn’t got much body control.”

Battier’s game is a weird combination of obvious weaknesses and nearly invisible strengths. When he is on the court, his teammates get better, often a lot better, and his opponents get worse — often a lot worse. He may not grab huge numbers of rebounds, but he has an uncanny ability to improve his teammates’ rebounding. He doesn’t shoot much, but when he does, he takes only the most efficient shots. He also has a knack for getting the ball to teammates who are in a position to do the same, and he commits few turnovers. On defense, although he routinely guards the N.B.A.’s most prolific scorers, he significantly reduces their shooting percentages. At the same time he somehow improves the defensive efficiency of his teammates — probably, Morey surmises, by helping them out in all sorts of subtle ways. “I call him Lego,” Morey says. “When he’s on the court, all the pieces start to fit together. And everything that leads to winning that you can get to through intellect instead of innate ability, Shane excels in. I’ll bet he’s in the hundredth percentile of every category.”

There are other things Morey has noticed too, but declines to discuss as there is right now in pro basketball real value to new information, and the Rockets feel they have some. What he will say, however, is that the big challenge on any basketball court is to measure the right things. The five players on any basketball team are far more than the sum of their parts; the Rockets devote a lot of energy to untangling subtle interactions among the team’s elements. To get at this they need something that basketball hasn’t historically supplied: meaningful statistics. For most of its history basketball has measured not so much what is important as what is easy to measure — points, rebounds, assists, steals, blocked shots — and these measurements have warped perceptions of the game. (“Someone created the box score,” Morey says, “and he should be shot.”) How many points a player scores, for example, is no true indication of how much he has helped his team. Another example: if you want to know a player’s value as a rebounder, you need to know not whether he got a rebound but the likelihood of the team getting the rebound when a missed shot enters that player’s zone.

There is a tension, peculiar to basketball, between the interests of the team and the interests of the individual. The game continually tempts the people who play it to do things that are not in the interest of the group. On the baseball field, it would be hard for a player to sacrifice his team’s interest for his own. Baseball is an individual sport masquerading as a team one: by doing what’s best for himself, the player nearly always also does what is best for his team. “There is no way to selfishly get across home plate,” as Morey puts it. “If instead of there being a lineup, I could muscle my way to the plate and hit every single time and damage the efficiency of the team — that would be the analogy. Manny Ramirez can’t take at-bats away from David Ortiz. We had a point guard in Boston who refused to pass the ball to a certain guy.” In football the coach has so much control over who gets the ball that selfishness winds up being self-defeating. The players most famous for being selfish — the Dallas Cowboys’ wide receiver Terrell Owens, for instance — are usually not so much selfish as attention seeking. Their sins tend to occur off the field.

It is in basketball where the problems are most likely to be in the game — where the player, in his play, faces choices between maximizing his own perceived self-interest and winning. The choices are sufficiently complex that there is a fair chance he doesn’t fully grasp that he is making them.

Taking a bad shot when you don’t need to is only the most obvious example. A point guard might selfishly give up an open shot for an assist. You can see it happen every night, when he’s racing down court for an open layup, and instead of taking it, he passes it back to a trailing teammate. The teammate usually finishes with some sensational dunk, but the likelihood of scoring nevertheless declined. “The marginal assist is worth more money to the point guard than the marginal point,” Morey says. Blocked shots — they look great, but unless you secure the ball afterward, you haven’t helped your team all that much. Players love the spectacle of a ball being swatted into the fifth row, and it becomes a matter of personal indifference that the other team still gets the ball back. Dikembe Mutombo, Houston’s 42-year-old backup center, famous for blocking shots, “has always been the best in the league in the recovery of the ball after his block,” says Morey, as he begins to make a case for Mutombo’s unselfishness before he stops and laughs. “But even to Dikembe there’s a selfish component. He made his name by doing the finger wag.” The finger wag: Mutombo swats the ball, grabs it, holds it against his hip and wags his finger at the opponent. Not in my house! “And if he doesn’t catch the ball,” Morey says, “he can’t do the finger wag. And he loves the finger wag.” His team of course would be better off if Mutombo didn’t hold onto the ball long enough to do his finger wag. “We’ve had to yell at him: start the break, start the break — then do your finger wag!”

Hockey has used a plus-minus stat for years. Now basketball is catching on:

One well-known statistic the Rockets’ front office pays attention to is plus-minus, which simply measures what happens to the score when any given player is on the court. In its crude form, plus-minus is hardly perfect: a player who finds himself on the same team with the world’s four best basketball players, and who plays only when they do, will have a plus-minus that looks pretty good, even if it says little about his play. Morey says that he and his staff can adjust for these potential distortions — though he is coy about how they do it — and render plus-minus a useful measure of a player’s effect on a basketball game. A good player might be a plus 3 — that is, his team averages 3 points more per game than its opponent when he is on the floor. In his best season, the superstar point guard Steve Nash was a plus 14.5. At the time of the Lakers game, Battier was a plus 10, which put him in the company of Dwight Howard and Kevin Garnett, both perennial All-Stars. For his career he’s a plus 6. “Plus 6 is enormous,” Morey says. “It’s the difference between 41 wins and 60 wins.” He names a few other players who were a plus 6 last season: Vince Carter, Carmelo Anthony, Tracy McGrady.

Battier’s strengths are subtle:

Before the Rockets traded for Battier, the front-office analysts obviously studied his value. They knew all sorts of details about his efficiency and his ability to reduce the efficiency of his opponents. They knew, for example, that stars guarded by Battier suddenly lose their shooting touch. What they didn’t know was why. Morey recognized Battier’s effects, but he didn’t know how he achieved them. Two hundred or so basketball games later, he’s the world’s expert on the subject — which he was studying all over again tonight. He pointed out how, instead of grabbing uncertainly for a rebound, for instance, Battier would tip the ball more certainly to a teammate. Guarding a lesser rebounder, Battier would, when the ball was in the air, leave his own man and block out the other team’s best rebounder. “Watch him,” a Houston front-office analyst told me before the game. “When the shot goes up, he’ll go sit on Gasol’s knee.” (Pau Gasol often plays center for the Lakers.) On defense, it was as if Battier had set out to maximize the misery Bryant experiences shooting a basketball, without having his presence recorded in any box score. He blocked the ball when Bryant was taking it from his waist to his chin, for instance, rather than when it was far higher and Bryant was in the act of shooting. “When you watch him,” Morey says, “you see that his whole thing is to stay in front of guys and try to block the player’s vision when he shoots. We didn’t even notice what he was doing until he got here. I wish we could say we did, but we didn’t.”

People often say that Kobe Bryant has no weaknesses to his game, but that’s not really true. Before the game, Battier was given his special package of information. “He’s the only player we give it to,” Morey says. “We can give him this fire hose of data and let him sift. Most players are like golfers. You don’t want them swinging while they’re thinking.” The data essentially broke down the floor into many discrete zones and calculated the odds of Bryant making shots from different places on the court, under different degrees of defensive pressure, in different relationships to other players — how well he scored off screens, off pick-and-rolls, off catch-and-shoots and so on. Battier learns a lot from studying the data on the superstars he is usually assigned to guard.

Why diversifying does not earn you a big bonus

Sunday, February 15th, 2009

Paul Wilmott explains why diversifying does not earn you a big bonus:

Suppose that you have 100 colleagues, each trading with $10 million. Bearing in mind Einstein’s advice, we are going to keep things simple, so as to make the mathematics as transparent as possible, and assume that they are betting on a coin toss. And, crucially, they are all betting on heads on the same toss of the same unbiased coin — it doesn’t get more undiversified than that.

It’s 50-50 whether they win or lose. If the single toss comes up heads then they all win, and the bank makes 100 times $10 million, of which each trader perhaps gets a tidy $2 million bonus. That’s their down payment on a decent yacht. Everyone’s happy: traders, management, shareholders and depositors. But if it comes up tails, they lose, and the bank goes bust. But while the traders and management only have to find new jobs, the shareholders and the depositors potentially face losing their life savings.

You come along, and, thanks to your college education, you have found a much better trade than your colleagues. Let’s say that you are betting on another, independent coin — but one that is biased. This coin has a 75 percent chance of heads. And you’ve also got $10 million to invest.

Let’s look at two possibilities: first, that you do the responsible thing of betting the good odds on the biased coin, and second, that you bet on the heads on the 50-50 toss just like your colleagues. I say that the first case is “responsible” for two reasons: one because it’s a better bet than that of your colleagues and so will increase the bank’s expected return; and two because it also helps the bank diversify. That’s classic Modern Portfolio Theory, and is also common sense.

O.K., so you bet $10 million on your coin. What is the probability of your getting your $2 million bonus? Easy, it’s just the probability of getting heads, 75 percent, isn’t it? Well, no, it’s not. Yes, there’s a 75 percent chance of your making money for your bank, but if your colleagues have meanwhile tossed a tail, your bank is broke and no one’s getting a bonus, even you. They’ve cost the bank a billion dollars, and you’ve made it a mere $10 million. But what if you toss tails on the biased coin when the others toss heads? The others get their bonus, but you’ve just lost $10 million, what a terrible trader you must be, and are shown the door.

No, the only way to get that bonus is if both you and the others make winning trades — that is, if both coins land heads up. And the probability of that is 50 percent times 75 percent — that’s 37.5 percent. So, even though you have a biased coin working in your favor, the chance of you getting a bonus is still substantially less than half.

By now you can probably see where I’m going with this. Suppose that instead of betting on the biased coin you join in with all your colleagues and bet on the same toss of the first coin. Now you all win or lose together, the odds are even and the probability of getting your bonus is 50 percent. This is significantly higher than if you’d done the “responsible” thing of helping your bank to increase its expected return and decrease its risk.

This example makes it clear that your interests and those of the shareholders and depositors can be complete opposites. They probably didn’t teach you that at business school.

Actually, I’m pretty sure they do teach you that business school.

Wall Street Can’t Count

Friday, February 13th, 2009

Cringely notes that Wall Street Can’t Count and shares this graphic as evidence:

My first thought, before studying it, was that market cap might not be the right metric for comparing enterprises that have just rejiggered their capital structures. Market cap takes into account equity, but an enterprise is also financed through debt — which can become substantial after, say, receiving a bailout.

But I was thinking far too deeply.

The real problem is that the graphic, produced by J. P. Morgan and distributed by Bloomberg, represents market caps as circles with diameters proportional to the dollar value, when your eye naturally assumes that the two-dimensional circle’s area should be proportional to the dollar value.

So they’ve squared all the values, vastly magnifying the already levered-up changes in market cap. Smooth.

Let’s Get It On — for Free

Friday, February 13th, 2009

In an effort to promote its MP3 store this Valentine’s Day, Amazon is giving away free copies of Marvin Gaye’s Let’s Get It On. Cute.

No, Not Calpis

Thursday, February 12th, 2009

Most Americans know very little about Hinduism, seeing it as a live-and-let-live religion, like Buddhism, but with a peculiar interest in cows. Most Americans are unaware of what hardcore Hindu nationalists are up to, like launching their new cow urine soft drink:

The bovine brew is in the final stages of development by the Cow Protection Department of the Rashtriya Swayamsevak Sangh (RSS), India’s biggest and oldest Hindu nationalist group, according to the man who makes it.

Om Prakash, the head of the department, said the drink – called “gau jal”, or “cow water” – in Sanskrit was undergoing laboratory tests and would be launched “very soon, maybe by the end of this year”.

“Don’t worry, it won’t smell like urine and will be tasty too,” he told The Times from his headquarters in Hardwar, one of four holy cities on the River Ganges. “Its USP will be that it’s going to be very healthy. It won’t be like carbonated drinks and would be devoid of any toxins.”

The drink is the latest attempt by the RSS – which was founded in 1925 and now claims eight million members – to cleanse India of foreign influence and promote its ideology of Hindutva, or Hindu-ness.

Hindus revere cows and slaughtering them is illegal in most of India. Cow dung is traditionally used as a fuel and disinfectant in villages, while cow urine and dung are often consumed in rituals to “purify” those on the bottom rungs of the Hindu caste system.

In 2001, the RSS and its offshoots – which include the opposition Bharatiya Janata Party – began promoting cow urine as a cure for ailments ranging from liver disease to obesity and even cancer.

The movement has often been accused of using more violent methods, such as killing 67 Christians in the eastern state of Orissa last year, and assaulting women in a pub in Mangalore last month. It also has a history of targeting foreign business in India, as in 1994, when it organised a nationwide boycott of multinational consumer goods, including Pepsi and Coca Cola.

The cola brands are popular in India, now one of their biggest markets, but have struggled in recent years to shake off allegations, which they deny, that they contain dangerous levels of pesticide.

Mr Prakash said his drink, by contrast, was made mainly of cow urine, mixed with a few medicinal and ayurvedic herbs. He said it would be “cheap”, but declined to give further details about its price or ingredients until it was officially launched.

When I first heard this story, I immediately thought of Calpis, the Japanese soft drink:

Calpis (???? Karupisu) is a Japanese uncarbonated soft drink, manufactured by Calpis Co., Ltd. (???????? Karupisu Kabushiki-gaisha), headquartered in Shibuya, Tokyo. The beverage has a light, somewhat milky, and slightly acidic flavor, similar to plain or vanilla-flavored yogurt, or Yakult. Its ingredients include water, nonfat dry milk, and lactic acid, and it is produced by lactic acid fermentation.
[...]
The name Calpis was actually constructed as a portmanteau, by combining cal from calcium and pis from Sanskrit sarpis (supreme taste). Sarpis is used to described the essense of Buddhist teaching.

I prefer Pocari Sweat.

(Hat tip to Yana.)

In House Software

Thursday, February 12th, 2009

Joel Spolsky briefly wrote in house software at Viacom in New York:

New York was the first place I got to see what most computer programmers do for a living. It’s this scary thing called “in house software.” It’s terrifying. You never want to do in house software. You’re a programmer for a big corporation that makes, oh, I don’t know, aluminum cans, and there’s nothing quite available off the shelf which does the exact kind of aluminum can processing that they need, so they have these in-house programmers, or they hire companies like Accenture and IBM to send them overpriced programmers, to write this software. And there are two reasons this is so frightening: one, because it’s not a very fulfilling career if you’re a programmer, for a list of reasons which I’ll enumerate in a moment, but two, it’s frightening because this is what probably 80% of programming jobs are like, and if you’re not very, very careful when you graduate, you might find yourself working on in-house software, by accident, and let me tell you, it can drain the life out of you.

OK, so, why does it suck to be an in house programmer.

Number one. You never get to do things the right way. You always have to do things the expedient way. It costs so much money to hire these programmers — typically a company like Accenture or IBM would charge $300 an hour for the services of some recent Yale PoliSci grad who took a 6 week course in dot net programming, and who is earning $47,000 a year and hoping that it’ll provide enough experience to get into business school — anyway, it costs so much to hire these programmers that you’re not going to allowed to build things with Ruby on Rails no matter how cool Ruby is and no matter how spiffy the Ajax is going to be. You’re going into Visual Studio, you’re going to click on the wizard, you’re going to drag the little Grid control onto the page, you’re going to hook it up to the database, and presto, you’re done. It’s good enough. Get out of there and onto the next thing.

That’s the second reason these jobs suck: as soon as your program gets good enough, you have to stop working on it. Once the core functionality is there, the main problem is solved, there is absolutely no return-on-investment, no business reason to make the software any better. So all of these in house programs look like a dog’s breakfast: because it’s just not worth a penny to make them look nice. Forget any pride in workmanship or craftsmanship you learned in CS323. You’re going to churn out embarrassing junk, and then, you’re going to rush off to patch up last year’s embarrassing junk which is starting to break down because it wasn’t done right in the first place, twenty-seven years of that and you get a gold watch. Oh, and they don’t give gold watches any more. 27 years and you get carpal tunnel syndrome.

Now, at a product company, for example, if you’re a software developer working on a software product or even an online product like Google or Facebook, the better you make the product, the better it sells. The key point about in-house development is that once it’s “good enough,” you stop. When you’re working on products, you can keep refining and polishing and refactoring and improving, and if you work for Facebook, you can spend a whole month optimizing the Ajax name-choosing gizmo so that it’s really fast and really cool, and all that effort is worthwhile because it makes your product better than the competition. So, the number two reason product work is better than in-house work is that you get to make beautiful things.

Number three: when you’re a programmer at a software company, the work you’re doing is directly related to the way the company makes money. That means, for one thing, that management cares about you. It means you get the best benefits and the nicest offices and the best chances for promotion. A programmer is never going to rise to become CEO of Viacom, but you might well rise to become CEO of a tech company.

Anyway. After Microsoft I took a job at Viacom, because I wanted to learn something about the internet and Microsoft was willfully ignoring it in those days. But at Viacom, I was just an in-house programmer, several layers removed from anybody who did anything that made Viacom money in any way.

And I could tell that no matter how critical it was for Viacom to get this internet thing right, when it came time to assign people to desks, the in-house programmers were stuck with 3 people per cubicle in a dark part of the office with no line-of-sight to a window, and the “producers,” I don’t know what they did exactly but they were sort of the equivalent of Turtle on Entourage, the producers had their own big windowed offices overlooking the Hudson River. Once at a Viacom Christmas party I was introduced to the executive in charge of interactive strategy or something. A very lofty position. He said something vague and inept about how interactivity was very important. It was the future. It convinced me that he had no flipping idea whatsoever what it was that was happening and what the internet meant or what I did as a programmer, and he was a little bit scared of it all, but who cares, because he’s making 2 million dollars a year and I’m just a typist or “HTML operator” or whatever it is that I did, how hard can it be, his teenage daughter can do that.

The Iceberg Secret, Revealed

Wednesday, February 11th, 2009

The Iceberg Secret, Revealed:

You know how an iceberg is 90% underwater? Well, most software is like that too — there’s a pretty user interface that takes about 10% of the work, and then 90% of the programming work is under the covers. And if you take into account the fact that about half of your time is spent fixing bugs, the UI only takes 5% of the work. And if you limit yourself to the visual part of the UI, the pixels, what you would see in PowerPoint, now we’re talking less than 1%.

That’s not the secret. The secret is that People Who Aren’t Programmers Do Not Understand This.

This leads to some Important Corollaries, like Important Corollary Two:

If you show a nonprogrammer a screen which has a user interface which is 100% beautiful, they will think the program is almost done.

Joel’s advice?

Once you understand the Iceberg Secret, it’s easy to work with it. Understand that any demos you do in a darkened room with a projector are going to be all about pixels. If you can, build your UI in such a way that unfinished parts look unfinished. For example, use scrawls for the icons on the toolbar until the functionality is there. As you’re building your web service, you may want to consider actually leaving out features from the home page until those features are built. That way people can watch the home page go from 3 commands to 20 commands as more things get built.

Does a Big Economy Need Big Power Plants?

Wednesday, February 11th, 2009

Does a Big Economy Need Big Power Plants? Amory B. Lovins says, no:

Thermal power stations burn fuel or fission atoms to boil water to turn turbines that spin generators, making 92 percent of U.S. electricity. Over a century, local combined-heat-and-power plants serving neighborhoods evolved into huge, remote, electricity-only generators serving whole regions. Electrons were dispatched hundreds of miles from central stations to dispersed users through a grid that the National Academy of Engineering ranked as its profession’s greatest achievement of the 20th century.

This evolution made sense at first, because power stations were costlier and less reliable than the grid, so by backing each other up through the grid and melding customers’ diverse loads, they could save capacity and achieve reliability. But these assumptions have reversed: central thermal power plants now cost less than the grid, and are so reliable that about 98 percent to 99 percent of all power failures originate in the grid. Thus the original architecture is raising, not lowering, costs and failure rates: cheap and reliable power must now be made at or near customers.

If central thermal power plants are so efficient and so reliable because they’re big and centralized, then numerous small plants might not help the situation. Rod Adams, publisher of Atomic Insights, makes this point — and others:

He talks about how most power failures occur in the grid, not the power plant, and then advises that a microgrid of small, distributed units can be more reliable than our current model. The problem with that statement is that central station power plant reliability is partially a result of careful engineering, redundancy and professionally trained operators that would not exist if units are too small. Microgrids also have many of the same vulnerabilities of the existing grid, but they will be less carefully engineered and less carefully maintained.

Lovins likes to use the evolution of computers as an analogy, but anyone who is commenting here who has paid close attention to the computer revolution knows that reliability has not been its strongest measure of effectiveness.
[...]
As William Tucker pointed out, Lovins is not totally wrong — there are some significant advantages to right sized power plants that can be manufactured in a factory rather than stick built and that can be delivered in far less time than is typically assumed for a large central station power plant of any kind. There are at least three companies who have publicly announced plans to build nuclear power plants in unit sizes of less than 50 MWe (150 MW thermal). They are Toshiba, which has designed a 10 MWe unit that can run for 30 years without new fuel; Hyperion, which has designed a 70 MW thermal heat source useful for assisting in enhanced oil recovery, district heating and which can be connected to a 27 MWe steam turbine for power production; and NuScale, which has designed a 45 MWe power plant that can be delivered as a single 300 ton unit to a site that has water or rail access.

For my money, those smaller nuclear plants have a huge advantage over the types of systems that Lovins advocates — they produce reliable power without producing any polluting emissions at all. They also need very little in the way of fuel delivery infrastructure. In a world powered by Lovins microgrids, there will be a large demand for diesel fuel and natural gas to fuel the generators that must back-up intermittent wind and solar power. That vision also includes a whole lot of excess capacity that must sit idle for much of its existence.

Is the Tipping Point Toast?

Monday, February 9th, 2009

Is the Tipping Point Toast? Duncan Watts’ research suggests it should be:

He programmed a group of 10,000 people, all governed by a few simple interpersonal rules. Each was able to communicate with anyone nearby. With every contact, each had a small probability of “infecting” another. And each person also paid attention to what was happening around him: If lots of other people were adopting a trend, he would be more likely to join, and vice versa. The “people” in the virtual society had varying amounts of sociability — some were more connected than others. Watts designated the top 10% most-connected as Influentials; they could affect four times as many people as the average Joe. In essence, it was a virtual society run — in a very crude fashion — according to the rules laid out by thinkers like Gladwell and Keller.

Watts set the test in motion by randomly picking one person as a trendsetter, then sat back to see if the trend would spread. He did so thousands of times in a row.

The results were deeply counterintuitive. The experiment did produce several hundred societywide infections. But in the large majority of cases, the cascade began with an average Joe (although in cases where an Influential touched off the trend, it spread much further). To stack the deck in favor of Influentials, Watts changed the simulation, making them 10 times more connected. Now they could infect 40 times more people than the average citizen (and again, when they kicked off a cascade, it was substantially larger). But the rank-and-file citizen was still far more likely to start a contagion.

Why didn’t the Influentials wield more power? With 40 times the reach of a normal person, why couldn’t they kick-start a trend every time? Watts believes this is because a trend’s success depends not on the person who starts it, but on how susceptible the society is overall to the trend — not how persuasive the early adopter is, but whether everyone else is easily persuaded. And in fact, when Watts tweaked his model to increase everyone’s odds of being infected, the number of trends skyrocketed.

“If society is ready to embrace a trend, almost anyone can start one — and if it isn’t, then almost no one can,” Watts concludes. To succeed with a new product, it’s less a matter of finding the perfect hipster to infect and more a matter of gauging the public’s mood. Sure, there’ll always be a first mover in a trend. But since she generally stumbles into that role by chance, she is, in Watts’s terminology, an “accidental Influential.”

Perhaps the problem with viral marketing is that the disease metaphor is misleading. Watts thinks trends are more like forest fires: There are thousands a year, but only a few become roaring monsters. That’s because in those rare situations, the landscape was ripe: sparse rain, dry woods, badly equipped fire departments. If these conditions exist, any old match will do. “And nobody,” Watts says wryly, “will go around talking about the exceptional properties of the spark that started the fire.”

He also replicated Milgram’s famous six degrees of separation experiment, but he did not get the same results: hubs weren’t crucial.

(Hat tip to Todd.)

Kindle 2

Monday, February 9th, 2009


Amazon has, as predicted, announced the Kindle 2; it will be released February 24.

It looks quite a bit sleeker, and they’re emphasizing that it’s just one-third of an inch thick. It also turns pages faster and displays images in 16 shades of gray, and the battery lasts longer.

I’m not sure how I feel about the text-to-speech capability. If you watch the demonstration video, it’s still quite Speak & Spell.

47 speed bicycles, AK brand

Monday, February 9th, 2009

Gun nuts say, do not mention firearms in the title line of any Craigslist post, because the “hoplophobes” will delete your post immediately:

Even though Craigslist does not allows firearms and ammunition advertisements, it is still beneficial to check the Sporting Goods section. In my my local Craigslist there are “47 speed bicycles, AK brand”, and similar items regularly for sale.

Ward Three Morality

Monday, February 9th, 2009

David Brooks laments that the rich are beginning to run afoul of Ward Three Morality:

The essence of the problem is this: Rich people used to set their own norms. For example, if one rich person wanted to use the company helicopter to aerate the ponds on his properties, and the other rich people on his board of directors thought this a sensible thing to do, then he could go ahead and do it without any serious repercussions.

But now, after the TARP, the auto bailout, the stimulus package, the Fed rescue packages and various other federal interventions, rich people no longer get to set their own rules. Now lifestyle standards for the privileged class are set by people who live in Ward Three.

For those who don’t know, Ward Three is a section of Northwest Washington, D.C., where many Democratic staffers, regulators, journalists, lawyers, Obama aides and senior civil servants live. Thanks to recent and coming bailouts and interventions, the people in Ward Three run the banks and many major industries. Through this power, they get to insert themselves into the intricacies of upscale life, influencing when private jets can be flown, when friends can lend each other their limousines and at what golf resorts corporate learning retreats can be held.

The good news for rich people is that people in this neighborhood are very nice and cerebral. On any given Saturday, half the people in Ward Three are arranging panel discussions for the other half to participate in. They live in modest homes with recently renovated kitchens and Nordic Track machines crammed into the kids’ play areas downstairs (for some reason, people in Ward Three are only interested in toning the muscles in the lower halves of their bodies).

Nonetheless, many people in Ward Three do have certain resentments toward those with means, which those of you in the decamillionaire-to-billionaire wealth brackets should be aware of.

In the first place, many people in Ward Three suffer from Sublimated Liquidity Rage. As lawyers, TV producers and senior civil servants, they make decent salaries, but 60 percent of their disposable income goes to private school tuition and study abroad trips. They have little left over to spend on themselves, which generates deep and unacknowledged self-pity.

Second, they suffer from what has been called Status-Income Disequilibrium. At work they are flattered and feared. But they still have to go home and clean out the gutters because they can’t afford full-time household help.

Third, they suffer the status rivalries endemic to the upper-middle class. As law school grads, they resent B-school grads. As Washingtonians, they resent New Yorkers. As policy wonks, they resent people with good bone structure.

In short, people in Ward Three disdain three things: cleavage, hunting and dumb people who are richer than they are. Rich people have to learn to adapt to the new power structure if they hope to survive.