Tech company executives have a new hobby – keeping chickens.
Michel uses “Coop Tender,” a system that allows owners to control their coops via smartphone, dictating temperature, ventilation and lighting.
The system includes an automatic door and “predator motion detection” that turns on a security light and sends owners a text when danger lurks. Despite their relative privilege, even these chickens are circled by predators like hawks, coyotes, raccoons and bobcats.
This article summarizes the problems with free parking pretty well. Then it goes on to lament that Australian cities aren’t moving faster to implement the policies that planners and engineers know (or should know) would work.
The third major approach is characterised as responsive. This approach is based around pricing parking to account more accurately for actual demand, to incentivise use of active and sustainable modes of transport, and advocating generally for more efficient publicly-shared spaces (not exclusively used by cars) and area-based planning. It can be said to include Donald Shoup’s well-known reforms, as well as Paul Barter’s adaptive and walkable parking reforms…
Parking can directly compromise the adoption of active and sustainable modes of transport. Firstly, free and easily accessible parking contributes to induced driving and car ownership. For example, researchers from Oslo’s Institute of Transport Economics found that access to private household parking facilities triples the likelihood of car ownership, whereas increasing the distance between parking and destinations reduces car mode share. This means planners must disincentivize convenience (including factors of distance, time and pricing), and reduce its domination of urban space. Secondly, on-street parking can directly compete for limited road space, inhibiting the ability to reallocate street space to improved pedestrian or cycling infrastructure (such as bicycle lanes), or to create priority lanes for road-based public transport (such as buses or trams). Additionally, on-street parking spurs congestion from “cruising” for parking spaces, and movements in and out of spaces, and well as increasing the risk of “dooring” cyclists.
I followed up on a link in yesterday’s story about lottery winners. In 2017 a group publishing in the Columbia Journalism Review submitted Freedom of Information Act requests to basically all the U.S. state lotteries and analyzed all the data they were able to get. The results are really surprising, verging on basically impossible.
- Clarance Jones of Lynn, Massachusetts, the nation’s most frequent winner, claimed more than 7,300 tickets worth $600 or more in only six years.
- Jones would have had to spend at least $300 million to have a 1-in-10 million chance of winning so often, according to a statistician we consulted at the University of California, Berkeley. (Jones did not respond to requests for comment.)
- The odds are extraordinary even for winners with far smaller win tallies. According to the analysis, Nadine Vukovich, Pennsylvania’s most frequent winner, would have had to spend $7.8 million to have a 1-in-10 million chance of winning her 209 tickets worth $600 or more.
What could explain any of this? I don’t know, of course. But here are a few explanations that would fit the evidence.
I’d place most of my bets on #2 and #3, and a small side bet on #4 or #5.
Here’s a long, interesting article in Huffington Post about a couple who developed a system to beat flawed lottery games in Michigan and Massachusetts. Eventually, they got found out, but not before making over $7 million. They reported all their earnings and paid all their taxes. Nobody really got in trouble, expect some store owners who lost their licenses to sell lottery tickets for breaking minor rules. Some other groups of people managed to exploit this same game too.
As interesting as the whole story is, there are a few paragraphs buried in the middle that really caught my eye. There really are people out there who win the lottery more than anyone should by random chance.
A 2017 investigation by the Columbia Journalism Review found widespread anomalies in lottery results, difficult to explain by luck alone. According to CJR’s analysis, nearly 1,700 Americans have claimed winning tickets of $600 or more at least 50 times in the last seven years, including the country’s most frequent winner, a 79-year-old man from Massachusetts named Clarance W. Jones, who has redeemed more than 10,000 tickets for prizes exceeding $18 million.
It’s possible, as some lottery officials have speculated, that a few of these improbably lucky individuals are simply cashing tickets on behalf of others who don’t want to report the income. There are also cases in which players have colluded with lottery employees to cheat the game from the inside; last August, a director of a multistate lottery association was sentenced to 25 years in prison after using his computer programming skills to rig jackpots in Colorado, Iowa, Kansas, Oklahoma and Wisconsin, funneling $2.2 million to himself and his brother.
But it’s also possible that math whizzes like Jerry Selbee are finding and exploiting flaws that lottery officials haven’t noticed yet. In 2011, Harper’s wrote about “The Luckiest Woman on Earth,” Joan Ginther, who has won multimillion-dollar jackpots in the Texas lottery four times. Her professional background as a PhD statistician raised suspicions that Ginther had discovered an anomaly in Texas’ system. In a similar vein, a Stanford- and MIT-trained statistician named Mohan Srivastava proved in 2003 that he could predict patterns in certain kinds of scratch-off tickets in Canada, guessing the correct numbers around 90 percent of the time. Srivastava alerted authorities as soon as he found the flaw. If he could have exploited it, he later explained to a reporter at Wired, he would have, but he had calculated that it wasn’t worth his time. It would take too many hours to buy the tickets in bulk, count the winners, redeem them for prizes, file the tax forms. He already had a full-time job.
Apparently the devastating wild fires in California recently may have been sparked by downed electric lines, and there is a California law that may hold the utilities responsible for those lines liable for massive damages. Their stocks are now plunging as a result. Somewhat ironically, they are arguing that the severity of the wild fires is a result of climate change, even if they were sparked by the power lines. Climate change is a “societal issue” requiring “holistic solutions”, they say. I’m thinking that the mix of fossil and renewable fuels used to generate electricity could be part of the problem.
BBC has a list of the 11 cities most likely to run out of drinking water. Cape Town, South Africa is not on the list, because it is out of drinking water. Here’s the list:
London and Tokyo surprised me, while some of the high-growth developing capitals didn’t surprise me but are nonetheless extremely concerning. There are plenty of cities that probably would be on the list but aren’t because they have invested massively in desalination. many of the coastal cities on this list may ultimately have to follow suit, or else convince their national governments to invest in major pipeline projects. And this is just drinking water, of course. Food has to be grown elsewhere and brought in to all the world’s cities, and industry also has water needs. Ecosystems also need water, but does anyone expect them to be anywhere other than last on this list?
SpaceX is planning to launch over 4,000 small satellites to provide internet service. In the meantime though, it is apparently raising some cash by launching spy satellites for friendly foreign governments.
There has been some progress on quantum computers.
Quantum computers, after decades of research, have nearly enough oomph to perform calculations beyond any other computer on Earth. Their killer app is usually said to be factoring large numbers, which are the key to modern encryption. That’s still another decade off, at least. But even today’s rudimentary quantum processors are uncannily matched to the needs of machine learning. They manipulate vast arrays of data in a single step, pick out subtle patterns that classical computers are blind to, and don’t choke on incomplete or uncertain data. “There is a natural combination between the intrinsic statistical nature of quantum computing … and machine learning,” said Johannes Otterbach, a physicist at Rigetti Computing, a quantum-computer company in Berkeley, California.
If anything, the pendulum has now swung to the other extreme. Google, Microsoft, IBM and other tech giants are pouring money into quantum machine learning, and a startup incubator at the University of Toronto is devoted to it. “‘Machine learning’ is becoming a buzzword,” said Jacob Biamonte, a quantum physicist at the Skolkovo Institute of Science and Technology in Moscow. “When you mix that with ‘quantum,’ it becomes a mega-buzzword.”
These things look more like horizontal elevators than cars.