Monday, September 30, 2019

It’s a Numbers Game in the Coup to Stop Johnson and Brexit Date: September 27, 2019 Author: Tom Luongo

When the decision came down from the Supreme Court I began my weekly article for Strategic Culture Foundation. They published it today. In that piece I outline what the dynamics are and what the options were for both sides of the Brexit conundrum.
So, now with this ruling in place what’s next and what’s really going on tactically and strategically?
Johnson, for his part, refuses to resign. He can’t or won’t get anything past this hostile Parliament. This Parliament will reconvene to push more legislation to attempt to tie his hands against negotiating with the EU from any position of strength.
Remember what made this ruling necessary. Parliament doesn’t want any meaningful Brexit and refused to accept Johnson’s offer of a General Election to allow the people to form a new government to break the deadlock.
Why? Because they know that a new Parliament would be decidedly more Leave than Remain. The polls are perfectly clear on this. Neither Jo Swinson of the Liberal Democrats nor Jeremy Corbyn of Labour have a prayer in hell of becoming Prime Minister.
If they did, they would have accepted Johnson’s offer. In fact, his offer was derided as a cheap political trick.
If Johnson were to resign here, he would be replaced by a caretaker government under Corbyn, most likely, which would then table a Second Referendum with two versions of Remain on the ballot.
This strategy neatly bypasses the original referendum to ensure the threat to the European Union is nullified.
After the shouting match in Parliament on Tuesday Jeremy Corbyn declined to table a motion of No Confidence. I believe his side of the House was as surprised by Johnson’s refusal to step down as Johnson and crew were taken aback by Corbyn’s refusal of a General Election.
And now that they’ve had a couple of days to think it over, we now know that this is what they are planning to do.
Nicola Sturgeon, the head of the Scottish National Party (SNP) tweeted out:
Furthermore, the Liberal Democrats are talking in public about a coup against Johnson. But they won’t move against him until they “know Jeremy has the numbers.” Every day they delay is another day in which he doesn’t have the numbers.
So, why wouldn’t he?
At least 20 former members of the Conservative Party, when push came to shove, would vote with Labour, the LibDems and the SNP on this. But, the bigger question is how many from their own parties would ‘defy the whip’ and not vote against the Government.
They would ‘defy the whip’ because they are rightly scared of a General Election which would see them booted out of office. But, that said, would they do it? My guess is yes because the pressure on them at this point to betray Brexit is enormous.
The entire British political and social elite want this pesky Brexit bother binned so they can move on with erecting their new, more perfect European Union on the ashes of trivial things like sovereignty and basic human dignity.
Editorial comments aside, here’s the situation as it stands. If the vote happens and Johnson is deposed, they will have 14 days under the Fixed Term Parliaments Act to form a ‘caretaker government.’ If Corbyn ‘has the numbers’ and the agreement from the other parties then this will happen.
It will take All of Labour (247 seats), the SNP (35), the LibDems (18) and at least another 11 MP’s to get this done. And then they have to also agree on what their proposal to the EU is.
Most of Corbyn’s shadow cabinet are with the LibDems and want Article 50 revoked and the whole thing called off. Corbyn doesn’t want that and has only reluctantly been dragged down this course in order to try and preserve some semblance of Brexit, which he does believe in.
What they will offer the EU is the biggest stumbling block to this backroom deal. But, at the final moment, goal-oriented behavior will take over and an agreement will be reached.
After Johnson is gone and Corbyn installed, the Benn bill will come into effect, an extension will be negotiated and a bill for a 2nd referendum will be tabled immediately. Once Corbyn secures a deal with the EU that referendum will happen with two choices, Remain (which shouldn’t be on the ballot) and Corbyn’s deal.
Basically Remain vs. Remain. This will ensure that the most forceful point of the Leave camp, that the 17.4 million people who voted to Leave are being ignored, is neutralized.
I told you, only Hobson’s Choices from here on out for the unwashed, thick and uppity plebes who think they have any other obligation than to be tax cows milked by vampiric oligarchs convinced of their own superiority.
Then they will go for a general election hoping that the Referendum will dispirit British voters to the point of not voting, which will give Remain the win and the General Election will be a moot point. The outcome would likely be a hung Parliament, as the malaise over Brexit betrayed will keep people at home. Parliament will be paralyzed and in no position to negotiate the final terms of surrender to the EU or carry out the next stage of the negotiations.
That’s why the Second Referendum is so important. It gives Remainers all the ammunition to throw back at the Leavers saying, “See the people have spoken!”
It’s vicious and dishonest, but that’s politics, folks.
But all of that is moot if they don’t have the numbers. Then Johnson will continue to run the clock down, go to Brussels on October 17th and try to work for a deal that isn’t BRINO — Brexit in Name Only. That’s why it’s obvious that there will be a coup against Johnson without an election.
The strategy now is to whip MPs into overthrowing Johnson’s government, securing that extension and destroying what’s left of the British political system.

The Scar I’m Most Proud Of September 30, 2019 by Will (

I grew up in a restaurant where scars were the closest thing anyone had to a resume. 
The prep cook’s hands looked like knife-sewn stitchwork quilts, and the line cooks all shared the same smooth fingerprints from searing burns. The mark of a novice pizza maker, like myself, was brands across the forearm from inexpert removal of a pie at the back of the 700° oven.
By the end of my less than illustrious tenure, my arms were scored with the bright red lashings. For years afterwards the scars remained distinct and pronounced against my skin. I still shudder when recalling the excruciating sizzle of the oven, but these days only I can see the scars. And only if I look closely. The scars, and their lessons, are now an inextricable part of who I am. 
It seems the marks on our hearts are the same. 

Eko died three years ago yesterday. In the years since I’ve written about loss as a measure of both time and space. Loss as a painful lesion across a once pristine stretch of heart. Loss as an invasive grief which I could not excise but refused to accept.
But scars are strange things. Their once distinct boundaries slowly blur. Their gnarled texture softens. Their conflagration of color burns out and dulls until neatly blended. These unwelcome sufferings become familiar companions. We begin to forget what the unblemished skin ever looked like.
I’ve now known my scars for half as long as I knew Eko. Sooner than I’d like, the days with my scars will outnumber the days with my puppy. Already, I struggle to recall what I looked like before Eko’s death. The man I picture seems nearly a stranger.

We are remade by the time we spend with our dogs and then unmade by the moment we lose them. I’ve written much about those transformative experiences, but only now do I have the perspective to consider the transformation Eko made possible after he died.
That transformation began when Eko was just a puppy. I was so desperate to love and protect my dog that I treated him with the care of a museum curator. But just a couple weeks after I brought him home Eko picked up his first scar – a notch on his ear from eagerly diving into the maw of a friend’s dog.
I winced every time I saw the hard scab on his soft coat, but Eko didn’t seem to mind. Nor did he care much about any of the scrapes and scars he accumulated over the years. Because Rhodesian Ridgebacks are not antiquities to be preserved. The flawless coat they’re born with is not meant to remain so. Their supple paw pads are not meant to go unworn. These creatures intuitively understand life is a treasure meant to be spent, not hoarded. 
To love a Ridgeback means accepting the cost of an unforgettable journey is innumerable scars. 
In time I came to understand the lesson —  the scars were Eko’s resume. His job? Teaching a boy that love is not safety, it’s vulnerability.
And I have never felt more vulnerable than I did after Eko died. I was lost and broken. I was also, as I learned the morning after Eko’s death, a father-to-be. 
I felt no joy for the child we’d dreamed about, only fear at all the ways Emily’s pregnancy might end tragically. My fear tethered the yearnings of my heart so that it could not rise high enough to break from another fall.
It was a miserable time and I was a miserable person. For months I did little more than stare at my wounds numbly. I became a detached stoic, unfeeling at circumstance so that I could not be hurt by it. It was three words from Emily which brought me back.
It was an invocation to be the man my puppy taught me to be. Flawed and scarred, but undaunted. In three words she cut loose the ballast on my heart so that it could rise again.
Three years later and I am transformed by Eko’s memory. The scar has faded, but I remember. I remembered Eko when I offered my love to a new puppy. I remembered Eko when I gave my heart unequivocally to my son. I remember Eko each time I am vulnerable but choose love over fear.
Yesterday morning at sunrise, Emily and I walked to the beach, Lincoln between us, Penny and Zero on either side. The dogs raced down the shore, Lincoln whooped, Emily smiled and my scarred heart was grateful for the dog who transformed me and made the moment possible.
I know I will be cast down and broken again. More reckonings undoubtedly await. These are the costs of a worthy journey. But I will never again hide from this price or be cowed in fear of the day I must pay it.
Because my scars are my resume, and the job my puppy entrusted me with is ever unfinished. Today, and all days, l race ahead with my heart lifted high. Full, vulnerable and free, as Eko insisted it must always be. 

Sunday, September 29, 2019

12 Truth Bombs from Milton Friedman As Milton Friedman wrote, "Governments never learn; only people learn." by Jon Miltimore

American economist Milton Friedman rose to prominence in the second half of the 20th century as one of the leading critics of the prevailing economic theories of John Maynard Keynes, whose mixed economy model became the standard for many developed nations during and after the World War II-era.
Born in Brooklyn to a Jewish family of modest means in 1912, Friedman distinguished himself scholastically at a young age. After graduating high school at age 16, he attended Rutgers University where he studied math and economics. He continued his education at the University of Chicago, where he received an MA in economics and would ultimately retire in 1977 after more than 30 years of teaching—a year after receiving the Nobel Prize for his contributions to economic science. Friedman continued writing and speaking publicly through various mediums—magazine columns and television, academic journals and newspaper op-eds—until his death in 2006.
The Economist has described Friedman as “a giant among economists” and “the most influential economist of the second half of the 20th century.” Here are 12 things he said to serve as food for thought:
1. "Underlying most arguments against the free market is a lack of belief in freedom itself." – >Capitalism and Freedom (2002)
2. "I’m in favor of legalizing drugs. According to my values system, if people want to kill themselves, they have every right to do so. Most of the harm that comes from drugs is because they are illegal." – As quoted in ‪If Ignorance Is Bliss, Why Aren't There More Happy People? (2009)
3. "With some notable exceptions, businessmen favor free enterprise in general but are opposed to it when it comes to themselves." –Lecture "The Suicidal Impulse of the Business Community" (1983)
4. "It's a moral problem that the government is making into criminals people, who may be doing something you and I don't approve of, but who are doing something that hurts nobody else." – America's Drug Forum interview (1991)
5. "One of the great mistakes is to judge policies and programs by their intentions rather than their results." – Interview with Richard Heffner on The Open Mind (Dec. 7, 1975)
6. "You must distinguish sharply between being pro-free enterprise and being pro-business." – Big Business, Big Government (1978)
7. "The society that puts equality before freedom will end up with neither. The society that puts freedom before equality will end up with a great measure of both." – From "Created Equal," an episode of the PBS Free to Choose television series (1980)
8. "Governments never learn; only people learn." – As quoted in The Cynic's Lexicon: A Dictionary Of Amoral Advice‎ (1984)
9. "We have to recognize that we must not hope for a Utopia that is unattainable. I would like to see a great deal less government activity than we have now, but I do not believe that we can have a situation in which we don't need government at all." – As quoted in The Times Herald, Norristown, Pennsylvania (Dec. 1, 1978)
10. "The great virtue of a free market system is that it does not care what color people are; it does not care what their religion is; it only cares whether they can produce something you want to buy. It is the most effective system we have discovered to enable people who hate one another to deal with one another and help one another." – "Why Government Is the Problem" (February 1, 1993), p. 19
11. "The case for prohibiting drugs is exactly as strong and as weak as the case for prohibiting people from overeating. We all know that overeating causes more deaths than drugs do." – America's Drug Forum interview (1991)
12. "There are four ways in which you can spend money. You can spend your own money on yourself. When you do that, why then you really watch out what you’re doing, and you try to get the most for your money. Then you can spend your own money on somebody else. For example, I buy a birthday present for someone. Well, then I’m not so careful about the content of the present, but I’m very careful about the cost. Then, I can spend somebody else’s money on myself. And if I spend somebody else’s money on myself, then I’m sure going to have a good lunch! Finally, I can spend somebody else’s money on somebody else. And if I spend somebody else’s money on somebody else, I’m not concerned about how much it is, and I’m not concerned about what I get. And that’s government. And that’s close to 40 percent of our national income." – Fox News interview (May 2004).

Moore’s Law Is Dying. This Brain-Inspired Analogue Chip Is a Glimpse of What’s Next By Shelly Fan

“Dark silicon” sounds like a magical artifact out of a fantasy novel. In reality, it’s one branch of a three-headed beast that foretells the end of advances in computation.
Ok—that might be too dramatic. But the looming problems in silicon-based computer chips are very real. Although computational power has exploded exponentially in the past five decades, we’ve begun hitting some intractable limits in further growth, both in terms of physics and economics.
Moore’s Law is dying. And chipmakers around the globe are asking, now what?
One idea is to bet on quantum computers, which tap into the ultra-weird world of quantum mechanics. Rather than operating on binaries of 0s and 1s, qubits can simultaneously represent both states, with each having a different probability and thus much higher information density.
Another idea is to look inside our heads: the quantum realm isn’t the only way to get past binary computation. Our brains also operate on probabilities, making them a tangible source of inspiration to overhaul the entire computational world.
This week, a team from Pennsylvania State University designed a 2D device that operates like neurons. Rather than processing yes or no, the “Gaussian synapse” thrives on probabilities. Similar to the brain, the analogue chip is far more energy-efficient and produces less heat than current silicon chips, making it an ideal candidate for scaling up systems.
In a proof-of-concept test, the team used a simulated chip to analyze EEG (electroencephalography) signals taken from either wakeful or sleeping people. Without extensive training, the chip was able to determine if the subject was sleeping.
“Combined, these new developments can facilitate exascale computing and ultimately benefit scientific discovery, national security, energy security, economic security, infrastructure development, and advanced healthcare programs,” the team concluded.

The Three-Headed Beast

With new iPhones every year and increasingly sophisticated processors, it certainly doesn’t feel like we’re pushing the limits of silicon-based computing. But according to lead study author Dr. Saptarshi Das, the ability to further scale traditional computation is dying in three different aspects: energy, size, and complexity.
Energy scaling helps ensure a practically constant computational power budget, explained Das. But it came to an end around 2005 because of hard limits in the silicon chip’s thermodynamic properties—something scientists dub the Boltzmann tyranny (gotta love these names!). Size scaling, which packs more transistors onto the same chip area, soon followed suit, ending in 2017 because quantum mechanics imposes limitations at the materials level of traditional chips.
The third, complexity scaling, is still hanging on but on the decline. Fundamentally, explained the team, this is because of the traditional von Neumann architecture that most modern computers use, which rely on digital, binary computation. In addition, current computers store logic and memory units separately and have to operate sequentially, which increases delay and energy consumption. As more transistors are jam-packed onto the same chip and multiple cores are linked together into processors, eventually the energy needs and cooling requirements will hit a wall.
This is the Dark Silicon era. Because too much heat is given out, a large amount of transistors on a single chip can’t be powered up at once without causing heat damage. This limitation requires a portion of computing components on a chip to be kept powered off—kept “dark”—at any instant, which severely limits computational power. Tinkering with variables such as how to link up transistors may optimize efficacy, but ultimately it’s a band-aid, not a cure.
In contrast, the brain deploys “billions of information processing units, neurons, which are connected via trillions of synapses in order to accomplish massively parallel, synchronous, coherent, and concurrent computation,” the team said. That’s our roadmap ahead.

Saved by the Bell

Although there are plenty of neuromorphic chips—devices that mimic the structure or functionality of neurons and synapses—the team took a slightly different approach. They focused on recreating a type of artificial neural network called a probabilistic neural network (PNN) in hardware form.
PNNs have been around since the 60s as software, and they’re often used for classification problems. The mathematical heart of PNNs differs from most of the deep learning models used today, but the structure is relatively similar. A PNN generally has four layers, and raw data travels from the first layer to the last. The two middle layers, pattern and summation, process the data in a way that allows the last layer to make a vote—it selects the “best” answer from a group of potential probable ones.
To implement PNNs directly in hardware form, the team engineered a Gaussian synapse made of two different materials: MoS2 and black phosphorus. Each represents a transistor, and is linked in series on a single synapse. The way the two transistors “talk” to each other isn’t linear. When the MoS2 component switches on, the electrical current rises exponentially until it reaches a max level, then it drops. The connection strength is like a bell-shaped curve—or in mathematical lingo, a Gaussian distribution widely used in probabilities (and where the device gets its name).
How each component turns on or off can be tweaked, which in turn controls communication between the transistors. This, in turn, mimics the inner workings of PNNs, said study author Amritanand Sebastian.

Decoding Biology With Artificial Synapses

As a proof of concept, the team decided to give back to neuroscience. The brain generates electrical waves that can be picked up by electrodes on top of the scalp. Brain waves are terribly complicated data to process, said the team, and artificial neural networks running on traditional computers generally have a hard time sorting through them.
The team fed their Gaussian synapse recordings from 10 whole nights from 10 subjects, with 32 channels for each individual. The PNN rapidly recognized different brainwave components, and were especially good at picking out the frequencies commonly seen in sleep.
“We don’t need as extensive a training period or base of information for a probabilistic neural network as we need for an artificial neural network,” said Das.
Thanks to quirks in the transistors’ materials, the chip had some enviable properties. For one, it was exceedingly low-power. To analyze 8 hours of EEG data, it consumed up to only 350 microwatts; to put this into perspective, the human brain generally runs on about 20 watts. This means that the Gaussian synapse “facilitates energy scaling,” explained Sebastian.
For another, the materials allow size scaling without losing their inherent electrical properties. Finally, the use of PNNs also solves the complexity scaling problem, because it can process non-linear decisions using fewer components than traditional artificial neural networks.
It doesn’t mean that we’ve slayed the three-headed beast, at least not yet. But looking ahead, the team believes their results can further inspire more ultra-low power devices to tackle the future of computation.
“Our experimental demonstration of Gaussian synapses uses only two transistors, which significantly improves the area and energy efficiency at the device level and provides cascading benefits at the circuit, architecture, and system levels. This will stimulate the much-needed interest in the hardware implementation of PNNs for a wide range of pattern classification problems,” the authors concluded.

Charts of the day: Historic energy/environmental milestones Carpe Diem

The top chart above shows CO2 emissions in the US frm the electric power sector for the first half of every year, which fell this year to a 35-year low for the January-June period, the lowest since 1984. That was back when Ronald Reagan was re-elected to a second term, Apple aired its famous “1984” Macintosh commercial, the Soviet Union boycotted the Olympics, crack cocaine showed up in LA, and Ghostbusters was the No. 1 movie.
What do we have to thank for that significant “greening of America” that brought CO2 emissions in the US to a 35-year low this year for the January-June period? A carbon tax? Government energy policy? A reduction in electric power generation? Nope. An increase in the use of renewables like solar and wind for generating electricity? Perhaps, since the combined contribution of solar and wind for electric power has increased from 6.7% in 2016 to about 10% this year through June.
But one of the biggest factors that has contributed to the significant decline in CO2 emissions from electric power over the last decade has been the gradual but increasing substitution of natural gas for coal to generate the nation’s electric power. The second chart above shows that substitution of natural gas for coal, which now provides a record low 24% share of electric power while the share of natural gas has increased to a record high of 36.6% this year through June.
So at the same time that climate alarmists like Greta Thunberg and AOC (Karla Marx) lecture us about reducing our carbon footprint to prevent a pending environmental collapse, carbon emissions in the US have fallen to a level not seen since before AOC was born in 1989. And that reduction in CO2 is largely due to free-market capitalism that brought us the advanced technologies of fracking and horizontal drilling that accessed oceans of affordable shale gas. Unfortunately, Greta and AOC want to squash the very free market forces that helped bring CO2 to a 35-year low and instead replace market forces with massive increases in command-and-control government power. To paraphrase Steve Horwitz, it is precisely this sort of contempt for the market and embrace of the heavy hand of government that will destroy the very forces that have pulled human beings from abject poverty and enabled us to have the resources to address environmental concerns.
Bonus graphics below.

Q&A Live Mini-Course: Solar Screams Hit Home— Solar Flares & Radio Burst...

Coax cable portable magnetic loop for 80 and 160m

Don't Mess With A Rhodesian Ridgeback's Couch

First test of the Nano VNA on my beacon antenna by Mark VandeWettering

Everyone I know in the twitterverse/blogosphere seems to be getting a cute little $50 piece of kit called the NanoVNA, which is a small vector network analyzer. In ham radio lingo, this means that it’s an antenna analyzer. IMSAI guy was the guy who first got me interested in getting one, and he did an awesome little video on one.
I ordered one for a little more than $50 off of eBay. Mine looks a teensy bit different, having a white case and sporting a stylish lizard on the front.
It came with a USB-C cable to allow it to be charged, a couple of short SMA cables, and a set of three small calibration dongles (one open, one short, one with 50 ohm resistance) so you could calibrate it. The battery was charged when it arrived, so I could power it on quite easily.
Here’s more or less what it looks like when powered on. I find the overall display to be a bit complicated by default. I need to work on figuring out how to set it up to a less cluttered display. As a ham, I’m usually most interested in using it as an antenna analyzer, which ideally means that I want to sweep it over a range of frequencies, and graph something like the standing wave ratio as it varies by frequency.
In fact, that’s exactly what I got it for. Long time followers of my blog might remember that I tried to setup a small WSPR beacon during the last Field Day, but that a variety of problems kept it from operating. Since then, I’ve actually replaced the burned out Arduino board and had it operating continuously from my back yard, powered by a small solar cell feeding a 7.2Ah lead acid battery through a Chinese charge controller. It consists of a (nominal, never accurately measured) 20mw signal feeding into this whip antenna dipole.
It’s way too low, and I didn’t do much to optimize it. I have an old MFJ-259 antenna analyzer which works fine and is built like a tank, but which is kind of annoying to use. It also doesn’t present any information graphically, and can’t sweep over a range of frequencies itself, so if you want to graph the performance of your antenna over an entire band, you need to basically get a pencil, fiddle the (analogue) frequency generator up and down, dutifully record the SWR (or whatever) over the frequencies, and then graph it yourself.
Yuck, who has time for that?
A friend of mine loaned me his Rig Expert AA600 which works well and will do frequency sweeps and graph the results, but it costs nearly $600, which is far too much for my hobby use.
That’s why I was interested in the NanoVNA. It seemed to be a good gadget that was available for hobbyist money.
This morning I finally located the necessary pigtail that would allow me to connect the SMA connectors to the UHF connector on my antenna and got it hooked up. I am still a total novice at using it, but I managed to set the NanoVNA to scan the 20m band (from 14.0Mhz to 14.3Mhz) and graph the SWR. Here is the result (with lots of glare from the sun, but hopefully legible).
I haven’t decluttered the display, but you can look at a couple of things. First, near the upper right you can see in white that the frequency of interest has been set to 14.069, which is close to the frequency that I’m operating the beacon at. Going toward the bottom you can see that it says the center is at 14.150 MHz, and the span of the display is 300kHz. Just above it, you can see the tagged “1” inside a small triangle, which shows the current frequency, just above the curve in yellow. This is the SWR measurement. You can see that the lowest part of the curve is very near the “1” target. Nice! At the top of the screen in yellow, you can see that it shows the SWR as 1.38, which seems better than I expected.
Near the center of the screen, you can see the antenna impedance graphed on a smith chart. It is calibrated so the very center of the circular display would mean a purely resistive impedance of 50 ohms. The green line shows the complex impedance plotted over the frequency range. The green triangle marker shows the current frequency, which is very close to the center of the Smith chart. Nice! At the top you can read the complex impedance in green, which is 46.8 Ohms and 781 pF.
All in all, it’s a very cool gadget, and I think it will be a nice addition to my list of ham accessories.
A couple of small caveats:
  • It has a nice color display that is touch sensitive, but it is on the small side, which makes it hard for a guy with large hands like myself to operate sometimes. It’s not insurmountable, and I’m sure it helps keep the cost down, but I do wish for more dedicated buttons.
  • The ruggedness of the unit is, well, questionable. In particular, the small tilt switch at the top seems like it would not be great to have kicking around inside your “go bag” and is difficult to operate with gloves. These aren’t fatal for a device you use in the lab (although even there I do have an appreciation for more rugged devices) but you might need to be more careful in the field.
  • The interface elements are a bit confusing, the fonts and color choices are not super legible, especially for someone with presbyopia like myself.
  • The calibration accessories I received were not labelled, and it took me a few minutes to figure out which was which.
  • I haven’t yet explored controlling the NanoVNA from a PC, which might allow for a better user experience.
It does appear that the firmware for the device is open source which means that some of the rough edges that I see might be fixed over time, and may in fact mean that I could write my own firmware that would be more tailored to my own use cases, which is awesome.
Addendum: if you want to see where my beacon has been seen on the WSPR network, you can search for K6HX on the website, or visit my own custom website which updates every fifteen minutes, and shows all the spots from the previous 24h. I do occasionally get spots from as far away as Hawaii and the East Coast, but today seems a bit more sedate.

Wednesday, September 25, 2019

Magic Band Contesting Setup (with Sporadic E)

The Secret Bunkers of The British Resistance

The Driving Force of Free Markets Is Empathy, Not Greed Only the entrepreneur who prioritizes other people’s needs can be successful. by Dr Rainer Zitelmann

Both capitalists and anti-capitalists frequently accuse capitalism of being a system driven by selfishness and greed. Capitalism’s defenders sometimes say: “By nature, man is selfish, which is why socialism will never work. Capitalism better reflects the fundamental characteristics of human nature.” Anti-capitalists claim that capitalism promotes the worst characteristics in man, especially greed.
But are greed and unbridled selfishness really the driving forces of capitalism? Human self-interest is one—not the only—driving force of all human action. But this has nothing to do with a particular economic system. Rather, it is an anthropological constant. In capitalism, however, this self-interest is curbed by the fact that only the entrepreneur who prioritizes other people’s needs can be successful.
There is overwhelming evidence to suggest that empathy, rather than greed, is the true driving force of capitalism. Empathy is the ability to recognize and understand another person’s feelings and motives, and this is the most important characteristic of successful entrepreneurs.
Take Steve Jobs as an example. He came up with the iPhone and other products because he understood modern consumers’ needs and desires better than anyone else. Under capitalism, consumers can (and do) punish companies that behave selfishly and lose sight of the needs of their customers.
The same applies to Mark Zuckerberg, today one of the world’s richest people. He created Facebook because he knew better than other entrepreneurs what people wanted. Like all successful entrepreneurs, it was consumers who made Steve Jobs and Mark Zuckerberg so rich.

For many years, the Albrecht brothers were the richest people in Germany. They earned their fortunes from the food discounter Aldi, which was founded on the principle of offering good quality products at very reasonable prices. This was the same recipe for success followed by Sam Walton, the founder of Walmart, who was consistently one of the richest people in the United States.
Consumers’ purchasing decisions confirm that Jobs, Zuckerberg, the Albrecht brothers, and Sam Walton had correctly understood their customers’ desires, needs, and emotions.
Of course, under the capitalist system, there are also examples of companies that have acted selfishly and lost sight of the wants and needs of consumers.
One example is Deutsche Bank, which has faced thousands of lawsuits. Such companies are punished under capitalism, not only by the law but far more so by the market. Deutsche Bank lost its position as one of the world’s leading banks because it put the interests of its investment bankers above those of its customers and shareholders.
Even companies that appear omnipotent today, such as Google or Facebook, will not retain their power forever.

A company’s most important asset is its image, and companies that behave like Deutsche Bank end up incurring massive damage to their images and reputations; their customers lose confidence and flock to their competitors.
In socialist systems, on the other hand, consumers are powerless and at the mercy of state-owned companies. If a state enterprise acts with no regard for the needs of consumers, they have no alternative under socialism because there is no competition.
Under capitalism, consumers can (and do) punish companies that behave selfishly and lose sight of the needs of their customers. Every day, customers vote on the company with their wallets—by buying its products or not.
Monopolies under capitalism are a temporary phenomenon. Even companies that appear omnipotent will eventually be ousted by new competitors as soon as they overreach their power and lose sight of their customers’ needs.
Ever since capitalism has existed, anti-capitalists have criticized the system’s inherent tendency to create monopolies. Lenin wrote over 100 years ago that imperialism and monopoly capitalism are the last stages of capitalism. But the monopolies he criticized at the time no longer exist. Even companies that appear omnipotent today, such as Google or Facebook, will not retain their power forever. Other companies and ambitious young entrepreneurs will seize the opportunity as soon as Google or Facebook starts to act too selfishly.
What is strange is that socialists who criticize capitalism for its tendency to form monopolies are in favor of state-owned companies. After all, the state is the most powerful monopolist of all, with the ability to brutally trample on the needs and wishes of its citizens through its means of coercion and because there are no alternatives for the customer.
The fact that people and companies pursue their own interests is the same in every society. This is not a specific feature of capitalism.
Under capitalism, though, only those entrepreneurs and companies who prioritize their customers’ interests rather than their own self-interest will achieve success in the long-term. Companies that fail to understand and respect what consumers want will lose market share and may even disappear entirely as they are driven out by other companies that better meet their customers’ needs.
Empathy, the ability to recognize the desires and needs of others, is the true basis of capitalism—not unbridled greed and selfishness.