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It appears that I accidentally disabled the automatic loading of MathJax so posts with LaTex were not being displayed properly. I fixed the problem this morning.
Tenebrarum highlights a number of fallacies of mainstream economics in “Theories Only a Mother Could Love“.
1. The fallacy of creating real wealth by printing pieces of paper or getting something for nothing:
‘The underlying assumption that creating additional amounts of money can “stave off economic stagnation” is 180 degrees wrong. It will achieve the exact opposite, namely a structural weakening of the economy – even if, or rather, especially if, economic activity as measured by aggregated data seems to “revive” as a result.
Those who have first access to the newly created money can exercise a demand for real goods without first having contributed anything to the economy’s pool of real funding. This makes it more difficult for those people who actually do make such contributions by their productive efforts to create wealth – as they are forced to compete for a shrinking pool of real resources. As Frank Shostak explains in recent article, what happens is that “exchanges of nothing for something” result from the creation of additional money:
“Before an individual can exercise demand for goods and services, he/she must produce some other useful goods and services. Once these goods and services are produced, individuals can exercise their demand for the goods they desire. This is achieved by exchanging things that were produced for money, which in turn can be exchanged for goods that are desired. Note that money serves here as the medium of exchange — it produces absolutely nothing. It permits the exchange of something for something. Any policy that results in monetary pumping leads to an exchange of nothing for something. This amounts to a weakening of the pool of real wealth — and hence to reduced prospects for the expansion of this pool.”‘
2. The fallacy that falling prices are problematic for consumers:
‘Just as ridiculous as the notion that we suffer from a “demand deficiency” is the assertion that the proper way to spur said demand is to make goods and services more expensive rather than allowing them to become cheaper.
This is what the perverse deflation-phobia of central bankers in effect means: they are not only putting the cart before the horse by asserting that “spurring demand” will magically “spur production”, in addition, they are actually standing the laws of supply and demand on their head.
Perhaps someone, somewhere, knows people whose willingness and capability to buy more goods increases when these goods become more expensive. Maybe they live in some Bizarro dimension we haven’t discovered yet? Who knows really. Meanwhile, the rest of the world (approximately 99.99999%, including central bankers themselves) is hunting for bargains and “everyday low prices”. If it were otherwise, Wal-Mart would not exist.
How devastatingly ridiculous this particular line of argument forwarded by these brain-dead charlatans is came home to us again when Mish mentioned another recent article in the FT entitled “Eurozone fails to benefit from weak currency as oil price slides.” There it is intoned sotto voce:
“The weaker exchange rate will ease pressure on the ECB in its fight to raise inflation back to its target of just below 2 per cent. Mario Draghi, the central bank’s president, has said the currency’s earlier strength explains 0.4 percentage points of the fall in inflation since 2012. In that year, prices were growing 2.7 per cent a year.
But just as this depreciation is starting to fuel inflation, the ECB must contend with a fall in oil prices that all but wipes out the effect of a sliding currency. A weaker euro should swiftly raise the cost of imported energy. Instead, Brent crude has fallen 9 per cent in euro terms this month alone. This is the main reason why eurozone inflation fell again in September to 0.3 per cent, a five-year low – a figure confirmed by data on Thursday.
“The drop in oil prices is a problem for the ECB,” says Marco Valli, an economist at UniCredit, adding, however, that the situation would have been far worse without the single currency’s fall.
So these bien pensants have concluded that “falling oil prices are creating problems for policymakers in the euro area in their struggle against deflation, luckily though the euro has declined sharply, lest they would face an even bigger problem“.
Yes, what a stroke of luck. Due to the ECB making every foreign good and service more expensive for the citizens of the euro area with its monetary debasement policy, Europe has managed to avoid reaping some of the dubious benefits of lower oil prices! They have made us all richer!‘
3. The fallacy of mercantilism via currency debasement:
“A cheaper euro will also please business leaders who have long called for action to curb the value of the currency. But economists warn it is hard to tell how far this bout of depreciation will help the region’s anaemic recovery.
In theory, a rise in company profits should support business investment, hiring and consumption. But analysts warn that the relationship between exchange rates and export volumes is far from clear-cut.”
First of all, who are those unnamed “business leaders who have long called for action to curb the value of the currency”? The only businesses that benefit – very temporarily we should add – from currency devaluation, are those primarily engaged in exports. These benefits are ephemeral and exist only for as long as it takes for internal prices to adjust. Moreover, they come at the expense of the entire rest of the economy, including every single consumer. So the expected effect of “rising company profits” that should lead to “more investment, hiring and consumption” is strictly confined to those in the export trade. Everybody else will see a decline in their fortunes.
Think for instance about companies that import the goods they are selling from abroad or import parts from abroad that are needed in their manufacturing processes. Obviously, they won’t reap any benefits at all. Instead of undertaking new investment or start hiring new employees, they will do the opposite. As Ludwig von Mises stated about the alleged benefits of currency devaluation:
“The much talked about advantages which devaluation secures in foreign trade and tourism, are entirely due to the fact that the adjustment of domestic prices and wage rates to the state of affairs created by devaluation requires some time. As long as this adjustment process is not yet completed, exporting is encouraged and importing is discouraged. However, this merely means that in this interval the citizens of the devaluating country are getting less for what they are selling abroad and paying more for what they are buying abroad; concomitantly they must restrict their consumption. This effect may appear as a boon in the opinion of those for whom the balance of trade is the yardstick of a nation’s welfare.
In plain language it is to be described in this way: The British citizen must export more British goods in order to buy that quantity of tea which he received before the devaluation for a smaller quantity of exported British goods.”
It should be obvious that the balance of trade is not “the yardstick of a nation’s welfare”. Countries don’t trade with each other, individuals do. National borders are entirely incidental to this process and have no economic significance whatsoever. Since trade is voluntary, it follows ipso facto that every trade is regarded as profitable by those engaging in it. If that were not the case, no trade would take place.‘
The format problems were due to stray end tags /div in the post “Hong Kong’s Remarkable Fiscal Policy by Dan Mitchell“. Specifically, they occurred in the a copy of a jpg from Mitchell’s article. When I deleted it, the format problems vanished.
The media hype surrounding artificial neural networks (ANN) is becoming absurd. These articles tend to be uncritical summaries of company press releases. The most over the top articles are those derived from press releases of companies seeking funding.
ANNs are useful machine learning algorithms. They perform reasonably well in static image recognition, some types of pattern recognition, and other tasks. However, they are far too simple in how they model time, feedback, etc. Also, they are very inefficient. Companies such as Google, Baidu, and Microsoft have used enormous numbers of servers to accomplish image recognition and language translation via ANNs. Indeed, the recent surge in so-called deep ANNs is largely due to better and cheaper computing power and some clever algorithmic tricks. As a machine learning algorithm, ANNs have been very successful and will continue to be a useful tool for a growing number of problems in an ever increasing number of areas.
However, the inherent limitations of ANNs will prevent them from every even approaching artificial general intelligence (AGI; see “Artificial General Intelligence Versus Narrow Artificial Intelligence (Machine Learning)“) and will limit their use in machine learning. While much of the hoopla about ANNs has been about their success in image recognition, it has been realized that there are problems lurking. In “The Flaw Lurking In Every Deep Neural Net by Mike James“, I linked to an article that cites a paper demonstrating two problems with ANNs.
On the NuPIC mailing list, Jeff Hawkins made some interesting comments about the limitations of ANNs.
‘Thanks for finding this. It is very interesting. I haven’t read the original paper yet, but I have preliminary thoughts that might be worth sharing.
The first problem they point out is that low level DL (deep learning) neurons are no better than random neurons. This sounds remarkably like our experience using an untrained spatial pooling function, what we call a “random SP”. We have found that using an untrained spatial pooling function works remarkably well. So well that we often don’t train the SP synapses until late in the development process. Spatial pooling is a mapping process and a random SP does the mapping just fine. The problem with untrained spatial pooling is that small changes in the input can lead to a large change in the output. This is what they are reporting in the second problem in the paper. A properly trained SP function is better than random and does not exhibit the “small change in input causes a large change in output” problem.
I don’t know why the DL neurons are not learning to be better than random. I don’t have a good enough insight into exactly how DL works to say. But we do understand a very similar phenomenon in HTM networks and we know that a properly trained HTM network does not have this issue.
On a more broader analysis we know that DL networks are not at all like the neural networks in biological brains. Anyone who says that ANNs and DL networks are similar to biological neural networks doesn’t know much about brains. The biological and DL networks are so different that the brittleness they are seeing almost certainly does not exist in biological brains.
In a couple of recent talks I have started to point out the difference between ANNs and biological networks to drive home that HTM networks are much closer to biology.
- biological and HTM neurons have active distal dendrites, ANN neurons don’t
– biological and HTM neurons have thousands of synapses, typical ANN neurons have dozens
– biological and HTM neurons have unreliable, low precision, synapses, most ANN neurons rely on synaptic weight precision
– biological and HTM neurons learn mostly by forming new synapses, ANN neurons only learn by synaptic weight modification
A typical biological neuron has 100’s of proximal synapses (say 500) and these sum linearly at the soma. The proximal synapses represent only 10% of the synapses on a cell. They correspond most closely to the dozens of synapses on ANN neurons. However, there is a huge difference in how biological neurons use their proximal synapses. The proximal synapses on a biological neuron recognize dozens of unique feedforward patterns, not one. In HTM theory this is how Temporal Pooling is implemented. A cell learns to respond to dozens of unique feedforward input patterns. Temporal pooling is an absolute requirement for inference and every neuron is doing it. For a cell to recognize multiple unique patterns on its proximal dendrites requires that the patterns to be recognized are sparse. So the entire process can only be understood in the context of SDRs.
Again, I am not an expert on deep learning but I have yet to meet a DL expert who understands these concepts or the relevant biology. I am certain that HTM networks applied to applications like vision will not exhibit the problems talked about in this paper. Brains won’t either.‘
Note that SDR stands for sparse distributed representation and HTM stands for hierarchical temporal memory.
ANNs and Hawkins’ HTM are both useful machine learning technologies that perform useful tasks, as is true of many other algorithms. None of them have reached the point to be considered universal algorithms that outperform all others on all problems. Thus, it is up to individuals to select and implement the best algorithm for a specific task.
A few days ago, the widgets on the right side of all pages were no longer visible on the homepage. They remained visible on the About and Libertarian Fiction pages and for individual posts. The only fix that I have been able to discover is that of publishing a blank post. I posted my problem to the wordpress.org forums, so if someone can suggest another way to fix the problem without the blank post, I will implement it.
“What Is a Liberal?” is the title of Henry Hazlitt’s Newsweek column from December 5, 1955. In this article, Hazlitt notes the perversion of the word liberal from designating advocates of freedom to worshipers of the state.
Although this is a overall a good article, I cannot praise the odd first paragraph in which Hazlitt lauds the utterances of federal judge. While Hazlitt was generally a passionate advocate of liberty, he erred in his advocacy of the Cold War and nationalism. Regardless, his remarks about the perversion of language by statists are important and still relevant today.
‘We have all been long indebted to Judge Harold R.
Medina, now of the U.S. Circuit Court of Appeals,
for the patience, balance, and firmness with which
he presided at the trial of eleven top Communists in
1949. A few weeks ago he put us further in his debt by
exposing the inverted semantics into which most of us
have recently fallen in our political discussion—particularly
in the strange use of the word “liberal.” He
regards himself as a liberal, Judge Medina declares, and
he does not intend “to be frightened away because the
Communists and their coadjutors have tried to appropriate
the word ‘liberal’ just as they have the names of
our great Presidents, Abraham Lincoln and Thomas
Jefferson, by the use of Aesopian language, twisting
names and personalities to suit their purpose.”
Today Socialists, fellow travelers, and Communists
all call themselves liberals. As a result, as Judge Medina
points out, the word has taken on “a sinister and evil
connotation.” I should like to supplement his own
remarks on this strange usage and its results.
Originally (as its Latin root liber implies) the liberal
was a man who believed in freedom. The foundations
of the liberal tradition were laid in England by such
great figures as Milton, Locke, Hume, Burke, Adam
Smith, and Mill. Politically, the liberal tradition stood
for freedom for the individual, the Rule of Law, strict
limitation of the powers of government, and decentralization
and diffusion even of these limited powers.
Economically, the liberal tradition stood for protection
of private property, and for freedom of trade, of prices,
of markets, and of enterprise.
But through historical accident and intellectual
confusion, the word “liberal,” particularly in this country,
altered and finally reversed its meaning. Today, in
popular speech, a “liberal” has come to mean a person
who wants constantly to expand the powers of government,
and to centralize them in Washington at the
expense of the states and localities. It has come to mean
a person who disparages Congressional restraint on the
executive power and who prefers bureaucratic discretion
to the Rule of Law. Economically, it has come to
mean a person who distrusts freedom of markets and
freedom of enterprise; who distrusts private ownership
and management and extols government ownership and
management; who presses for more government “planning,”
and who wants to tax and penalize success in
order to subsidize failure. Continue reading