Author: Scott Buchanan

WW II Key Initiatives 2: “Thatch Weave” Tactic to Counter More-Agile Japanese Fighter Planes

Scott Buchanan1 Comment

This is the second of a series of occasional posts on observations of how some individual initiatives made strategic impacts on World War II operations and outcome.  While there were innumerable acts of initiative and heroism that occurred during this conflict, I will focus on actions that shifted the entire capabilities of their side.

It’s the summer of 1941. The war in Europe between mainly Germany and Britain had been grinding on for around two years, with Hitler in control of nearly all of Europe. The Germans then attacked the Soviet Union, and quickly conquered enormous stretches of territory. It looked like the Nazis were winning. Relations with Japan, which aimed to take over the eastern Pacific region were uneasy. The Japanese had already conquered Korea and coastal China, and were eyeing the resource-rich lands of Southeast Asia and Indonesia. It was a tense time.

The Japanese military had been building up for decades, preparing for a war with the United States for control of the eastern Pacific. They developed cutting edge military hardware, including the world’s biggest battleships, superior torpedoes and a large, well-trained aircraft carrier force. They also produced a new fighter plane, dubbed the “Zero” by Western observers.

Intelligence reports started to trickle in that the Zero was incredibly agile: it could outrun and out-climb and out-turn anything the U.S. could put in the air, and it packed a wallop with twin machine cannons. Its designers achieved this performance with a modestly-powered engine by making the airframe supremely light.

As I understand it, the U.S. military establishment’s response to this intel was fairly anemic. It was such awful news, that seemingly they buried their heads in the sand and just hoped it wasn’t true. Why was this so disastrous? Well, since the days of the Red Baron in World War I, the way you shot down your opponent in a dogfight was to turn in a narrower circle than him, or climb faster and roll, to get behind him. Get him in your gunsights, burst of incendiary machine-gun bullets to ignite his gasoline fuel tanks, and down he goes. If the Zero really was that agile, then it could easily shoot down any U.S. plane with impunity. Even if you started to line up behind a Zero for a shot, he could execute a tight turning maneuver, and end up on your tail, every time. Ouch.

A U.S. Navy aviator named John Thatch from Pine Bluff, Arkansas did take these reports on the Zero seriously. He racked his brains, trying to figure out a way for the clunky American Wildcat fighters to take on the Zeros. He knew the American pilots were well-trained and were good shots, if only they could get some crucial four-second (?) windows of time to line up on the enemy planes.

So, he spent night after night that summer, using matchsticks on his kitchen table, trying to invent tactics that would neutralize the advantages of the Japanese fighters. He found that the standard three-plane section (one leader, two wingmen) was too clumsy for rapid maneuvering. He settled on having two sections of two planes each.   The two sections would fly parallel, several hundred yards apart. If one section got attacked, the two sections would immediately make sharp turns towards each other, and cross paths. The planes of the non-attacked section could then take a head-on shot at the enemy plane(s) that were tailing the attacked section.

Here is a diagram of how this works:

Source: U. S. Naval Institute

The blue planes are the good guys, with a section on the left and on the right. At the bottom of the diagram, an enemy plane (green) gets on the tail of a blue plane on the right. The left and the right blue sections then make sudden 90 degree turns towards one another. The green plane follows his target around the turn, whereupon he is suddenly face-to-face with a plane from the other section, which (rat-a-tat-tat) shoots him down. In a head-to-head shootout, the Wildcat was likely to prevail, since it was more substantial than the flimsy Zero. Afterwards, the two sections continue flying parallel, ready to repeat the maneuver if attacked again. And of course, they don’t just fly along hoping to be attacked, they can make offensive runs at enemy planes as well, as a unified formation. This technique was later dubbed the “Thatch weave”.

Thatch faced opposition to his unorthodox tactics from the legendary inertia of the pre-war U.S. military establishment. Finally, he and his trained team submitted to a test: their four-plane formation went into mock combat against another four planes (all Wildcats), but his planes had their throttles restricted to maximum half power. Normally that would have made them toast, but in fact, with their weaving, they frustrated every attempt of the other planes to line up on them. This demonstration won over many of the actual pilots in the carrier air force, though the brass on the whole did not endorse it.

By some measures the most pivotal battle in the Pacific was the battle of Midway in June, 1942. The Japanese planned to wipe out the American carrier force by luring them into battle with a huge Japanese fleet assembled to invade the American-held island of Midway. If they had succeeded, WWII would have been much harder for the U.S. and its allies to win.

The way that battle unfolded, the U.S. carriers launched their torpedo planes well before their dive bombers. The Japanese probably feared the torpedo planes the most, and so they focused their Zeros on them. Effectively only Thatch and two other of his Wildcats were the only American fighter protection for the slow, poorly-armored torpedo bombers by the time they got to their targets. Using his weave maneuver for the first time in combat, he managed to shoot down three Zeros while not getting shot down himself. This vigorous, unexpectedly effective defense by a handful of Wildcats crucially helped to divert the Japanese fighters and kept them at low altitudes, just in time for the American dive bombers to arrive and attack unmolested from high altitude.

In the end, four Japanese fleet carriers were sunk by the dive-bombers at Midway, at a cost of one U.S. carrier. That victory helped the U.S. to hang on in the Pacific until its new carriers started arriving in 1943. Thatch’s tactic made a material difference in that battle, and was quickly promulgated throughout the rest of the U.S. carrier force. It was not a complete panacea, of course, since the once the enemy knew what you were about to do, they might be able to counter it. However, it did give U.S. fighters a crucial tool for confronting a more-agile opponent, at a critical time in the war. Thatch went on to train other pilots, and eventually became an admiral in the U.S. Navy.

Source: Wikipedia

Circular AI Deals Reminiscent of Disastrous Dot.Com Vendor Financing of the 1990s

Scott BuchananLeave a comment

Hey look, I just found a way to get infinite free electric power:

This sort of extension-cord-plugged-into-itself meme has shown up recently on the web to characterize a spate of circular financing deals in the AI space, largely involving OpenAI (parent of ChatGPT). Here is a graphic from Bloomberg which summarizes some of these activities:

Nvidia, which makes LOTS of money selling near-monopoly, in-demand GPU chips, has made investing commitments in customers or customers of their customers. Notably, Nvidia will invest up to $100 billion in Open AI, in order to help OpenAI increase their compute power. OpenAI in turn inked a $300 billion deal with Oracle, for building more data centers filled with Nvidia chips.  Such deals will certainly boost the sales of their chips (and make Nvidia even more money), but they also raise a number of concerns.

First, they make it seem like there is more demand for AI than there actually is. Short seller Jim Chanos recently asked, “[Don’t] you think it’s a bit odd that when the narrative is ‘demand for compute is infinite’, the sellers keep subsidizing the buyers?” To some extent, all this churn is just Nvidia recycling its own money, as opposed to new value being created.

Second, analysts point to the destabilizing effect of these sorts of “vendor financing” arrangements. Towards the end of the great dot.com boom in the late 1990’s, hardware vendors like Cisco were making gobs of money selling server capacity to internet service providers (ISPs). In order to help the ISPs build out even faster (and purchase even more Cisco hardware), Cisco loaned money to the ISPs. But when that boom busted, and the huge overbuild in internet capacity became (to everyone’s horror) apparent, the ISPs could not pay back those loans. QQQ lost 70% of its value. Twenty-five years later, Cisco stock price has never recovered its 2000 high.

Beside taking in cash investments, OpenAI is borrowing heavily to buy its compute capacity. Since OpenAI makes no money now (and in fact loses billions a year), and (like other AI ventures) will likely not make any money for several more years, and it is locked in competition with other deep-pocketed AI ventures, there is the possibility that it could pull down the whole house of cards, as happened in 2000.  Bernstein analyst Stacy Rasgon recently wrote, “[OpenAI CEO Sam Altman] has the power to crash the global economy for a decade or take us all to the promised land, and right now we don’t know which is in the cards.”

For the moment, nothing seems set to stop the tidal wave of spending on AI capabilities. Big tech is flush with cash, and is plowing it into data centers and program development. Everyone is starry-eyed with the enormous potential of AI to change, well, EVERYTHING (shades of 1999).

The financial incentives are gigantic. Big tech got big by establishing quasi-monopolies on services that consumers and businesses consider must-haves. (It is the quasi-monopoly aspect that enables the high profit margins).  And it is essential to establish dominance early on. Anyone can develop a word processor or spreadsheet that does what Word or Excel do, or a search engine that does what Google does, but Microsoft and Google got there first, and preferences are sticky. So, the big guys are spending wildly, as they salivate at the prospect of having the One AI to Rule Them All.

Even apart from achieving some new monopoly, the trillions of dollars spent on data center buildout are hoped to pay out one way or the other: “The data-center boom would become the foundation of the next tech cycle, letting Amazon, Microsoft, Google, and others rent out intelligence the way they rent cloud storage now. AI agents and custom models could form the basis of steady, high-margin subscription products.”

However, if in 2-3 years it turns out that actual monetization of AI continues to be elusive, as seems quite possible, there could be a Wile E. Coyote moment in the markets:

WW II Key Initiatives 1: FDR Prodded the Navy To Convert Cruisers to Carriers, Just in Time

Scott Buchanan4 Comments

This is the first of a series of occasional posts on observations of how some individual initiatives made strategic impacts on World War II.  Most major decisions were made by teams of qualified engineers or military staff or whatever. But there were cases where one person’s visionary action made a material difference. There were, of course, many thousands of individual acts of initiative and heroism that went into the outcome of any given battle. However, I will focus on actions that shifted the entire capabilities of their side.

In this regard, I recently read how the intervention of President Roosevelt helped to give the U.S. nine additional aircraft carriers in the Pacific at a time when they were critically needed. As of U.S. entry into WWII in December, 1941, America had a total of 7 carriers, while Japan had 11.

It had been clear for a while that the U.S. needed more carriers, but (pre-Pearl Harbor), the Navy was more focused on building battleships; for centuries, big ships carrying big cannons were the vessels that ruled the seas. Navy brass had run studies of carrier sizing, and decided they would rather have fewer, larger carriers, due to operational efficiencies. A problem was these large carriers took years to construct.

Thus, as of 1940 the projections were that the U.S. Navy would receive no new carriers before 1944. As a naval war with Japan looked more and more likely, the President got concerned. FDR had been Assistant Secretary of the Navy during World War I, and maintained an interest in naval affairs, so he had informed judgement here. In October, 1940, Roosevelt sent a letter to the Chief of Naval Operations,  expressing interest in converting merchant ships into carriers for secondary duties such as convoy escort, antisubmarine warfare, aircraft transport, and air support of landing beaches. The Navy’s response was lukewarm. In 1941, FDR proposed that some of the many cruisers under construction could be converted to small carriers. The Navy considered this, and on 13 October 1941, the General Board of the United States Navy replied that such a conversion showed too many compromises to be effective: such carriers would be less stable platforms than the big carriers, and carry less than half the number of planes per ship.

I think most presidents would have given up at this point, but not FDR. He immediately ordered another study (I assume with the implicit message, “…and this time give the boss the answer he wants”). Lo and behold, on 25 October 1941, the Navy’s Bureau of Ships reported that aircraft carriers could in fact be converted from cruiser hulls. They would be of lesser capability, but fast enough for fleet action, and available much sooner than large carriers.

The December 7, 1941 attack on Pearl Harbor changed everything. That ninety-minute raid showed that aircraft carriers were by far the most critical warships. A carrier could reach out a hundred miles and easily sink any battleship with torpedo bombers, as Japan showed on that “day of infamy” and further demonstrated by sinking British battleships near Singapore, and chasing the British navy largely out of both the Pacific and the eastern Indian Oceans. (If the brass had been paying attention, the British Navy had already used carrier-based torpedo bombers to cripple battleships at the Taranto raid and with sinking the Bismarck, well before Pearl Harbor).

The U.S. did end up converting some (slow) merchant ships to carriers, and built a huge number of small, slow, fragile “escort” carriers for transporting planes and for shore bombardment. But there was still an immediate need for better-protected small “fleet” carriers which were fast enough to keep up with the big carriers and which could survive being hit by a bomb. Japanese leaders knew they could not prevail in a long drawn-out war, so their strategy was to inflict so much damage on American military and territorial assets in the first year of conflict that the U.S. would sue for peace under Japanese terms. Japan, like Germany, was very successful at first. The Japanese overran nearly all of Southeast Asia, including the Philippines (an American possession), the Dutch East Indies (a source of rubber, petroleum, and minerals) and the British stronghold at Singapore. They came perilously close to invading Australia. So the first year or so was critical: the Allies needed to survive the onslaught from a better-prepared opponent until American mobilization took full effect.

The Navy settled on repurposing a suite of nine Cleveland class light cruisers which were under construction. These new “light carriers” could carry about 30 planes apiece, compared to a complement of around 60 planes on the full-sized ships. The smaller carriers carried fewer spares, rolled more in heavy seas, and had smaller flight decks which led to more accidents. Nevertheless, they provided a boost to U.S. naval air power at a critical time.

The U.S. entered the war with seven fleet carriers, of which six were assigned to the Pacific. In the course of 1942, four of those six fleet carriers were sunk, and the other two were severely damaged from bombs and torpedoes. Thus, there was a time in October, 1942 that the U.S. had not a single operational carrier in the Pacific, while Japan was fielding around six. That was dire.

No new U.S. carriers were commissioned until the last day of 1942 (U.S.S. Essex). That was a long dry spell. Finally, in the first six months of 1943 eight fleet carriers commissioned. Of these, three were full-sized ships, while five were the cruiser-based light carriers. That finally gave the U.S. some breathing room, which allowed it to defend its assets and pursue offensive operations. These “Independence-class” light carriers fought in many battles, sometimes providing around a quarter of the fleet airpower.

Thereafter, the astonishing mid-century American industrial capacity took over. From mid-1943 through mid-1945 another 17 fleet carriers (including four more Independence-class light carriers in the second half of 1943) poured out of U.S. shipyards, along with some 60 “escort” carriers. By late 1944, this gigantic fleet had utterly overwhelmed Japan’s navy.

But it was largely Roosevelt’s vision and repeated poking of the stodgy Navy staff that produced the first batch of light carriers which helped tipped the balance of forces during the critical first eighteen months of the war.

The “Lost World” of 2% Inflation

Scott BuchananLeave a comment

Here is a chart of the Core Personal Consumer Index for inflation (Core PCE), which is the Fed’s favorite measure on inflation, from 1970 through early 2024:

This chart is from an article by the Richmond Fed, The Origins of the 2 Percent Inflation Target. That article has a long discussion of how and why the Fed decided to name an explicit inflation target of 2% in 2012. Although controlling inflation has been formally part of the Fed’s “dual mandate” since the Federal Reserve Reform Act of 1977, it had traditionally not set a single numerical target. After years of discussions within the Fed, it was decided that the benefits of a clear single target outweighed the potential downsides. 2% was though to be about the lowest you could run, while still giving the Fed some room to cut short term rates in a recession without running up against the dreaded zero lower bound. It was understood that 2% was a loose target, with some years a little over or under to be allowed to balance each other out.

That Richmond Fed article was published in early 2024. At that point, inflation was falling quickly and steadily from its post-Covid high, as consumers finished spending down their gigantic stimulus package windfalls.

Unsurprisingly, this article concludes that “Even during this period, long-run inflation expectations have remained anchored, rising no higher than 2.5 percent, according to the Cleveland Fed.”

That was about 18 months ago. The actual path of inflation since then has not be a descent to 2-2.5%. Between gigantic peacetime deficits by two administrations, and the results of tariffs, inflation seems to have leveled out at around 3%:

Source

The sub-2% inflation that was normal for twenty years (2000-2020) may now be a lost world.   This puts the Fed in an awkward spot. Even ignoring the irresponsible squawking from some quarters of the government, it will not be an easy decision to keep cutting rates (to address soft employment) if inflation stays this high. The Fed’s mantra this time around is that the current inflation is just a transient response to tariffs and so can be largely discounted. But I recall similar verbiage in 2021, as the Fed dismissed the ramping inflation back then as merely a transitory effect of pandemic supply chain restrictions. They were wrong then, and I suspect it would be wrong now to be too complacent. The 1970s-80’s showed that once the inflation genie gets out of the bottle, it can be very costly to subdue it. Whether 2.0 % is still the right target, however, may be open to debate.

Shift in AI Usage from Productivity to Personal Therapy: Hazard Ahead

Scott BuchananLeave a comment

A couple of days ago I spoke with a friend who was troubled by the case of Adam Raine, the sixteen-year-old who was counseled by a ChatGPT AI therapy chatbot into killing himself.  That was of course extremely tragic, but I hoped it was kind of an outlier. Then I heard on a Bloomberg business podcast that the number one use for AI now is personal therapy. Being a researcher, I had to check this claim.

So here is an excerpt from a visual presentation of an analysis done by Marc Zao-Sanders for Harvard Business Review. He examined thousands of forum posts over the last year in a follow-up to his 2024 analysis to estimate uses of AI. To keep it tractable, I just snipped an image of the first six categories:

It’s true: Last year the most popular uses were spread across a variety of categories, but in 2025 the top use was “Therapy & Companionship”, followed by related uses of “Organize Life” and “Find Purpose”. Two of the top three uses in 2024, “Generate Ideas” and “Specific Search”, were aimed at task productivity (loosely defined), whereas in 2025 the top three uses were all for personal support.

Huh. People used to have humans in their lives known as friends or buddies or girlfriends/boyfriends or whatever.  Back in the day, say 200 or 2000 or 200,000 or 2,000,000 years ago, it seems a basic unit was the clan or village or extended kinship group. As I understand it, in a typical English village the men would drift into the pub most Friday and Saturday nights and banter and play darts over a pint of beer.  You were always in contact with peers or cousins or aunts/uncles or grandmother/grandfathers who would take an interest in you, and who might be a few years or more ahead of you in life. These were folks you could bounce around your thoughts with, who could help you sort out what is real. The act of relating to another human being seems to be essential in shaping our psyches. The alternative is appropriately termed “attachment disorder.”

The decades-long decline in face-to-face social interactions in the U.S. has been the subject of much commentary. A landmark study in this regard was Robert Putnam’s 1995 essay, “Bowling Alone: America’s Declining Social Capital”, which he then expanded into a 2000 book. The causes and results of this trend are beyond the scope of this blog post.

The essence of the therapeutic enterprise is the forming of a relational human-to-human bond. The act of looking into another person’s eyes, and there sensing acceptance and understanding, is irreplaceable.

But imagine your human conversation partner faked sympathy but in fact was just using you.  He or she could string you along by murmuring the right reflective phrases (“Tell me more about …”,  “Oh, that must have been hard for you”, blah, blah, blah) but with the goal of getting money from you or turning you towards being an espionage partner. This stuff goes on all the time in real life.

The AI chatbot case is not too different than this. Most AI purveyors are ultimately in it for the money, so they are using you. And the chatbot does not, cannot care about you. It is just a complex software algorithm, embedded in silicon chips. To a first approximation, LLMs simply spit out a probabilistic word salad in response to prompts. That is it. They do not “know” anything, and they certainly do not feel anything.

Here is what my Brave browser embedded AI has to say about the risks of using AI for therapy:

Using AI chatbots for therapy poses significant dangers, including the potential to reinforce harmful thoughts, fail to recognize crises like suicidal ideation, and provide unsafe or inappropriate advice, according to recent research and expert warnings. A June 2025 Stanford study found that popular therapy chatbots exhibit stigmatizing biases against conditions like schizophrenia and alcohol dependence, and in critical scenarios, they have responded to indirect suicide inquiries with irrelevant information, such as bridge heights, potentially facilitating self-harm. These tools lack the empathy, clinical judgment, and ethical framework of human therapists, and cannot ensure user safety or privacy, as they are not bound by regulations like HIPAA.

  • AI chatbots cannot provide a medical diagnosis or replace human therapists for serious mental health disorders, as they lack the ability to assess reality, challenge distorted thinking, or ensure safety during a crisis.
  • Research shows that AI systems often fail to respond appropriately to mental health crises, with one study finding they responded correctly less than 60% of the time compared to 93% for licensed therapists.
  • Chatbots may inadvertently validate delusional or paranoid thoughts, creating harmful feedback loops, and have been observed to encourage dangerous behaviors, such as promoting restrictive diets or failing to intervene in suicidal ideation.
  • There is a significant risk of privacy breaches, as AI tools are not legally required to protect user data, leaving sensitive mental health information vulnerable to exposure or misuse.
  • The lack of human empathy and the potential for emotional dependence on AI can erode real human relationships and worsen feelings of isolation, especially for vulnerable individuals.
  • Experts warn that marketing AI as a therapist is deceptive and dangerous, as these tools are not licensed providers and can mislead users into believing they are receiving professional care.

I couldn’t have put it better myself.

Leveraged Bullion and Mining Funds to Cash in on the Gold Bonanza

Scott BuchananLeave a comment

Stocks (e.g., S&P 500) are up 12.5 % year to date. That is pretty good for 9.5 months. But gold has been way better, up 40%:

Fans of gold cite various reasons for why its price should and must keep going up (out of control federal debt and associated money-printing, de-dollarization by non-Western nations, buying by central banks, etc.). I have no idea if that is true. But if it is, that raises the question in my mind:  for the limited amount of funds I have to invest in gold, can I get more bang for my investing bucks, assuming gold continues to rise?

It turns out the answer is yes.  A straightforward way is to buy into a fund which is 2X or 3X leveraged to the price of gold. If gold goes up 10%, then such a fund will go up 20% or 30%. Let’s see how two such funds have done this year, UGL (a large 2X gold fund) and a newer, smaller 3X fund, SHNY:

Holy derivatives, Batman, that leverage really works! With GLD (1X gold) up 40%, UGL was up 80% year to date, and 3X SHNY is up 120%. So, your $10,000 would have turned into $24,000. The mighty S&P500 (blue line) looks rather pitiful in comparison.

But wait, there’s more. Let’s consider gold “streamers”, like WPM (Wheaton Precious Metals) or FNV. They give money to mines in return for a share of the production at fixed, discounted prices, so their cash flow soars when gold prices rise. Year to date, FNV is up 73%, while WPM is up 91%.

And then there are the gold miners themselves. They tend to have fairly fixed breakeven costs of production, currently around $1200-1400/oz.  Again, their profit margin rockets upward when gold prices get far above their breakeven:

Source

GDX is a large fund of representative mining stocks. For icing on the cake, there are funds that are 2X (NUGT) or 3X (GDXU) leveraged to the price changes in mining stocks. The final chart here displays their year-to-date performance in all their glory:

The blue S&P 500 line is lost in the noise, and even the orange 40% GLD line is left in the dust. The 1X miner fund was up 108%, the 2X fund NUGT was up 276%, and the 3X GDXU was up 506%. Your $10,000 would have turned into $51,000.

Of course, what goes up fast will also come down fast, since leverage works both ways. For instance, from Oct 21 to Dec 30, 2024, gold was down a mere 4%, but WPM was down 15%, the 1X gold miner GDX was down 20%, and 3X GDXU down an eye-watering 54%. That means that your $10,000 turned into $4,600 in two months. Imagine watching that unfold, and not panic-selling at the bottom. Gold fell by more than half between 2011 and 2015. If it fell by even 20% (i.e., gave up half of this year’s gains), I could see a 3X miner fund losing over 90% of its value (just a guess).

One more twist to mention here is the “stacked” fund GDMN, which uses derivatives to be long 1X gold PLUS 1X gold miners. It is up 151% this year, which is nearly four times as much as gold. This fund seems to have a nice combination of decent leverage with moderate volatility. It has on average kept pace with the 2X miner fund NUGT, with shallower dips. NUGT has surged way ahead in the past two months as miner stock prices have gone nuts, but that is somewhat exceptional.

Disclaimer: As usual, nothing here should be considered advice to buy or sell any security.

What is in a QR Code?

Scott Buchanan1 Comment

Bar codes have been common in retail stores since the 1970s. These give a one-dimensional read of digital data. The hardware and software to decode a bar code are relatively simple.

The QR code encodes information in a two-dimensional matrix. The QR code, short for quick-response code, was invented in 1994 by Masahiro Hara of the Japanese company Denso Wave for labelling automobile parts. It can pack far more information in the same real estate than a bar code, but it requires sophisticated image processing to decode it. Fortunately, the chip power for image processing has kept up, so smart phones can decode even intricate QR codes, provided the image is clear enough.

Here is the QR code that encodes the URL for Wikipedia, i.e., the characters: “https://en.wikipedia.org/wiki/Wikipedia”.

Like most QR codes, it has three distinctive square patterns on three corners, and a smaller one set in from the fourth corner, that give information to the image processing software on image orientation and sizing.

As time goes on, more versions of QR codes are defined, with ever finer patterns that convey more information. For instance, here is a medium-resolution QR Code (version 3), and a very high resolution QR code (Version 40):

Version 3 QR Code (29×29), encodes up to 50 characters

Version 40 QR Code  (177×177), encodes up to 1852 characters

My phone could not decode the Version 40 above; the limit may be how much detail the camera could capture.

QR codes use the  Reed–Solomon error correction methodology to correct for some errors in image capture or physical damage to the QR code. For instance, this QR code with the torn-off corner still decodes properly as the URL for Wikipedia (whole image shown above):

Torn QR Code still decodes properly.

Getting down a little deeper in the weeds, this image shows, for Version 3  (29×29) QR code, which pixels are devoted to orientation/alignment (reddish, pinkish), which define the format (blueish), and which encode the actual content (black and white):

Uses Of QR Codes

A common use of QR codes is to convey a web link (URL), so pointing your phone at the QR code is the equivalent of clicking on a link in an email. Here is an AI summary of uses:

They are used to access websites and digital content, such as restaurant menus, product information, and course details, enabling a contactless experience that reduces the need for printed materials. Smartphones can scan QR codes to connect to Wi-Fi networks by automatically entering the network name (SSID), password, and encryption type, simplifying the process for users. They facilitate digital payments by allowing users to send or receive money through payment apps by scanning a code, eliminating the need for physical cash or cards. QR codes are also used to share contact information, such as vCards, and to initiate calls, send text messages, or compose emails by pre-filling the recipient and message content. For app downloads, QR codes can directly link to the Apple App Store or Google Play, streamlining the installation process. In social media and networking, they allow users to quickly follow profiles on platforms like LinkedIn, Instagram, or Snapchat by scanning a code. They are also used for account authentication, such as logging into services like WhatsApp, Telegram, or WeChat on desktop by scanning a code with a mobile app. Additionally, QR codes are employed in marketing, event ticketing, and even on gravestones to provide digital access to obituaries or personal stories. Their versatility extends to sharing files like PDFs, enabling users to download documents by scanning a code. Overall, QR codes act as a bridge between the physical and digital worlds, enhancing efficiency and interactivity across numerous daily activities.

Note that your final statement in this world might be a QR code on your gravestone.

Security with QR Codes

On an iPhone, if “Scan QR Codes” (or something similar) has been enabled, pointing the phone at a QR code in Camera mode will display the first few characters of the URL or whatever, which gives you the opportunity to click on it right then. If you want to be a bit more cautious, you can take a photo, and then open Photos to look at the image of QR code. If you then press on the photo of the QR code, up will come a box with the entire character string encoded by the QR code. You can then decide if clicking on something ending in .ru is what you really want to do.

Accessing a rogue website can obviously hurt you. And even if you aren’t dinged by that kind of browser exploit, the reader’s permissions on your phone may allow use of your camera, read/write contact data, GPS location, read browser history, and even global system changes. The bad guys never sleep. Who would have thought that a QR code on a parking meter posing as a quick payment option could empty your bank account? Our ancestors needed to stay alert to physical dangers, for us it is now virtual threats.

ACKNOWLEDGEMENT: The bulk of the content, and all the images, in this blog post were drawn from the excellent Wikipedia article “QR code”.

Bears and Bulls Battle Over Nvidia Stock Price

Scott BuchananLeave a comment

Nvidia is a huge battleground stock – – some analysts predict its price will languish or crash, while others see it continuing its dramatic rise. It has become the world’s most valuable company by market capitalization.  Here I will summarize the arguments of one bear and one bull from the investing site Seeking Alpha.

In this corner…semi-bear Lawrence Fuller. I respect his opinions in general. While the macro prospects have turned him more cautious in the past few months, for the past three years or so he has been relentlessly and correctly bullish (again based on macro), when many other voices were muttering doom/gloom.  

Fuller’s article is titled Losing Speed On The AI Superhighway. This dramatic chart supports the case that NVDA is overvalued:

This chart shows that the stock value of Nvidia has soared past the value of the entire UK stock exchange or the entire value of US energy companies. Fuller reminds us of the parallel with Cisco in 2000. Back then, Cisco was a key supplier of gateway technology for all the companies scrambling to get into this hot new thing called the internet. Cisco valuation went to the moon, then crashed and burned when the mania around the internet subsided to a more sober set of applications. Cisco lost over 70% of its value in a year, and still has not regained the share price it had 25 years ago:

… [Nvidia] is riding a cycle in which investment becomes overinvestment, because that is what we do in every business cycle. It happened in the late 1990s and it will happen again this time.

…there are innumerable startups of all kinds, as well as existing companies, venturing into AI in a scramble to compete for any slice of market share. This is a huge source of Nvidia’s growth as the beating heart of the industry, similar to how Cisco Systems exploded during the internet infrastructure boom. Inevitably, there will be winners and losers. There will be far more losers than winners. When the losers go out of business or are acquired, Nvidia’s customer base will shrink and so will their revenue and earnings growth rates. That is what happened during the internet infrastructure booms of the late 1990s.

Fuller doesn’t quite say Nvidia is overvalued, just that it’s P/E is unlikely to expand further, hence any further stock price increases will have to be produced the old-fashioned way, by actual earnings growth. There are more bearish views than Fuller’s, I chose his because it was measured.

And on behalf of the bulls, here is noob Weebler Finance, telling us that Nvidia Will Never Be This Cheap Again: The AI Revolution Has Just Begun:

AI adoption isn’t happening in a single sequence; it’s actually unfolding across multiple industries and use cases simultaneously. Because of these parallel market build-outs, hyper-scalers, sovereign AI, enterprises, robotics, and physical AI are all independently contributing to the infrastructure surge.

…Overall, I believe there are clear signs that indicate current spending on AI infrastructure is similar to the early innings of prior technology buildouts like the internet or cloud computing. In both those cases, the first waves of investment were primarily about laying the foundation, while true value creation and exponential growth came years later as applications multiplied and usage scaled.

As a pure picks and shovels play, Nvidia stands to capture the lion’s share of this foundational build-out because its GPUs, networking systems, and software ecosystem have become the de facto standard for accelerated computing. Its GPUs lead in raw performance, energy efficiency, and scalability. We clearly see this with the GB300 delivering 50x per-token efficiency following its launch. Its networking stack has become indispensable, with the Spectrum-X Ethernet already hitting a $10b annualized run rate and NVLink enabling scaling beyond PCIe limits. Above all, Nvidia clearly shows a combined stack advantage, which positions it to become the dominant utility provider of AI compute.

… I believe that Nvidia at its current price of ~$182, is remarkably cheap given the value it offers. Add to this the strong secular tailwinds the company faces and its picks-and-shovels positioning, and the value proposition becomes all the more undeniable.

My view: Out of sheer FOMO, I hold a little NVDA stock directly, and much more by participating in various funds (e.g. QQQ, SPY), nearly all of which hold a bunch of NVDA.  I have hedged some by selling puts and covered calls that net me about 20% in twelve months, even if stock price does not go up.   Nvidia P/E (~ 40) is on the high side, but not really when considering the growth rate of the company. It seems to me that the bulk of the AI spend is by the four AI “hyperscalers” (Google, Meta, Amazon, Microsoft). They make bazillions of dollars on their regular (non-AI) businesses, and so they have plenty of money to burn in purchasing Nvidia chips. If they ever slow their spend, it’s time to reconsider Nvidia stock. But there should be plenty of warning of that, probably no near time crisis: last time I checked, Nvidia production was sold out for a full year ahead of time. I have no doubt that their sales revenue will continue to increase. But earnings will depend on how long they can continue to command their stupendous c. 50% net profit margin (if this were an oil company, imagine the howls of “price gouging”).

As usual, nothing here should be considered advice to buy or sell any security.

Government Makes Quasi-Nationalization Deal to Assure Supply of Critical Rare Earths for Defense 

Scott BuchananLeave a comment

If top government officials were regular readers of this blog, they would have been warned by a headline here more than two years ago, “China To Squeeze West by Restricting Export of Essential Rare Earths “.  For the last few years, the U.S. has been trying to limit Chinese access to the most powerful computing chips, which are largely made by American company Nvidia. But China has some high cards to play in this game. It produces some 90% of refined rare earths and rare earth products like magnets.  These super-powerful neodymium-containing magnets are utterly critical components in all kinds of high-tech products, including wind turbine generators and electric motors for electric vehicles and drones, and miscellaneous military hardware.

It has been painfully obvious at least since 2010, when China put the squeeze on Japan by unofficially slowing rare earth exports to Japan over a territorial dispute, that it was only a matter of time before China played that card again. But the West slumbered on. There is a reasonable amount of rare earth ores that are mined outside China, but nobody wanted to build and operate the expensive and environmentally messy processes to refine the rare earth minerals (carbonates, oxides, phosphates) into the pure metals. Unlike the esoteric and hard-to-imitate processing for cutting edge computing chips, anyone can gear up and start refining rare earth ores. It mainly just takes money, lots and lots of it, to build and operate all the processing equipment for the multiple steps involved*. There was little free market incentive for a Western company to invest in expensive processing, since China could readily bankrupt them by cutting prices as soon as they started up their shiny new process line. Reportedly, the Chinese used this tactic twice before (in 2002 and 2012) to kill nascent refining of the rare earth ores at Mountain Pass mine in California.

As of April of this year, in response to ongoing U.S. export restrictions on chips, China threw its latest rare earth card down on the table, requiring export licenses and imposing other restrictions that throttled rare earth exports. Western manufacturers were soon howling in pain. As of early June:

Global automakers are sounding the alarm on an impending shortage of rare earth magnets as China’s restrictions on the material vital for the automotive, defence and clean energy industries threaten production delays around the world.

German automakers became the latest to warn that China’s export restrictions threaten to shut down production and rattle their local economies, following a similar complaint from an Indian EV maker last week. U.S., Japanese and South Korean automakers warned President Donald Trump on May 9 car factories could close.

The Trump administration quickly caved on chips and in July permitted boatloads of high-end H20 Nvidia chips to ship to China, in return for resumption of rare earth exports from China. Score one for the CCP. As of mid-August, rare earth shipments had climbed back to around half of their pre-May levels, but China ominously warned Western companies against trying to stockpile any reserves of rare earths, or they would “face shortages” in the future.

After this ignominious face-slapping, the administration finally did something that should have been done years ago: they gave an American company a solid financial incentive to buckle down and do the dirty work of refining rare earth ores at large scale. The Defense Department inked a deal with MP Materials Corp, the current operator of the Mountain Pass mine and the modest refining operation there to quickly ramp up production:

The Department of Defense is investing capital in MP across several fronts. This includes a $400 million convertible preferred equity, struck at a fixed conversion price of $30.03. The government gets 10-year MP stock warrants also set for a $30.03 price. As planned, this would get the Department of Defense to about a 15% ownership position in MP Materials. In addition, the Department of Defense will lend MP Materials $150 million at a highly competitive interest rate to help the company expand its heavy rare earth element separation capabilities.

It’s not just a financing deal, however. This arrangement also provides a striking level of influence over pricing and profitability for MP Materials going forward.

For one thing, the Department of Defense will provide a price floor of $110 per kilogram for NdPr. NdPr is a product that is a combination of neodymium and praseodymium. This is a generous floor price…

The Department of Defense’s involvement now gives MP Materials the runway necessary to build what’s being dubbed the 10X magnet manufacturing expansion plant. The Department of Defense is committed to buying the output of this plant with a controlled cost-plus pricing structure. And there will be a profit split with the DoD getting a significant chunk of the upside above certain EBITDA thresholds.

This is being billed as a private-public partnership, but it is akin to nationalization. The government will be heavily involved in planning output and setting pricing here, as well as sharing in profits.  Fans of laissez-faire free markets may be understandably queasy over this arrangement, but national security considerations seem to make this necessary.

I predict that further “private-public” deals will be struck to subsidize Western production of vital materials. Let’s be clear: massive subsidies or similar incentives, in one form or another, will be needed. And this means that Americans will have to devote more resources to grinding out industrial materials, and less to consumer goods; hence, we will likely live in smaller houses, perhaps (gasp) lacking granite countertops and recessed lighting. Economics is all about trade-offs.

Due to its vast, lower-paid, hard-working and highly-capable workforce, the whole Chinese supply chain and production costs run far, far cheaper than anything in the West. We don’t have to produce 100% of what we use, even say 40% might be enough to keep from being helplessly squeezed by another nation. How to do this without descending into unproductive rent-seeking rip-offs will be a challenge.

Some other materials candidates:  China has as of December 2024 completely shut off exports to the U.S. of three key non-rare earth technical elements, gallium, germanium and antimony, so those might be a good place to start. China mines or refines between half and 90% of global supply of those minerals. Also, China has instituted export regulations of for more key metals (tungsten, tellurium, bismuth, indium and molybdenum-related products), so these may be further subjects for squeeze plays. Finally, “China is the world’s top graphite producer and exporter, and also refines more than 90% of the world’s graphite into a material that is used in virtually all EV batteries,” so that is yet another vital material where the West must decide how much it is worth to break its dependence on an unreliable trading partner.

A Modern-Day Pirate Seeks to Recover Up to Ten Billion Dollars of Gold from Republic Shipwreck Off Nantucket

Scott Buchanan4 Comments

Arrrr, me hearties! What think ye of a venture to raise a gigantic hoard of sunken treasure?

The story begins with the last voyage of RMS Republic. This was a luxurious passenger steamship of the White Star Line, which sailed between Europe and America.

Wikipedia

Republic was a large vessel (15,000 tons displacement) for her day, and was known as the “Millionaires’ Ship” for the number of wealthy Americans who sailed back and forth on her. A number of such magnates were aboard on her last voyage. In January, 1909 Republic left New York City with  passengers and crew, bound for Gibraltar and Mediterranean ports. In thick fog off the island of Nantucket, Republic was rammed amidships by the Italian liner Florida. Florida’s bow was crumpled back, but she stayed afloat. The damage to Republic was fatal. The engine rooms flooded, the ship began to list, and it was clear that the passengers needed to be evacuated.

Using the new-fangled Marconi “wireless” apparatus, a CQD distress signal was broadcast by radio operator Jack Binns. This was the first wireless transmission that resulted in a major life-saving marine rescue. (Binns had to scramble and improvise to get this done, since his apparatus had been damaged and the ship’s power was lost as a result of the collision, so he was a technology nerd turned hero, duly lauded by a ticker-tape parade). It was hard for other ships to locate Republic in the fog, but eventually nearly all the passengers and crew from Republic and from the damaged Florida were safely transferred to other ships.

As was the custom of the time, she did not carry enough lifeboats to hold all the passengers, but only enough to ferry them to some other ship; it was assumed that on the busy Atlantic route there would always be other large ships around.  (That scheme played out well with the Republic, but when sister White Star liner Titanic sank four years later, the dearth of lifeboats helped doom some 1,500 people to a watery grave.) Despite efforts to save her, Republic went down stern-first on January 24. She was the largest ship ever to sink at the time.  There were reports at the time that she was carrying some $3 million (1909 dollars) of gold, which went down with the ship. That would translate to hundreds of millions of dollars today for that gold.

But wait, there’s more, maybe much more. Enter a modern-day pirate, Martin Bayerle:

Vineyard Gazette

Bayerle looks like a pirate, sporting a genuine eyepatch covering an eye lost in an explosives accident. He killed a man who was fooling around with his wife, which seems like a piratical thing to do, and he is after a ship’s gold.   His salvage enterprise is even formally described in legal court papers as “modern day pirates”. 

His company, Martha’s Vineyard Scuba Headquarters, Inc. (“MVSHQ”), acquired salvage rights to the wreck of the Republic. In 2013 he published a book, The Tsar’s Treasure, detailing his thesis that Republic carried far more gold than was publicly acknowledged. He notes that there was no formal inquiry regarding the sinking of Republic, which was highly unusual and is suggestive of a cover-up. Cover-up of what?

Well, Europe at the time was a tinder box of potential conflict, which did in fact erupt five years later in World War I.  Czarist Russia was a key part of the European military equation. Britain was counting on Russia to help contain the emerging militaristic Germany. Russia had incurred huge debts in its disastrous war with Japan in 1905. Russia was about to issue a new round of bonds in 1909, to roll over its debt from 1905. It was critical that that bond issuance would go forward.


Bayerle believes that a large amount of gold was stashed in the hold of the Republic, destined for European banks, to support the Russian bonds of 1909. The revelation that that gold was lost would have jeopardized this crucial financial transaction, perhaps leading to Russia’s collapse, which is something Britain could not afford. Hence, the cover-up. Bayerle estimates that the value of this trove is up to $10 billion in today’s money. Shiver me timbers!

This geopolitical speculation, together with stories of failed previous salvage attempts on Republic, all make for a rollicking yarn. Is it for real? Nobody knows, but Bayerle is offering investors a chance at a slice of the booty. If you are inclined to “Dare to dream the impossible” (per the website), you have the opportunity to invest in his Lords of Treasure enterprise as they make a dive on the site this summer.


I don’t happen to have that much risk appetite, but it should be an interesting story to follow.

UPDATE

According to the June 2025 Lords of Fortune Newletter, salvage operations originally slated for 2025 are being put off till 2026, as funding is still being developed. We note the technical challenge of picking through hundreds of tons of steel plate and girders, deep underwater, in search of a smallish volume of gold. On the other hand, Capt. Bayerle’s recent researches suggest the gold trove may be even larger than earlier estimated, up to some $30 billion. So high risk meets high reward here. It seems ironic that VC’s will throw say $300 million into dubious tech unicorns or the latest crap-coin, but eschew a pretty sure bet of at least breaking even here (if only the lowest estimates of the Republic gold pan out) with a good shot at 10X-ing their investment. We will stay tuned.