META Stock Slides as Investors Question Payout for Huge AI Spend

How’s this for a “battleground” stock:

Meta stock has dropped about 13% when its latest quarterly earnings were released, then continued to slide until today’s market exuberance over a potential end to the government shutdown. What is the problem?

Meta has invested enormous sums in AI development already, and committed to invest even more in the future. It is currently plowing some 65% (!!) of its cash flow into AI, with no near-term prospects of making big profits there. CEO Mark Zuckerberg has a history of spending big on the Next Big Thing, which eventually fizzles. Meta’s earnings have historically been so high that he can throw away a few billion here and there and nobody cared. But now (up to $800 billion capex spend through 2028) we are talking real money.

Up till now Big Tech has been able to finance their investments entirely out of cash flow, but (like its peers), Meta started issuing debt to pay for some of the AI spend. Leverage is a two-edged sword – – if you can borrow a ton of money (up to $30 billion here) at say 5%, and invest it in something that returns 10%, that is glorious. Rah, capitalism! But if the payout is not there, you are hosed.

Another ugly issue lurking in the shadows is Meta’s dependence on scam ads for some 10% of its ad revenues. Reuters released a horrifying report last week detailing how Meta deliberately slow-walks or ignores legitimate complaints about false advertising and even more nefarious mis-uses of Facebook. Chilling specific anecdotes abound, but they seem to be part of a pattern of Meta choosing to not aggressively curtail known fraud, because doing so would cut into their revenue. They focus their enforcement efforts in regions where their hands are likely to be slapped hardest by regulators, while continuing to let advertisers defraud users wherever they can get away with it:

…Meta has internally acknowledged that regulatory fines for scam ads are certain, and anticipates penalties of up to $1 billion, according to one internal document.

But those fines would be much smaller than Meta’s revenue from scam ads, a separate document from November 2024 states. Every six months, Meta earns $3.5 billion from just the portion of scam ads that “present higher legal risk,” the document says, such as those falsely claiming to represent a consumer brand or public figure or demonstrating other signs of deceit. That figure almost certainly exceeds “the cost of any regulatory settlement involving scam ads.”

Rather than voluntarily agreeing to do more to vet advertisers, the same document states, the company’s leadership decided to act only in response to impending regulatory action.

Thus, the seamy underside of capitalism. And this:

…The company only bans advertisers if its automated systems predict the marketers are at least 95% certain to be committing fraud, the documents show. If the company is less certain – but still believes the advertiser is a likely scammer – Meta charges higher ad rates as a penalty, according to the documents. 

So…if Meta is 94% (but not 95%) sure that an ad is a fraud, they will still let it run, but just charge more for it.  Sweet. Guess that sort of thinking is why Zuck is worth $250 million, and I’m not.

But never fear, Meta’s P/E is the lowest of the Mag 7 group, so maybe it is a buy after all:

Source

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

Is Tesla Stock Grossly Overpriced?

One of the more polarizing topics in investing is the valuation of Tesla stock. Its peers among the Magnificent 7 big tech leaders sport price/earnings ratios mainly in the 30s. Those are high numbers, but growth stocks deserve high P/Es. A way to normalize for expected growth of earnings is to look at the Price/Earnings/Growth (PEG) ratio. This number is usually 1.5-2.0 for a well-regarded company. Anything much over 2 is considered overvalued.

Tesla’s forward P/E of about 270 is nearly ten times higher than peers. Its anticipated growth rate does not seem to justify this astronomical valuation, since its PEG of around 4-10 (depending on assumptions) is way higher than normal. This seems to be a case of the CEO’s personal charisma dazzling shareholders. There is always a new “story” coming out to keep the momentum going.

Tesla’s main actual business is selling cars, electric cars. It has done a pretty good job at this over the past decade, supported by massive government subsidies. With the phasing out of these subsidies by the U.S. and some other governments, and increasing competition from other electric carmakers, it seems unlikely that this business will grow exponentially. Ditto for its smallish ($10 billion revenue) business line of supplying large batteries for electric power storage. But to Tesla fans, that doesn’t really matter. Tesla is valued, not as a car company, but as an AI startup venture. Just over the horizon are driverless robo-taxis (whose full deployment keeps getting pushed back), and humanoid Optimus robots. The total addressable market numbers being bandied about for the robots are in the trillions of dollars.

Source: Wikipedia

From Musk’s latest conference call:

Optimus is Tesla’s bipedal humanoid robot that’s in development but not yet commercially deployed. Musk has previously said the robots will be so sophisticated that they can serve as factory workers or babysitters….“Optimus will be an incredible surgeon,” Musk said on Wednesday. He said that with Optimus and self driving, “you can actually create a world where there is no poverty, where everyone has access to the finest medical care.”

Given the state of Artificial General Intelligence, I remain skeptical that such a robot will be deployed in large numbers within the next five years. It is of course a mind-bending exercise to imagine a world where $50,000 robots could do anything humans can do. Would that be a world where there is “no poverty”, or a world where there is no wealth (apart from the robot owners)? Would there be a populist groundswell to nationalize the robots in order to socialize the android bounty? But I digress.

On the Seeking Alpha website, one can find various bearish articles with the self-explanatory titles of, for instance, Tesla: The Dream Factory On Wall Street, Tesla: Rallying On Robotaxi Hopium, and Tesla: Paying Software Multiples For A Car Business – Strong Sell . There are also bullish pieces, e.g. herehere, and here.

Musk’s personal interaction with shares has propped up their value. He purchased about $1 billion in TSLA shares in September. This is chicken feed relative to its market cap and his net worth, but it apparently wowed TSLA fans, and popped the share price. What seems even more inexplicable is the favorable response to a proposed $1 trillion (!!) pay package for Elon. For him to be awarded this amount, Tesla under his watch would have to achieve hefty boosts both in physical production and in stock market capitalization. But… said package would be highly dilutive (like 12%) to existing shareholders, so, rationally they should give it thumbs down. However, it seems likely that said shareholders are so convinced of Musk’s value that they will approve this pay package on Nov 6, since he has hinted he might leave if he doesn’t get it.

Such is the Musk mystique that shareholders seem to feel that giving him an even greater stake in Tesla than he already has  will cause hundreds of billions of dollars of earnings appear from thin air. From the chatter I read from Wall Street professionals, they view all this as ridiculous magical thinking, yet they do not dare place bets against the Musk fanbase: the short interest in TSLA stock is only a modest 2.2%. Tesla is grossly overvalued, but it will likely remain that way as long as Elon remains and keeps spinning grand visions of the future.

WW II Key Initiatives 3: Kurt Tank Gives Germany a Superior Fighter Plane, the Focke-Wulf 190

This is the third in a series of occasional blog posts on individual initiatives that made a strategic (not just tactical) difference in the course of the second world war.

World War II was not only the biggest, bloodiest conflict, in human history. It played a definitive role in giving us the world we have today. Everyone can find something to complain about in the current state of affairs, but think for a moment what the world would be like if the Axis powers had prevailed.

Having control of the air became crucial in the second world war. It meant you could drop bombs on enemy soldiers, ships, tanks, cities, factories, etc., etc. The Germans showed early on how important that can be. Their terror bombing of the Dutch city of Rotterdam compelled the Netherlands to surrender to spare other cities from being likewise bombed, even though the Dutch armed forces could have held out for some time longer. The German breakthrough in their invasion of France in 1940 was facilitated by a concentrated Stuka dive bombing attack on a key sector of the French front lines. The 1940 Battle of Britain was an air war, where the Germans hoped to whittle the British Air Force capability down enough to permit them to invade across the English Channel. And so on.

The main German fighter plane at first was the Messerschmidt Me 109. It was a good plane, although by 1941 the British Spitfire had become a match for it. Both the Me 109 and the Spitfire were designed around in-line engines, where the cylinders were arranged in two long rows in the engine block. That gave a narrow engine, and hence a skinny profile to the airplane, which tended to reduce wind resistance and make for higher speeds. A weak point of all in-line engines is that they need to have a circulating coolant system, going through a radiator, to cool down the engine block from the heat of the internal combustion. This makes for more complicated maintenance and is very vulnerable to being damaged by enemy fire,

Just when the Brits were starting to wrest air superiority back from the Germans, the FW 190 appeared in the skies over France. Allied pilots were shocked. The new German fighter could out-climb, out-roll, and in many cases out-fight the current Spitfire models. This so-called “butcher bird” gave air superiority back to the Germans.

Its remarkable performance was the result of one man’s engineering philosophy and persistence: Kurt Tank, chief designer at the German aircraft manufacturer Focke-Wulf. Tank was a pilot as well as an engineer, with long and varied prior military experience. He chose a radial engine for his plane, to make it more rugged and easy to maintain. With a radial engine, the individual cylinders all stick out from a central crankcase; airflow past the fins on the cylinders cools the engine. Hence, no vulnerable cooling system and radiator. The conventional thinking was that a radial engine was so fat that an airplane using it would have a wide, draggy profile. His ingenious design features allowed him to make a fast, agile plane. However, was an uphill job for Tank to sell his concept to the German military establishment. Eventually, his results spoke for themselves and the Fw 190 was produced. With its critical spots armored, the Fw 190 was hard to kill. Tank deliberately gave a wide stance and long travel to the landing gear, to allow deployment in rough frontline airfields.

The Fw 190 was a superb low-medium altitude fighter, and was also widely pressed into service (due to its rugged design) as a precision bomber on the front lines. Around 20,000 Fw 190s were produced. They shot down many thousands of Allied planes, killed untold thousands of Allied airmen and soldiers, and destroyed thousands of Allied vehicles, mainly on the Eastern Front. It was not enough to change the ultimate outcome of the war, but Tank stretched it out appreciably, by (largely single-handedly) giving the Germans such a versatile and deadly weapon.

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

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

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

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

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

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

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?

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”.