76report

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October 11, 2024
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76report

October 11, 2024

Positioning for a Productivity Bonanza

The technological landscape that we all marveled at as children—eating popcorn as we watched science fiction movies—is arriving in real time. Tesla held a Robotaxi event on October 10, 2024, featuring the highly functioning Optimus robot, which the company has described as “your personal R2D2 / C3PO, but better.”


Speaking at the event, the company’s founder Elon Musk, who happens to be the richest person in the world, said he expects we will eventually be able to buy his robot for less than $30,000. He also revealed plans to launch fully autonomous self-driving vehicles in Texas and California by 2025.

So everything we've developed for our cars, the batteries, power electronics, the advanced motors, gearboxes, the software, the AI inference computer, it all actually applies to a humanoid robot. It's the same techniques—it's just a robot with arms and legs instead of a robot with with wheels. - Elon Musk (10/10/2024)

Tesla is known for pioneering electric cars, but the real future of Tesla is artificial intelligence—designing products, whether a car or a robot, that can think and act independently.


Tesla is one of several of the largest and most successful business enterprises in world history that are now investing hundreds of billions of dollars annually to develop Artificial General Intelligence (AGI). The goal is to create a computing capability that meets and exceeds human intelligence.


It is unclear when AGI might become a reality, but there is widespread belief that it is indeed a question of when and not if. Accompanying this perspective is the emerging belief that the world is on the cusp of an unprecedented productivity boom.


Technological progress is generally speaking a continuous process, although there are periods when it is more accelerated. Between 1950 and 1970, for example, the U.S. experienced a particularly high rate of productivity growth, close to 3%. This was driven by the implementation of a wide range of scientific breakthroughs.


The difference this time is that the pace of change is expected, by many well-informed observers, to be exponential rather than linear. One reason is that the technology being developed—artificial intelligence—will help produce its own advancements.


We are not just making better computing systems now. We are making computing systems that can make themselves better.


If we are on the cusp of an AI-driven step-up in productivity growth, this will have serious implications for the economy and markets. Investors need to understand the potentially complicated consequences of this scenario, which presents both risks and opportunities.


Labor productivity is a critical concept within economics. It is essentially a measure of output per hour worked. Technological advancements allow human beings to get more done in a given time frame.


When productivity increases, this means less labor is required to achieve the same level of output. Businesses need fewer workers, or they can do more with the same number of workers.


Productivity improvements are generally quite positive. Jobs lost to efficiency gains are eventually replaced by new jobs that are the result of wealth creation brought about by those efficiency gains.


A century ago, about 30% of the U.S. population worked on farms, while today the figure is closer to 2%. As the U.S. industrialized, many farm workers became factory workers. Now, more than 80% of Americans with private sector jobs are in service sectors (such as administration, professional services, healthcare and education).


In a real sense, productivity growth is progress. For the most part, the process is gradual. Old jobs are replaced by new, often better ones, as the economy becomes wealthier and more advanced.


The famous Austrian economist Joseph Schumpeter called this process “creative destruction.” While on balance positive, it does produce casualties along the way. Very often, there are localized impacts where the downside is borne by a small number of people (e.g., laid-off workers in a factory that was automated) for the slight benefit of a much larger number of people (who enjoy lower cost goods).


Innovation winners and losers


Innovation-driven changes to the economy can have dramatic social and political impacts. These impacts can result in policy changes that ultimately influence markets.


We already see some of them playing out in the current Presidential election in the huge divide between the industrial/agricultural interior of the country versus coastal areas.


Globalization and trade deals like NAFTA are often blamed (to some extent justifiably) for the disappearance of manufacturing jobs in the American heartland over the past several decades. Technological advancement, however, is arguably the more important variable.


The reality is, with robotics, automation and other incremental improvements in manufacturing productivity, not as many human bodies are needed on factory floors. Technology, which is portable, has also enabled globalization and the relocation of manufacturing operations to far-flung regions of the world.


Outside the U.S., labor and land are often cheaper, energy may be more available, and environmental and workplace standards are lower. Technological advancements, in the form of highly automated and sophisticated logistics and transportation systems, have allowed for the creation of extremely complicated international supply chains.


Much of the momentum behind the MAGA movement, including its success in Midwestern swing states, comes from its focus on the consequences of American de-industrialization. A resident of Manhattan or Los Angeles, who may be employed within the financial services, technology or entertainment sector, is likely to be much less sensitive to where physical products are made than someone in Michigan or Wisconsin.


Will the entire U.S. become the Rust Belt?


The manufacturing sector, from an employment perspective, has borne the brunt of technological innovation. AI, however, may cast a much wider net.


AI is in a multi-year phase of development now where capacity is being built through the creation of data centers (many of which are, ironically, being located in states like Ohio and Wisconsin). These data centers are being used to develop and train the Learned Language Models (LLMs) that drive AI applications.


Once all this investment is actually put to work, the consequences to the national labor market could be considerable. This time, it may not just be factory workers who find themselves replaced by machines.


In a recent article that appeared in The Wall Street Journal, Silicon Valley entrepreneur and venture capitalist Vinod Khosla (whom Forbes ranks among the top 400 wealthiest people in the world) outlined his expectations of a massive increase in labor productivity resulting from AI deployment. Khosla was the co-founder of Sun Microsystems and has been a partner at one of the most successful venture capital firms, Kleiner Perkins, since 1986.

Most expertise in the world, whether you’re talking about structural engineers, oncologists, mental health therapists or primary care doctors, or journalists and teachers, that expertise will be near-free for all of us to access. - Vinod Khosla

Khosla believes more than 60% of jobs today can be replaced by AI. He expects U.S. GDP growth to climb towards 5%, which is approximately double current levels, as a result of productivity gains.


We think it makes a great deal of sense to pay heed to the most connected individuals in the tech and venture capital industry, who are naturally closest to developments on the ground. To a large extent, these developments are happening at private companies, like OpenAI.


In a recent @76research video segment, we shared commentary by former Google CEO Eric Schmidt, who believes the transformative impact of AI is actually underestimated, notwithstanding the tremendous attention AI is now getting. A recurrent theme coming from Schmidt is that AI will drive advances in basic scientific research and solve problems (for example, in the physics of energy storage) that mere mortals cannot.

GOOGLE Billionaire Predicts AI Will Have 'Unimaginable' Impacts on Society

Another interesting voice on the topic is growth fund manager Cathie Wood, who likewise foresees very elevated rates of productivity growth on the horizon, far beyond historical experience. She has stated that stocks linked to these technology trends have the potential to appreciate in value at a rate of 40% per year within the next decade.


Wood’s extremely optimistic projections for tech stocks are reminiscent of Michael Saylor’s bold claims that Bitcoin will reach or even exceed $13 million (from current levels around $60,000) by 2045, which we examined here.


Wood, like Saylor, who personally has billions of dollars of Bitcoin exposure, is no doubt “talking her own book.” As a fund manager who earns fees by getting people to invest in early-stage growth stocks, she stands to benefit personally from the perception that early-stage growth stocks will skyrocket.


Everyone should therefore take Cathie Woods’ predictions with a grain of salt. But the mere fact that someone’s viewpoint aligns with his or her financial self-interest does not make the viewpoint false.


The more extreme presentations of blue sky scenarios are at a minimum interesting in that they provide a full-fledged explanation of all the “pros” of a certain investment. Like listening to a lawyer speak in defense of a client, we can then critically analyze all the arguments and try to figure out the truth.


Extremely bullish forecasts like those of Saylor and Wood also do not have to be precisely correct. The real issue is whether or not they are directionally correct. If Bitcoin were to compound at 10% or 15% per year for the next 20 years, rather than 30%, an investment today would be more than justified.


Cognitive mistakes


While financial self-interest is a form of bias, there are also a number of cognitive biases, as described by behavioral economists, that prevent people from accepting scenarios that imply dramatic change. These include recency bias, which refers to the tendency of human beings to think that patterns or events that occurred more recently are more likely to repeat in the future.


The idea of a major unprecedented step-up in productivity growth (not to mention fundamentally transformative changes in how civilization operates) naturally seems “crazy” because it requires us to accept the idea that we are about to experience radical change.


The human mind has a tendency to assume the status quo until proven otherwise (“status quo bias” is also a recognized cognitive bias). This is perhaps a helpful default tendency in that it prevents us from falling prey to every exaggerated or apocalyptic claim that may come our way.


Every now and then, however, the status quo does break.


Hedge fund manager John Paulson became a multi-billionaire because he predicted such a break. Paulson made billions betting against subprime mortgages through various levered instruments.


These investments were, in retrospect, wildly mispriced because they heavily discounted the possibility of what was at the time seen as an extreme outcome. This created an opportunity for Paulson and others to earn outsized returns, like winning a bet at the track on a horse with 50:1 odds.


(John Paulson is incidentally in the mix to be named Treasury Secretary if Trump wins in November and, along with Elon Musk, was by Trump’s side at the recent rally in Butler, Pennsylvania. He has also been a very large investor in gold and gold-mining stocks. With gold having compounded at 12% annualized over the past 5 years, this trade is starting to look pretty smart as well.)


In the 2008 time frame, we witnessed firsthand how many investors downplayed credit risks within the banking system despite many smart, well-informed people pointing out that the sky would soon be falling.


The alarmists may have seemed crazy and extreme at the time, but they were right. The sky did indeed fall.


Financial melt-up?


Severe ruptures with the status quo can turn into great investment opportunities because they are not already priced in. The 2008 financial crisis was not captured in asset prices. The ones who saw it coming made a fortune, while most people brushed aside the risk and sustained major losses.


What if asset prices today fail to capture a radical change in circumstances that will instead lead to tremendous upside?


Among the predictions of Vinod Khosla is that the AI-driven productivity improvements coming our way will be deflationary. This is a critical observation, and the potential consequences of this important insight may be counterintuitive.


The reason productivity gains represent a deflationary force is that these gains, by definition, make the production of goods and services less expensive.


Nowhere is the deflationary impact of technology more visible than in consumer electronics. When the first high definition television sets came out around the turn of the century, they cost thousands of dollars and could not be lifted by one person. Today, a much larger flat screen television with far better picture quality can be purchased for a few hundred dollars and lifted with one hand.


Why AI is deflationary


AI has the potential to bring prices down by eliminating workers from the production process. One example we recently heard relates to what is known as “agentic AI", where you simply instruct the computer to accomplish a certain task and it does so more or less independently.


To build a website or e-commerce platform from scratch, for instance, is now a complicated process that requires a substantial amount of coding and integration. It can become quite expensive and involve hundreds of hours of skilled labor. Ultimately, however, it is a computer programming exercise.


What if one could simply ask AI, using plain language, to build an internet platform with a certain set of specifications, similar to how we might ask ChatGPT to write a poem on a specific topic? Within moments, a viable website could perhaps be produced, rendering web developers useless.


In the early stages, AI-generated websites may be clunky and flawed, but as AI continuously improves, such websites could conceivably be better than anything a human is capable of making—and at a fraction of the cost.


The world Vinod Khosla is describing is a world in which there is shrinking demand for human cognitive ability and production costs plunge. This suggests reduced demand for workers. This also suggests some combination of lower final prices to consumers and higher corporate profits.


Deflation is unacceptable


The problem with deflation is that modern economies, built on debt and fiat money systems, cannot handle it. The Federal Reserve has a 2% inflation target (rather than zero, or -2%) because our system requires steady inflationary drift.


Deflation is dangerous in that it discourages spending and investment. Why part with your money today if you can buy more with it tomorrow? As demand drops in the economy, prices fall even further. This is the “deflationary spiral” that economists fear most of all.


Our federal government currently also has some $35 trillion of debt (and growing). In a deflationary scenario, these liabilities become more valuable in real terms. To avoid financial catastrophe, our government needs them to become less valuable.


The U.S. central banking system, organized around the Federal Reserve, is also mandated to maximize employment. When unemployment starts to tick up, easier monetary policy is implemented, as we observed with the recent 50 basis point interest rate hike.


High levels of joblessness are politically unacceptable and can create all kinds of social dangers. In periods of declining employment, fiscal policy becomes more stimulative, in some cases automatically through mechanisms like unemployment insurance. Deficit spending occurs.


We may indeed be on the cusp of massively deflationary productivity increases, which have the potential to translate into broad-based prosperity. But, in our view, it is highly unlikely that these productivity gains will manifest as actual deflation.


Instead, monetary and fiscal policy will likely become highly aggressive to offset these deflationary forces. The productivity gains will therefore manifest as potentially large nominal increases in certain asset prices.


In an actual deflationary scenario, the small percentage of the population that has a lot of money tends to benefit (in the form of stronger purchasing power) while those who do not have much money find it more difficult to earn money.


The vast majority of voters in the United States do not have much wealth and rely on income from either an employer or the government for their survival. According to 2022 Federal Reserve data, the mean net worth of an American household exceeds $1 million, but the median net worth is less than $200,000.


The concentration of wealth in the United States is not necessarily high relative to most other countries, but it is still quite severe. There is unsurprisingly an enormous age component as well, with households under age 35 averaging less than $40,000 in median net worth. Households in the 65-74 year old bracket exceed $400,000 in median net worth.


Our political system is under constant pressure to keep money flowing to the broad population, either through robust labor markets or government transfer payments.


Even wealthy retirees, who may benefit from greater real purchasing power in a deflationary environment, are unlikely to support policies that align with deflation. They may have children and grandchildren whose interests they prioritize. They also are unlikely to favor policies that can lead to social unrest, crime and even political violence, which high rates of unemployment historically produce.


All roads lead to monetary debasement


To offset the deflationary impacts of a potential sustained jump in productivity growth, our government will likely (and probably appropriately) pursue monetary and fiscal policies that halt deflation and redirect money to those who do not have it.


More extreme measures like universal basic income are conceivable, but much of this redistribution could also be accomplished through less direct means, such as expansion of government payrolls or subsidies for higher education. Through a variety of potential fiscal and monetary mechanisms, the real value of dollars can be diluted in order to prevent newfound productivity gains from benefiting only the wealthy.


In a sustained deflation scenario (no government interference), a rational investment strategy may be to hold cash or bonds. Dollars will simply gain in purchasing power. But in a scenario in which deflationary forces are combatted with aggressive monetary and fiscal policy, a different approach is required.


An investor anticipating a tech-driven pick-up in productivity should have two overriding goals: (1) benefit from the trends in innovation; and (2) benefit from the potentially substantial monetary debasement that will need to occur to prevent U.S. dollars from naturally deflating (and to sustain inflation at the Fed’s 2% target).


AI-proof your portfolio


Stocks tend to be more volatile than bonds and tend to carry much greater risk of capital loss, which can be mitigated through diversification. But stocks have the distinct advantage of passing through economy-wide monetary inflation.


We do not have to go far back in time to make the case that stocks benefit from inflationary money creation. Since year-end 2020, cumulative inflation (as measured by the Consumer Price Index) has been approximately 20% as lavish Covid-era fiscal spending and loose monetary policy flooded the economy with U.S. dollars. Over the same time frame, the S&P 500 has risen by approximately 50%.


When more money circulating through the economy leads to generalized inflation, businesses face higher costs. However, businesses are also able to charge higher prices and earn higher profits, and if they have debt on their balance sheets, it depreciates in real terms. When it comes to stocks, monetary debasement tends to get passed through.


As mentioned, cost efficiencies driven by AI can result in either lower prices to customers or higher corporate profits (or some combination). Investors should prioritize stocks that are more likely to retain the benefit of cost efficiencies and generate higher profits.  


The level of competitive intensity within any particular market should determine how much of the efficiency gains would be retained as corporate profits. In the highly competitive consumer electronics industry, for example, most of the cost savings accrued to customers in the form of lower prices.


As a general matter, investors should seek out companies with competitive moats and pricing power. They should also avoid businesses that play in intensely competitive areas. These qualitative attributes are emphasized across our Model Portfolios.


In an environment where AI may produce a windfall of cost savings throughout the economy, focusing on competitively advantaged firms is even more important. Businesses that have barriers to entry and pricing power stand to benefit most. Shareholders of companies that will have to pass the cost savings through to customers (because their competitors are doing so) might see no value creation at all.


When it comes to AI, disruption is the major risk factor investors in stocks should focus on. While many firms will benefit from AI through lower costs, many companies, if not entire industries, could be competitively damaged, if not destroyed, by new business models that are created by AI technology.


We recently highlighted how call centers, which employ some 3 million people in the United States alone, might be first in line for replacement by AI-based customer service systems. A hypothetical business that specializes in call center facilities is arguably an unappealing business to invest in at this moment.


Investors should think carefully about how companies they own might become victims of “creative destruction” from new, low-cost AI technologies. It is possible that some of the most AI-resilient investments will include many low-tech companies that are built around certain physical assets or commodities that will continue to have relevance (and appreciate in value as money is printed).


Gold and crypto


Gold is often described as an inflation hedge, so it may seem counterintuitive that gold would be an attractive asset in the context of a deflationary productivity boom. But gold truly shines as an investment when money is being debased to prevent deflation.


A good way to illustrate how gold performs in this context is to look at the experience of Japanese investors. With an aging population, low levels of family formation and a high savings rate, Japan has struggled with deflationary forces for decades.


To prevent deflation, the Bank of Japan has historically been extremely aggressive. Japan has been a pioneer in quantitative easing and has resorted to negative interest rates and direct purchases of securities by the central bank. Japan’s public debt to GDP now exceeds 250%, a ratio that is approximately twice that of the United States.


Gold has performed quite well in U.S. dollar terms over the past 20 years but even better in Japanese yen terms. In U.S. dollar terms, gold has appreciated approximately 500%, whereas in yen terms, it has appreciated approximately 750%.

One ounce of gold priced in Japanese Yen (20 years)

The long-term performance of gold in yen terms is interesting for two main reasons.


First, it is notable that gold never really suffered a big price decline in yen terms after peaking in U.S. dollar terms in 2011. While the U.S. dollar strengthened materially in the post-2011 time frame, which corresponded with the European sovereign debt crisis, the yen continued to depreciate thanks to the efforts of its central banks.


Second, the exceptional performance of gold in yen terms was in the context of consumer price increases in Japan that generally fluctuated between -1% and 2%, much below U.S. levels. In the U.S., consumer price increases over the 20 year period typically ranged between 0% and 4%, until much more significant rates of increase in the past few years.


The moral of the story, we would argue, is that loose monetary policy, rather than increases in consumer prices, is the primary driver of the gold price. Deflationary forces lead to loose monetary policy, which leads to appreciation of the gold price in terms of the fiat currency being printed by the country battling deflation.


Cryptocurrencies, especially Bitcoin, function like gold as a supply-constrained store of value that in theory should benefit from sustained fiat money creation. Bitcoin does not have the lengthy track record of gold (approximately 15 years versus multiple millennia) but is an asset class that would likely benefit if aggressive monetary policy were used to combat falling consumer prices in the U.S.


The key to Bitcoin is mass adoption and acceptance as a financial instrument. One could argue that Bitcoin adoption, which is already underway, would only be accelerated if developed economies were to engage in aggressive quantitative easing and other monetary debasement strategies to counter deflationary forces.


A productivity boom that becomes a monetary boom strikes us as a scenario that is a clear net positive for cryptocurrencies, which largely exist as an alternative to fiat money systems that are prone to debasement and other risks.


Will the AI productivity boom happen?


The future is inherently unpredictable. As successful as Vinod Khosla and others have been, they don’t have crystal balls. Yet the productivity potential of AI technology is hard to dismiss.


AI is fundamentally about enabling computers to perform the cognitive tasks that drive advanced economies. As AI gets better, which it inevitably will, thanks in part to AI itself, this productivity potential only increases.


Investors who want to be positioned for economy-wide productivity gains should focus on competitively advantaged stocks that will capture the benefit of the potential cost savings in the form of higher profits. They should also avoid stocks that are built around business models that could be badly disrupted by AI-related innovations.


Investors should also consider owning gold and cryptocurrencies as a way of protecting their savings from monetary debasement. Governments around the world will likely be compelled to print money to counteract any AI-driven consumer price deflation and job losses.

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