Author Archives: rdmyers75@hotmail.com

How problematic is U.S. national debt?

Here’s a plot from Gemini, not fact checked by me or any other human. Thanks Gemini!

I’ve always thought reporting “debt as % of GDP” is dumb. What really matters is how much interest payments on the debt are relative to the size of our economy. Or, in a more rational, less political environment, that is all that would matter – but in our real world politics matters a lot, and because politics limits our government’s ability to use taxes to pay the debt, debt payments as % of tax revenue also matter.

So…after World War II interest payments on the debt were very high, but this wasn’t a big deal because the economy was growing very quickly. In the 1980s and 1990s, interest payments spiked as interest rates spiked and growth slowed down. Eventually interest rates came down and got us out of that particular pickle. But now, from the plot we can see that current interest payments as a % of GDP are spiking to a similar level to how they did in the 1980s and 1990s. Interest rates are higher than they have been in recent decades, but not crazy high like in the 1980s. The difference really is the size of the debt relative to the economy. We can hope for faster growth to get us out of this one – there is some hope for AI-led productivity gains, but at the same time we have our government shooting itself in the foot by gutting research, development, and education spending, the historical underpinnings of our nation’s growth, while also blowing enormous sums on reckless, illegal wars of aggression with no end in site, and actually reducing taxes on affluent tax payers and corporations. We have inflation and interest rates both seemingly ramping up. So the situation does indeed seem pretty dire. Do I really even have to suggest solutions here? Sure, don’t stand in the way of the AI thing, but also don’t put all our eggs in that basket and do the opposite of all the obviously stoopid policies I just mentioned.

coal and China

Yale Environment 360 explains the situation with coal use in China.

Paradoxically, China is at the same time the biggest installer of renewable energy, the biggest emitter of greenhouse gases, and the biggest user of coal. One explanation for this conundrum is a national concern over energy security: Coal is the only fossil fuel that China is not obliged to import, either through vulnerable pipelines or along sea routes that pass through precarious choke points like the Straits of Hormuz. China has an abundant supply of coal, boasting about 13.3 percent of the world’s recoverable coal reserves, and, importantly, it is the one fossil fuel that Chinese planners know will remain abundantly available, regardless of any tensions in China’s East Asia region or military action in the Middle East, the region that supplies China with nearly half its oil. This means that despite China’s role as a renewable energy superpower, coal has continued to play a leading role in its energy system. 

They talk about a decrease in “energy intensity”, which is energy use per unit of GDP. So the economy is growing, energy demand is growing, and renewables and battery technology are able to keep up with some but not all of that growth. Hydroelectric is a big part of their energy strategy, and that has been affected by drought recently. There are also complicated reasons why their grid is not run as efficiently as it could be.

My main impression is that it all sounds so…rational. Compared to the U.S. government which at the moment appears to be corrupt, immoral, and just bat-shit crazy.

Thermoeconomics in a Time of Monsters

I am always trying to puzzle out how the financial and real economies are related, and how the loss of functioning ecosystems may eventually put the brakes on both – hopefully, in theory, with the financial markets acting as some sort of cushion where prices rise and allow some degree of adjustment that reduces the onset of actual physical shortages and severe hardship. Anyway, I heard an interview with Warwick Powell recently that seemed to cover some of this. Below is the Goodreads description of his most recent book (which I haven’t read).

Thermoeconomics in a Time of Monsters: Rethinking Theory, China and International Geopolitical Economy

In an era when the old world is dying and the new one struggles to be born, Thermoeconomics in a Time of Monsters delivers a groundbreaking reframing of political economy through the unforgiving laws of thermodynamics.

Warwick Powell argues that all social-economic systems are fundamentally energetic and metabolic. Their reproduction, stability and resilience are perpetually threatened by entropy—the natural tendency toward disorder and energetic dispersion. Successful societies survive and thrive through deliberate negentropic energetic renewal, efficiency gains, and institutional arrangements that convert energy surpluses into sustained order.

Building on classical concerns with value, surplus, production and circulation, Powell develops Systemic Exchange Value (SEV) theory. Money, information, supply chains and fictitious capital are reinterpreted as energetic phenomena. The result is a coherent ontology that integrates thermodynamics, endogenous money and information theory.

I often hear the claim that classical economics “ignores” or “doesn’t know about” land, energy, natural resources, or ecosystem services more generally as an input to production. I don’t think this is exactly true, they just choose to assume these factors are negligible compared to labor and capital, and they have some sound evidence that this assumption has been reasonable over the past couple centuries. What could change their minds is if the assumption becomes unreasonable because high prices or outright shortages of food, water, energy, and/or the physical environment’s ability to absorb our wastes becomes a large factor relative to labor and capital. Then maybe that will force a merger between the abstract models of economics and the iron laws of our actual physical universe. But is it possible that incorporating these factors in advance could help us head off the crisis? You might want to try to invent a parachute before you jump off the cliff, not while you’re in freefall.

https://www.goodreads.com/book/show/249361440-thermoeconomics-in-a-time-of-monsters

medieval castles and scalders

Here’s a fun video on the defenses of medieval castles. Basically, they were designed to be very difficult to take militarily.

Sadly, “medieval scalder” is a job that has been made obsolete by modern life, replaced by something like “ballistic missile launch technician”, which itself is soon to be replaced by Terminators. Chris Farley and Macauley Culkin, 1991. RIP Chris Farley. Macauley Culkin is 45.

the future of scientific and engineering modeling

I’ve been using AI to assist me with coding (R, in my case) since shortly after ChatGPT came out. In engineering, we tend to run off-the-shelf models that were of course written in some kind of code. Sometimes these are open access but often they are proprietary. The brutality of market discipline pretty much requires specialized off-the-shelf solutions in industry because customers are not going to be willing to pay for custom coding. The proprietary ones are even often preferred for legal/liability reasons. Anyway, the future of modeling appears to be humans providing a detailed specification to an AI agent which then follows it to do the coding, debug the coding, run the model, process and present the results. The humans have to be able to detect whether the results are BS, of course, at this point in history. One can imagine using a different agent or a more specialized agent to assist the humans in the bullshit-detection stage, that agent getting more independent over time, and so in a cycle. I wonder if we will be using agents to set up, run, and post-process the specialized models, or if things will trend toward just letting the agents write more fundamental code over time. Or maybe the specification will be what future scientists, engineers, and business people focus their efforts on, with translating that into 0s and 1s being basically a commodity done on the fly by AIs. This makes sense to me – the most crystal clear function of AI so far, in my view, is making it easier and easier for humans to communicate with computers in more abstract language, logic, and mathematical symbols.

Anyway, this example used something called Roo Code which included a couple versions of Claude Code along with some other agents, to run a fishery-related model. There is a peer reviewed article, but I also like this blog post and this example of a specification given to the agents.

MEMOP, MOP, and SMOP

These are some more decision-making frameworks I hadn’t heard of, at least by name. I am hopeful that AI can help techniques like this make the transition from gown to town.

Developing Robust Management Pathways for Nutrient Pollution in Watersheds Under Climate Uncertainty

Nutrient management represents an enduring effort toward sustainability. However, long-term management planning faces notable challenges, mainly due to substantial investments required under uncertainty of forthcoming climate. To address these challenges, this paper proposes and tests a Multi-climate-scenario (MCS) Multi-epoch Multi-objective Planning (MEMOP) framework (in combination MCS-MEMOP). This framework divides the long-term planning horizon into multiple epochs, allowing nutrient mitigation measures (e.g., fertilization management, filter strip) to be initiated at any epoch, each with its own water quality and investment constraints. To tackle climate uncertainty, it incorporates principles of Robust Decision-Making. MCS-MEMOP generates solution pathways outlining the timeline and progression of management measures, tested here for a case of a small, agriculture-dominated watershed. Considering a single climate scenario, the MEMOP method was compared with Multi-objective Planning (MOP) and Stepwise MOP (SMOP) for a 25-year nutrient management horizon, using the SWAT model to evaluate the test case water quality effects of solution pathways. Results show that MEMOP’s multi-epoch approach generates a larger and more diverse set of solutions than MOP and SMOP, offering greater flexibility to select optimal trade-offs among objectives. Additionally, MEMOP solutions exhibit superior cost-effectiveness compared to MOP and SMOP solutions. Applied separately to different climate scenarios, the MEMOP results show that changed climate conditions may significantly alter the Pareto front. In contrast, MCS-MEMOP yields robust solutions that can consistently satisfy 72%∼89% of epoch-specific constraints under new climate conditions in the test case, with a cost increase of 12% that reflects the price of addressing climate uncertainty in this case.

March 2026 in Review

In fast-moving current events as I write on April 4, 2026…I have nothing left to say about the stoopid war in Iran and our stooopid war criminal “leaders” who chose this path. I tell my children “stupid” is a bad word that nice people don’t use, and I don’t use it lightly here. I just hope when I am reviewing April 2026 a month from now at least the part where human beings are dying daily from shooting and blowing up is over.

Most frightening and/or depressing story: The idea of the lone psychopath developing a bioweapon in their garage with AI assistance is very scary. I outlined some proposals out there for how to deal with this issue, but none are really completely satisfying. Of course, nuclear proliferation is always a close runner-up.

Most hopeful story: I took my first Waymo rides in the Phoenix area in March, and I observed Waymo being tested in Philadelphia. I would like to live in a society where transportation is oriented around walking, cycling and other very light personal vehicles, and public transportation. But given that the U.S. is unequivocally not headed in that direction, I think autonomous vehicles are going to be a win for safety, mobility, and the environment in most U.S. cities.

Most interesting story, that was not particularly frightening or hopeful, or perhaps was a mixture of both: I finally got around to reading The Singularity is Nearer. Kurzweil is very big on cultured meat, vertical farming, 3D printing, and generally using computer simulation to super-charge scientific and technical progress in many areas. Then there are his weird ideas about nanobots in our brains allowing us to upload our brains to the internet sometime in the 2030s – sounds crazy at first, but I could sit down and name a few things that sounded crazy a decade ago and are now commonplace. I mused about when the robots are coming now that we seemingly have their AI brains ready for transplant. I mused about the seeming paradox that AI is increasing demand for dirty fossil fuel energy and its attendant impacts while also representing some possibility of a longer-term solution to those problems. It seems like slowing down the deployment of AI is not on the table, so the important question becomes how long is “longer-term” – if measured in single digit years, we just may pull through, but if measured in multiple decades, we may be sunk. Anyway, I brainstormed a list of specific areas of research AI may be able to boost: incremental improvement and deployment of today’s solar, wind, battery, electrification, and electric grid technology; fusion power; safer, more cost-effective and scalable fission power; space-based solar technology; cutting edge materials science and energy storage technology; and fundamental research into the mysteries of the universe, which also comes with attendant risks.

more on augmented reality glasses

In China, you can rent them to try out. Students are using them to cheat on tests (surely teachers will catch on to this soon?). They are still expensive and heavy at the moment.

The glasses scan the questions and display answers on the lens. “Any subject that I may fail at,” she said, requesting the use of a pseudonym so she could speak freely. Some schoolmates have rented her glasses to use in exams.

AI-powered smart glasses have become a multibillion-dollar industry. The glasses, priced from $270 to more than $1,000, are generally equipped with cameras and audio features, powered by large language models. Those with screens can display text or images with augmented reality effects…

Researchers at the Hong Kong University of Science and Technology recently connected Rokid glasses with ChatGPT 5.2. A tester wearing the glasses scored in the top five in a class of over 100 students. The research group is also developing systems that help teachers detect AI glasses, Zili Meng, an assistant professor at the university, told Rest of World. 

deflation and oil price shocks

In fast-moving current events as I write on March 22, 2026, the insane, illegal war of aggression started by the US in Iran (okay, maybe started by Israel, but it was the choice of the US and our mad leader to enable it) continues to escalate. We have talk of ground troops. We have talk of intentionally targeting civilian water infrastructure, which is a massive and unambiguous violation of international law not to mention common morality. There has been idle speculation at least about the use of nuclear weapons. I hope there will not have been a nuclear exchange by the time you read this. If the world is going to get past this moment and move on to a path leading back toward eventual normalcy, this has to end and the people who caused it have to be held accountable. And now, back to regularly scheduled programming…

This article suggests that the oil price shock caused by Russia’s invasion of Ukraine in 2022 played a role in snapping Japan out of decades of deflation, and that the current shock caused by the Iran war could do the same for China.

Recently I posted a contrarian analysis suggesting that China’s deflation is not a true recession, but rather evidence of a sudden acceleration in manufacturing productivity. This article presents the more conventional picture:

Since the country’s COVID-19 reopening in late 2022, a manufacturing glut and sluggish consumer demand have led to intense price wars that eroded company profits and slowed wage growth.

Where am I going with all this? I don’t know yet – it is something I am struggling to understand.