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Let's Know Things

Let's Know Things

By: Colin Wright
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A calm, non-shouty, non-polemical, weekly news analysis podcast for folks of all stripes and leanings who want to know more about what's happening in the world around them. Hosted by analytic journalist Colin Wright since 2016.

letsknowthings.substack.comColin Wright Politics & Government
Episodes
  • Supersonic Flight

    Supersonic Flight
    Nov 4 2025
    This week we talk about Mach 1, the Bell X-1, and the Concorde.We also discuss the X-59, the Tu-144, and Boom Supersonic.Recommended Book: Red Team Blues by Cory DoctorowTranscriptThe term “supersonic,” when applied to speed, refers to something moving faster than the speed of sound—a speed that is shorthanded as Mach 1.The precise Mach 1 speed of sound will be different depending on the nature of the medium through which an object is traveling. So if you’re moving at sea level versus up high in the air, in the stratosphere, the speed of sound will be different. Likewise if you’re moving through moist air versus dry air, or moving through water versus moving through syrup, different speed of sound, different Mach 1.In general, though, to give a basic sense of how fast we’re talking here, if an object is moving at sea level through dry air at a temperature of 20 degrees celsius, which is 68 degrees fahrenheit, Mach 1 is about 768 miles per hour, which is about 1,126 feet per second, and 343.2 meters per second.It’s fast! It’s very fast. Again, this is the speed at which sound moves. So if you surpass the speed of sound, if you go supersonic, you will arrive faster than the sound you make while moving.Back in 1947, an experimental American plane called the Bell X-1 broke the sound barrier, surpassed Mach 1, reaching a speed of almost 1,000 miles per hour using a 6,000 pound thrust rocket propulsion system. A later version of the same rocket-powered plane, the Bell X-1A, which was basically the same vehicle, it just had more fuel capacity, allowing the rocket to burn longer, achieved 1,600 miles per hour in 1956.Prior to that, in 1943, British began working on a secret experimental aircraft called the Miles M.52, intending to build a plane capable of traveling 1,000 mph. Interestingly, this project was apparently the result of the British wanting to keep up with a supposed already existing German aircraft capable of achieving that speed, though it’s now believed the intelligence that led the British to believe the Germans had a supersonic-capable plane was the result of a mistranslation—the Germans hit 1,000 km per hour, which is about 621 mph, and still subsonic.Though apparently a success in terms of research and innovation, the Miles M.52 project was cancelled in 1946, due partly to budgetary concerns, and partly because the new government didn’t believe supersonic aircraft were practical, or maybe even feasible.After the existence of this project was revealed to the public, however, criticism for the cancellation mounted, and the design was translated into new, unmanned scale-model experimental versions of the plane which achieved controlled Mach 1.38 supersonic speeds, and both the design and research from this program was shared with the American company, Bell, and all that knowledge informed the development of the aforementioned Bell X-1 supersonic plane.Again, that successful Bell mission was flown in 1947, and in 1961, a Douglas jetliner, a commercial jet, broke the sound barrier during a controlled test dive, and that fed the development of an intended supersonic airliner in the US, though similar research being conducted elsewhere would bear more direct and immediate fruit.In the Soviet Union, a supersonic jetliner called the Tupolev Tu-144 entered service in 1968, and a jetliner co-developed by the British and French, the Concorde, began construction in 1965, and tallied its first flight in March of 1969.The Tu-144 was thus the world’s first commercial supersonic airliner, by a few months, and it also became the first commercial transport to exceed Mach 2, twice the speed of sound, in 1970.The Tu-144 was plagued by reliability issues from the get-go, however, and while performing maneuvers at an air show in Paris in 1973, it disintegrated in midair, which—combined with its high operating costs reduced its long-term market viability, especially internationally. By the mid-1970s, it was primarily operating within the Soviet Union, and after a new variant of the jet crashed in 1978, the Tu-144 program was cancelled in 1983. Existing models continued to be use for niche purposes, like training space program pilots, and for a supersonic research program undertaken by NASA in the late-1990s, but the final Tu-144 flight was in mid-1999, and all surviving aircraft are now on display or in storage.The Concorde has a similar history. Original forecasts for the supersonic airliner market were optimistic, and while the craft seemed to be generally more reliable and less issue-prone than the Tu-144, and it enjoyed a period of fanfare and promotion, as a sort of luxury experience for folks crossing the Atlantic in particular, cutting travel times in half, a major crash in mid-2000, which killed all 109 occupants and four people on the ground, led to the suspension of service until late-2001, and all remaining Concorde aircraft were retired in 2003—about 20 of them are on display ...
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    15 mins
  • Workplace Automation

    Workplace Automation
    Oct 28 2025
    This week we talk about robots, call center workers, and convenience stores.We also discuss investors, chatbots, and job markets.Recommended Book: The Fourth Consort by Edward AshtonTranscriptThough LLM-based generative AI software, like ChatGPT, Gemini, and Claude, are becoming more and more powerful by the month, and offering newfangled functionality seemingly every day, it’s still anything but certain these tools, and the chatbots they power, will take gobs of jobs from human beings.The tale that’s being told by upper-management at a lot of companies makes it seem like this is inevitable, though there would seem to be market incentives for them to both talk and act like this is the case.Companies that make new, splashy investments in AI tech, or which make deals with big AI companies, purporting to further empower their offerings and to “rightsize” their staff as a consequence, tend to see small to moderate bumps in their stock price, and that’s good for the execs and other management in those companies, many of whom own a lot of stock, or have performance incentives related to the price of their stock built into their larger pay package.But often, not always, but quite a lot of the time, the increased effectiveness and efficiencies claimed by these higher-ups after they go on a firing spree and introduce new AI tools, seem to be at least partly, and in some cases mostly attributable to basically just threatening their staff with being fired in a difficult labor market.When Google executives lay off 5 or 10% of their staff on a given team, for instance, and then gently urge those who survived the cull to come to the office more frequently rather than working from home, and tell them that 60 hours a week is the sweet spot for achieving their productivity goals, that will tend to lead to greater outputs—at least for a while. Same as any other industry where blood has been drawn and a threat is made if people don’t live up to a casually stated standard presented by the person drawing that blood.Also worth mentioning here is that many of the people introducing these tools, both into their own companies and into the market as a whole, seem to think most jobs can be done by AI systems, but not theirs. Many executives have outright said that future businesses will have a small number of people managing a bunch of AI bots, and at least a few investors have said that they believe most jobs can be automated, but investing is too specialized and sophisticated, and will likely remain the domain of clever human beings like themselves.All of which gestures at what we’re seeing in labor markets around the globe right now, where demands for new hires are becoming more intense and a whole lot of low-level jobs in particular are disappearing entirely—though in most cases this is not because of AI, or not just, but instead because of automation more broadly; something that AI is contributing to, but something that is also a lot bigger than AI.And that’s what I’d like to talk about today. The rapid-speed deployment, in some industries and countries, at least, of automated systems, of robots, basically, and how this is likely to impact the already ailing labor markets in the places that are seeing the spearpoint of this deployment.—Chatbots are AI tools that are capable of taking input from users and responding with often quite human-sounding text, and increasingly, audio as well.These bots are the bane of some customers who are looking to speak to a human about some unique need or problem, but who are instead forced to run a gauntlet of AI-powered bots. The interaction often happens in the same little chat window through which they’ll eventually, if they say the right magic words, reach a human being capable of actually helping them. And like so many of the AI innovations that have been broadly deployed at this point, this is a solution that’s generally hated by customers, but lauded by the folks who run these companies, because it saves them a lot of money if they can hire fewer human beings to handle support tickets, even if those savings are the result of most people giving up before successfully navigating the AI maze and reaching a human customer support worker.In India right now, the thriving call center industry is seeing early signs of disruption from the same. IT training centers, in particular, are experimenting with using audio-capable AI chatbots instead of human employees, in part because demand is so high, but also, increasingly, because doing so is cheaper than hiring actual human beings to do the same work.One such company, LimeChat, recently said that it plans to cut its employee base by 80% in the near-future, and if that experiment is successful, this could ripple through India’s $283 billion IT sector, which accounts for 7.5% of India’s GDP. Hiring growth in this sector already collapsed in 2024 and 2025, and again, while this shift seems to be pretty good for the ...
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    16 mins
  • Circular Finance

    Circular Finance
    Oct 21 2025
    This week we talk about entanglements, monopolies, and illusory money.We also discuss electrification, LLMs, and data centers.Recommended Book: The Extinction of Experience by Christine RosenTranscriptOne of the big claims about artificial intelligence technologies, including but not limited to LLM-based generative AI tech, like ChatGPT, Claude, and Gemini, is that they will serve as universal amplifiers.Electricity is another universal amplifier, in that electrifying systems allows you to get a lot more from pretty much every single thing you do, while also allowing for the creation of entirely new systems.Cooking things in the kitchen? Much easier with electricity. Producing things on an assembly line? The introduction of electricity allows you to introduce all sorts of robotics, measuring tools, and safety measures that would not have otherwise been available, and all of these things make the entire process safer, cheaper, and a heck of a lot more effective and efficient.The prime argument behind many sky-high AI company valuations, then, is that if these things evolve in the way they could evolve, becoming increasingly capable and versatile and cheap, cooking could become even easier, manufacturing could become still faster, cheaper, and safer, and every other aspect of society and the economy would see similar gains.If you’re the people making AI, if you own these tools, or a share of the income derived from them, that’s a potentially huge pot of money: a big return on your investment. People make fortunes off far more focused, less-impactful companies and technologies all the time, and being able to create the next big thing in not just one space, but every space? Every aspect of everything, potentially? That’s like owning a share of electricity, and making money every time anyone uses electricity for anything.Through that lens, the big boom in both use of and investment in AI technologies maybe shouldn’t be so surprising. This represents a potentially generational sea-change in how everything works, what the economy looks like, maybe even how governments are run, militaries fight, and so on. If you can throw money into the mix, why wouldn’t you? And if that’s the case, the billions upon billions of dollars sloshing around in this corner of the tech world make a lot of sense; it may be curious that there’s not even more money being invested.Belief in that promise is not universal, however.A lot of people see these technologies not as the next electricity, but maybe the next smartphone, or perhaps the next SUV.Smartphones changed a whole lot about society too, but they’re hardly the same groundbreaking, omni-powerful upgrade that electricity represents.SUVs, too, flogged sales for flailing car companies, boosting their revenues at a moment in which they desperately needed to sell more vehicles to survive. But they were just another, more popular model of what already came before. There’s a chance AI will be similar to that: better software than came before, for some people’s use-cases—but not revolutionary, not groundbreaking even on the scale of pocketable phone-computers.What I’d like to talk about today are the peculiar economics that seem to be playing a role in the AI boom, and why many analysts and financial experts are eyeballing these economics warily, worrying about what they maybe represent, and possibly portend.—The term ‘exuberance,’ in the context of markets, refers to an excitement among investors—sometimes professional investors, sometimes casual investors, sometimes both—about a particular company, technology, or financial product type.The surge in interest and investment in cryptoassets during the height of the COVID-19 pandemic, for instance, including offshoot products like NFTs, was seemingly caused by a period of exuberance, sparked by the novelty of the product, the riches a few lucky insiders made off these products, and the desire by many people—pros and consumer-grade investors—to get in on that action, at a moment in which there wasn’t as much to do in the world as usual.Likewise, the gobs of money plowed into early internet companies, and the money thrown at companies laying fiberoptic cable for the presumed boom in internet customers, were, in retrospect, at least partly the consequence of irrational exuberance.In some cases these investors were just too early, as was the case with those cable-laying companies—the majority of them going out of business after blowing through a spectacular amount of money in a short period of time, and not finding enough paying customers to fund all that expansion—in others it was the result of sky-high valuations that were based on little beyond the exuberance of investors who probably should have known better, but who couldn’t get past their fear of missing out on the next big thing.In that latter case, that flow of money into early dotcom startups did fund a few winners that survived the ...
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    16 mins
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