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The Devin mishap is a reminder of how tricky it often is for the general public to gauge what's currently possible and what isn't for AI. A lot of people, including myself, assumed the claimed performance was legitimate. No doubt many AI startups like Devin are waiting for the rising tide of improving foundational models to make their ideas feasible. I wonder how many are engaging in similar deceptive marketing tactics or will do so in the future.
How many horses were there?
Well over a million in England by 1850. However they were used primarily for agriculture and later transport. Not industry. As such, they played, at most, a supporting role in industrialization. Also, my original question stands, "Why England?", given the Dutch Golden Age had similar conditions.
Also, development of those 3 technologies wasn't limited by available power.
No, but they were limited by technological advancement and production getting cheaper, which by the mid 1800s were very much tied to steam power. They were also limited by the availability of capital for development, capital which would be much harder to come by with less energy to begin with. And of course the steam turbine was developed directly from the steam engine.
All of three technologies you've listed were not ready for broad practical use until well over 150 years after Newcomen's steam engine. By this time, steam power had long since dethroned wind and water as the primary source of energy for industrial production.
https://histecon.fas.harvard.edu/energyhistory/data/Warde_Energy%20Consumption%20England.pdf
By the mid 1800s, steam was producing as much power for England and Wales as all other sources of fixed motive power combined. That's not even mentioning the world changing impact of inventions such as the train and steamship. Now consider a world without this technology. What leads you to believe that a practical ICE, large steam turbine, and/or hydroelectric power would develop even remotely on schedule in a world with no trains, far lower steel production, and half the motive power? The steam engine's impact on early industrialization is often overstated but its impact by 1850 really can't be exaggerated. It was the diffusion and improvement of the steam engine that bridged the economic gap between the first and second industrial revolution.
One popular conception of the Industrial Revolution is that steam engines were invented, and then an increase in available power led to economic growth.
This doesn't make sense, because water power and horses were much more significant than steam power until well after technological development and economic growth became fast.
While it is true that the first industrial revolution was largely propelled by water, wind, and horsepower rather than the steam engine, the steam engine was instrumental in continuing that momentum into the latter half of the 19th century. The Dutch Golden Age is sometimes characterized as a kind of proto-industrial revolution and likely saw the highest productivity in history prior to the 1800s. (The Dutch by this time also ticked most of the boxes you listed as causes of industrialization.) This economic revolution, like early British industrialization, relied on wind and water power (along with peat) but eventually hit a wall. Without the steam engine, once the rivers are dammed, the countryside is dotted with windmills, and the easily accessible biomass is depleted, energy availability becomes a major constraint for further growth.
Had a practical steam engine somehow failed to materialize during early industrialization, the first industrial revolution may very well have gone down in the annals of history as just another lost "golden age" like so many economic economic efflorescences before it. A period of high mechanization like the Dutch Golden Age that generated new technologies and vast wealth for a short period before sputtering out.
I'm skeptical that spelling reform moved the needle much. I'm admittedly not super familiar with the subject but the notion that vast swathes of information were lost due to phonetic spelling seems unlikely to me. Intellectuals could always fallback on Latin as a lingua franca until shortly before industrialization. Striking that entry from your industrialization checklist, the obvious next question becomes "Why Britain?", as many other European states met the other requirements, yet not only failed to industrialize before Britain but even struggled to follow Britain's progression. Industrialization in The Netherlands would not really take off in earnest until nearly a century after the first textile factories opened on the other side of the North Sea.
Interested in any of the roles. I haven't played chess competitively in close to a decade and my USCF elo was in the 1500s at the time of stopping. So long as I'm given a heads up in advance, I'm free almost all day on Wednesdays, Fridays, and Sundays.
This line leaves me wondering about human isolation on our little planet and what maladaptations humanity is stuck with because we lack neighbors to learn from.
Failing to adopt cheap and plentiful nuclear power comes to mind as a potential example.
I largely agree with the sentiment of your post. However, one nitpick:
The world's largest protest-riot ever, when measured by estimated damage to property.
This claim is questionable. The consensus is that the economic cost of the George Floyd Protests was between one and several billion. Perhaps it was the most expensive riot in US history (though when inflation-adjusted the LA riots may give it a run for its money) and the most expensive to be cleanly accounted for economically, but intuitively I would imagine many of the most violent riots in history, such as the partition riots in India and Pakistan, caused more economic damage.
Sam's comments a few months ago would also make sense given this context:
https://www.lesswrong.com/posts/ndzqjR8z8X99TEa4E/?commentId=XNucY4a3wuynPPywb
further progress will not come from making models bigger. “I think we're at the end of the era where it's going to be these, like, giant, giant models,” he told an audience at an event held at MIT late last week. “We'll make them better in other ways.” [...] Altman said there are also physical limits to how many data centers the company can build and how quickly it can build them. [...] At MIT last week, Altman confirmed that his company is not currently developing GPT-5. “An earlier version of the letter claimed OpenAI is training GPT-5 right now,” he said. “We are not, and won't for some time.”
This new rumor about GPT-4's architecture is just that and should be taken with a massive grain of salt...
That said however, it would explain OpenAI's recent comments about difficulty training a model better than GPT-3. IIRC, OA spent a full year unable to substantially improve on GPT-3. Perhaps the scaling laws do not hold? Or they ran out of usable data? And thus this new architecture was deployed as a workaround. If this is true, it supports my suspicion that AI progress is slowing and that a lot of low-hanging fruit has been picked.
Altman said there are also physical limits to how many data centers the company can build and how quickly it can build them.
This seems to insinuate a cool down in scaling compute and Sam previously acknowledged that the data bottleneck was a real roadblock.
Yep, just as developing countries don't bother with landlines, so to will companies, as they overcome inertia and embrace AI, choose to skip older outdated models and jump to the frontier, wherever that may lie. No company embracing LLMs in 2024 is gonna start by trying to first integrate GPT2, then 3, then 4 in an orderly and gradual manner.
Pretty sure that's just an inside joke about Lex being a robot that stems from his somewhat stiff personality and unwillingness to take a strong stance on most topics.
You're likely correct, but I'm not sure that's relevant. For one, Chinchilla wasn't announced until 2022, nearly two years after the release of GPT-3. So the slowdown is still apparent even if we assume OpenAI was nearly done training an undertrained GPT-4 (which I have seen no evidence of).
Moreover, the focus on efficiency itself is evidence of an approaching wall. Taking an example from the 20th century, machines got much more energy efficient after the 70s which is also when energy stopped getting cheaper. Why didn't OpenAI pivot their attention to fine-tuning and efficiency after the release of GPT-2? Because GPT-2 was cheap to train and relied on a tiny fraction of all available data, sidelining their importance. Efficiency is typically a reaction to scarcity.
AFAIK, no information regarding this has been publicly released. If my assumption that Bing's AI is somehow worse than GPT-4 is true, then I suspect some combination of three possible explanations must be true:
- To save on inference costs, Bing's AI uses less compute.
- Bing's AI simply isn't that well trained when it comes to searching the web and thus isn't using the tool as effectively as it could with better training.
- Bing's AI is trained to be sparing with searches to save on search costs.For multi-part questions, Bing seems too conservative when it comes to searching. Willingness to make more queries would probably improve its answers but at a higher cost to Microsoft.
I'm also quite sympathetic to the idea that another AI winter is plausible, mostly based off compute and data limits. One trivial but frequently overlooked data point is that GPT-4 was released nearly three years after GPT-3. In contrast, GPT-3 was released around a year after GPT-2 which in turn was released less than a year after GPT-1. Despite hype around AI being larger than ever, there already has been a progress slowdown relative to 2017-2020.
That said, a big unknown is to what extent specialized hardware dedicated to AI can outperform Moore's Law. Jensen Huang sure thinks it can:
So obviously, computing has advanced tremendously and the way that’s happened, of course, is a complete reinvention of how computers write software, the computer architecture of it, and the computer runs software. Every single layer from the chip to the system to the interconnect to the algorithms, all completely redesigned and so this way of doing full-stack computing as you projected out ten years, there’s no question in my mind, large language models and these very large language models will have an opportunity to improve by another factor of a million. It just it has to be full stack.
That said, the economy is absorbing AI much slower than it is progressing and even if frontier progress halts tomorrow, investment may still be buoyed by the diffusion of the current models. It's hard to argue that current models aren't powerful enough to have economic value and won't get less expensive as time progresses, regardless of how the frontier moves.
Does GPT-4 seem better than Bing's AI (which also uses some form of GPT-4) to anyone else? This is hard to quantify, but I notice Bing misunderstanding complicated prompts or making mistakes in ways GPT-4 seems better at avoiding.
The search requests it makes are sometimes too simple for an in-depth question and because of this, its answers miss the crux of what I'm asking. Am I off base or has anyone else noticed this?
Probably? Though it's hard to say since so little information about the model architecture was given to the public. That said, PaLM is also around around 10x the size as GPT-3 and GPT-4 seems better than it (though this is likely due to GPT-4's training following Chinchilla-or-better scaling laws).
So Bing was using GPT-4 after all. That explains why it felt noticeably more capable than chatGPT. Still, this advance seems like a less revolutionary leap over GPT-3 than GPT-3 was over GPT-2, if Bing's early performance is a decent indicator.
Question for people working in AI Safety: Why are researchers generally dismissive of the notion that a subhuman level AI could pose an existential risk? I see a lot of attention paid to the risks a superintelligence would pose, but what prevents, say, an AI model capable of producing biological weapons from also being an existential threat, particularly if the model is operated by a person with malicious or misguided intentions?
I'm puzzled by this as well. For a moment I thought maybe PaLM used an encoder-decoder architecture, but no it uses next-word prediction just like GPT-3. Not sure what GPT-3 has that PaLM lacks. A model with the parameter count of PaLM and training dateset size of Chinchilla would be a better hypothetical for "Great Palm".
Erik Engheim and Terje Tvedt introduced me another important development in Europe that seems connected to the industrial revolution: The Machine Revolution. While Medieval China invented plenty of industrial machines, including the first water-powered textile spinning wheel, by the high middle ages Western Europe was using more water and wind power per capita than anywhere else in history.
...watermills in 1086 did the work of almost 400,000 people at a time when England had no more than 1.25 million inhabitants. That means doing as much work as almost 30 percent of the English population.
Cultural explanations are often given for this divergence but in recent years, geography has been given greater focus. Western Europe had waterways more naturally suited for the use of water-power than the rest of Eurasia.
While water and wind power had been harnessed for centuries prior, this intensification of capital provided Europe with far more output than what would otherwise have been possible and more opportunities for engineers and mechanics to experiment, tinker with, and improve machinery.
It may be that the earliest seeds of industrial revolution were planted as far back as the middle ages.
Agreed. The printing press, newspapers, and The Republic of Letters certainly expanded the communication bandwidth.
Any eta on when applicants will receive an update?
Does OpenAI releasing davinci_003 and ChatGPT, both derived from GPT-3, mean we should expect considerably more wait time for GPT-4? Feels like it'd be odd if they released updates to GPT-3 just a month or two before releasing GPT-4.
Interesting, how good can they get? Any ELO estimates?
I'm curious how long it'll be until a general model can play Diplomacy at this level. Anyone fine-tuned an LLM like GPT-3 on chess yet? Chess should be simpler for an LLM to learn unless my intuition is misleading?
GPT-3 was announced less than two and a half years ago. I don't think it's reasonable to assume that the market has fully absorbed its capabilities yet.
Hmm, I should rewrite the Falcon 9 sentence to clarify my intent. I meant to express that more affordable rockets were possible in the 90s compared to what existed, rather than that the F9 exactly was possible in the 90s.
They were, some Soviet engine design from the 70s were the best for their niche until the late 2010s.
Given that the Soviet Union collapsed soon after and that no competitive international launch market really began to emerge until the 2000s this isn't surprising. There was no incentive to improve. Moreover, engines are just one component of the rocket launch cost equation.
From NASA:
The technical problems leading to high space launch costs have been identified and cures proposed, but the long delay until the recent reduction in launch costs suggests that cultural and institutional barriers have hindered implementing potential technical improvements.
One study suggested that the record low cost of the Saturn V could be reduced by a factor of 5, to a cost similar to the Falcon Heavy.
The fundamental cause of the past high commercial launch cost seems to be lack of competition. The US launch industry has been a monopoly, the United Launch Alliance (ULA), and its main customer has been the US government, NASA and the military, which need high reliability and had little incentive to exert cost pressure. The ULA lost most of the commercial market to Russia and Arianespace which are also heavily subsidized by their governments
In 2010, NASA compared SpaceX’s cost to develop the Falcon 9 to the cost NASA’s models predicted using the traditional cost-plus-fee method. Using the NASA-AF Cost Model (NAFCOM), NASA estimated that it would have cost NASA $1,383 million to develop these systems using traditional contracting. The estimated SpaceX cost was $443 million, a 68% reduction from the traditional approach.
Until recently, virtually all major players in this space (heh) were monopolies, whether public or private. These organizations had little incentive to improve and were known to be highly inefficient. Why assume the Soviets reached a magical price floor that was impassable prior to the 2010s?
Funny you should say that, the king of France initially wanted condemned criminals to be the first test pilots for that very reason.
Would you consider the space shuttle doomed from the start then? Even without bureaucratic mismanagement, legislative interference, and persistent budget cuts? The market for rocket development in the 80s and 90s seems hardly optimal. You had OTRAG crushed by political pressure, the space shuttle project heavily interfered with, and Buran's development halted by the collapse of the Soviet Union. A global launch market didn't really even emerge until the 2000s.
As a broader point, even if you chalk up the nonexistence of economically competitive partially reusable rockets to Moore's law, that still leaves an apparent gap in the development of more cost-effective expendable systems. Launch prices stagnated from the early 1970s until the 2000s. Surely expendable rockets in the 70s were not already as optimized as possible without 2000s computers.
Are contemporary rocket computer systems necessary for economical reusability? As I understand it, rocket launch costs stagnated for decades due to a lack of price competition stemming from the high initial capital costs involved in developing new rocket designs rather than us hitting a performance ceiling.
Thanks for the response jmh!
One idea might be that it should have been invented then IF the idea that air (gases) were basically just like water (fluids).
I dunno if this is an intuitive jump but it seems unnecessary. Sky lanterns were built without knowledge of the air acting as a fluid. I don't see why the same couldn't be true for the hot air balloon.
But there would also have to be some expected net gain from the effort to make doing the work worthwhile. Is there any reason to think the expect value gained from the invention and availability of the balloon was seen as anything more than a trivial novelty or toy (such as the Chinese seemed to think)?
As I understand it, expectations for the hot air balloon were placed too high rather than too low. In the 1600s, Francesco Lana de Terzi envisioned that a hypothetical airship (which he deemed impossible) could break sieges (ofc airships are not the same as hot air balloons, but at the time there was no distinction). A very valuable use case. After the invention of the hot air balloon, lofty expectations continued for some time. From Wikipedia, "The military applications of balloons were recognized early, with Joseph Montgolfier jokingly suggesting in 1782 that the French could fly an entire army suspended underneath hundreds of paper bags into Gibraltar to seize it from the British. Military leaders and political leaders soon began to see a more practical potential for balloons to be used in warfare; specifically in the role of reconnaissance."
After all, a balloon is not much like a ship which can be steered and the value of higher ground limited to just how far one can see clearly, and with sufficient detail.
This wasn't known prior to the invention of the hot air balloon. Bartolomeu de Gusmão, who allegedly built a prototype of something similar to a hot air balloon in the early 1700s expected it to be steerable like a ship.
The Archimedes example might be an easy case, but I'm wondering if there are not things to look into regarding the motivations for the work on an invention at the time that offer some type of change in the "environment" (social or intellectual/level of knowledge) that point to why no one did something we now think of as obvious.
The scientific and budding industrial revolution motivated a "spirit of invention". The idea of being an inventor by profession took root and led to more people taking a detailed look at the invention space. IMO, this shift in thinking turned the hot air balloon from an invention that some lone inventor with sufficient capital could have invented into a statistical inevitability.
Thanks for the detailed and informative response Breakfast! I think I largely agree with your post.
I find it likely that that the coincidence of the Montgolfier brothers' and Lenormands' demonstrations in France in 1873 was no accident. There was something about that place and that time that motivated them. If I had to guess, it was something cultural: the idea of testing things in the real world, familiarity with hundreds of years of parachute designs, a critical mass of competitive and supportive energy in the nascent aeronautics space, increasing cultural familiarity with connecting physical intuitions with practical engineering to design"magical" machines.
(1783* you mean.) A revolution in thought definitely aided the invention of the hot air balloon. Novel philosophical ideas and the scientific revolution inspired a more discerning examination of the invention space. But let me ask you this, do you believe the hot air balloon could not have been invented prior to these cultural ideas and parachute design knowledge? My intuition says no, especially given that the Montgolfiers' first balloon prototype was just a large sky lantern made of thin wood and taffeta lifted by burning paper.
IMO, the hot air balloon is an invention that had a fair probability of being invented anytime after the invention of the sky lantern but simply failed to materialize until the scientific revolution and aeronautics pushed said probability near 100%.
This is my first post on LessWrong as well as my Substack. Been sitting on this post for a while but finally dug up the courage to publish it today. Any feedback would be greatly appreciated!
Wouldn't the capital saved on fewer car accidents be free to boost consumption and production? Moreover, most of the $800 billion figure does not entail savings from car repairs/replacements but working hours lost to injuries, traffic jams, medical bills, and QALY lost.
For what it's worth, I'm fairly confident self-driving cars will cause a bigger splash than $500 billion. Car accidents in the US alone cost $836 billion. In a world with ubiquitous self-driving cars, not only could this cost be slashed by 80% or more, but reduced parking spots will also allow much more economic activity. Parking spots currently comprise about a third of city land in the US. The total impact could easily be over a trillion for the US alone.
Still not enough to get even close to 20% growth though.
Guzey goes on to give other takes I find puzzling like the following:
If Google makes $5/month from you viewing ads bundled with Google Search but provides you with even just $500/month of value by giving you access to literally all of the information ever published on the internet, then economic statistics only capture 1% of the value Google Search provides.
He already has his conclusion and dismisses arguments that reject it. "Of course the internet has provided massive economic value, any metric which fails to observe this must be wrong." What is the evidence that Google Search provides consumers with $500/month of value? The midcentury appliances revolution alone saved families 20 hours or more of weekly labor. No one argues that the digital revolution hasn't improved technological productivity, economists cite it as the cause of the brief TFP growth efflorescence from the mid-90s to the early 2000s. But Guzey seems to think its impact is far larger and imagines scenarios to support this claim.
I'm skeptical. Guzey seems to be conflating two separate points in the section you've linked:
- TFP is not a reliable indicator for measuring growth from the utilization of technological advancement
- Bloom et al's "Are Ideas Getting Harder to Find?" is wrong to use TFP as a measure of research output
The second point is probably true, but not the question we're seeking to answer. Research output does not automatically translate to growth from technological advancement.
For example, the US TFP did not grow in the decade between 1973 and 1982. In fact, it declined by about 2%. If – as Bloom et al claim – TFP tracks the level of innovation in the economy, we are forced to conclude that the US economy regressed technologically between 1973 and 1982.
Of course such conclusion is absurd.
Is it absurd? I'm not so sure. Between '73 and '82 the oil shock led to skyrocketing energy prices. Guzey acknowledges this economic crisis but goes on to claim that the indicator must be bad since semiconductors got better, crop yields improved, and life expectancy improved. And he's right, for Bloom's paper, this is a major discrepancy. TFP is not a good measure of research output. However, TFP roughly measures an economy's technological capacity given current restraints.
America in '73 was more productive than America in '82 because a key technological input (energy) was significantly cheaper in '73 than it would be for most of the following decade while the technological advancements made during the same period were not enough to offset the balance.
Let's look at the other examples provided:
According to the data provided, France's TFP peaked prior to the Great Recession and has largely stagnated since. This doesn't seem surprising given France's sluggish economic growth since then. French GDP peaked in 2008. Its labor productivity has also barely grown. If one examines the data without holding the bias that tech advancements since 2001 MUST have vastly improved productivity, the results are hardly surprising.
This is harder to explain. According to the data, Italy's TFP effectively peaked in 1979, remained near this peak until just before the Great Recession, and declined since. Italy's GDP peaked around the time of the Great Recession and declined since. Nonetheless, its TFP being higher in 1970 than 2019 is shocking. CEPR argues that Italian manufacturing misallocates resources on a massive scale but I'd hesitate to give any firm opinion. Rising energy costs may also play a role? This is worthy of further research, but as Guzey points out, Italy is not on the technological frontier and is a bit of a basket case.
Japan’s TFP in 1990 was higher (a) than in 2009.
Unsurprising. 2009 was an unusually weak year for TFP in Japan given the Great Recession's effects. Moreover, since the 1990s, Japan has been in its lost decades. Japan's TFP growth looks more healthy and similar to America's compared to France and Italy.
(See Italy)
Skipping Sweden and Switzerland as they are small countries.
The United Kingdom's TFP peaked in 2007, one year before its GDP peaked. Like France, Italy, and Spain, it has yet to recover from the Great Recession.
TFP is NOT a measure of the pure technological frontier. It cannot tell you how much cutting-edge lab research has progressed over time. What it can tell you is how much technological advancement has soaked into the economy. Recessions, market shocks, structural barriers, and other forms of inertia can slow or even regress TFP.
Total Factor Productivity would fit the bill
What "civilizational development", as you refer to it, would you say that The Netherlands lacked during the Dutch Golden Age? What hindered them from industrializing 200 years before England?
IIRC, the aeolipile provided less than 1/100,000th of the torque provided by Watt's steam engine. Practical steam engines are orders of magnitude more complex than Hero's toy steam turbine. It took a century or more of concerted effort on the part of inventors to develop them.
I also have an additional query regarding the stocking frame:
Did Queen Elizabeth I really inhibit the development of the stocking frame? The common narrative is yes. Wikipedia seems to think so, but I stumbled across a post disputing this claim. The same post also makes some pretty bold claims:
By 1750 — the eve of the Industrial Revolution — there were 14,000 frames in England. The stocking frame had by that time become very sophisticated: it had more than 2000 parts and could have as many as 38 needles per inch (15 per centimeter).
Sounds like a remarkably complex and diffused pre-industrial machine.
Why didn’t clockwork technology get applied to other practical purposes for hundreds of years?
Could the stocking frame count? I'm uncertain of its exact inner workings, but it does represent a fairly complex, practical machine invented before the industrial revolution. Seems plausible parts of it were derived from clockwork technology?
Why is hating humanity acceptable?
A good starting point to answer this would be to ask another question, "Is misanthropy more common today than in the past?"
I suspect three factors play a big role:
- Lack of historical weight—Genocide and ethnic hatred only became acknowledged as the evils they are after the horrors of the 20th century. Run-of-the-mill misanthropy has rarely been the driving force behind large-scale atrocities. This makes the taboo it holds much weaker.
- Doomer mindset—The average person today, particularly those in young adulthood, seems to have a more negative outlook on society, progress, and life in general. Frustration over climate change and other manmade disasters may also contribute. Misanthropy can easily manifest from these feelings.
- Isolation—Speaking of society, misanthropy is probably closely correlated with a sense of disconnectedness from society. With civic engagement dropping and loneliness rising, misanthropy may be an outlet to vent frustration.
Anyone else shown DALL-E 2 to others and gotten surprisingly muted responses? I've noticed some people react to seeing its work with a lot less fascination than I'd expect for a technology with the power to revolutionize art. I stumbled on dalle2 subreddit post describing a similar anecdote so maybe there's something to this.
For comparison, according to pg. 11 of The Census of Manufacturers: 1905, the average 16+ male wage-earner made $11.16 per week and the average 16+ woman made $6.17.
Is it true that 19th-century wheelwrights were extremely highly paid?
I'm quite skeptical of the claim that wheelwrights made $90 a week in 1880s.
San Francisco Call, Volume 67, Number 177, 26 May 1890: A job listing offers $3.50 a day for wheelwrights. Another offers $75(!) but I suspect this is for a project rather than a daily (or weekly) wage.
San Francisco Call, Volume 70, Number 36, 6 July 1891: Two job listings offer $3 a day for wheelwrights. Another offers $30 to $35 for a "wheelwright: orchardist" but again I suspect this is commission work rather than a daily wage.
San Francisco Call, Volume 96, Number 135, 13 October 1904: Two wheelwright job listings offer a daily wage of $3 and $3.50 respectively. And from the San Francisco Call, Volume 96, Number 46, 16 July 1904, three additional job listings for wheelwrights all offer compensation between $3 and $3.50 a day.
Whew, I think we've figured it out.
Even working daily with no rest, an average wheelwright in San Fransisco from 1890-1905 probably made no more than $25 weekly. Of course with a rising wave of mechanization, it's possible wheelwright wages were previously higher. After all, from 1890 to 1904, their wages do seem to be declining accounting for inflation. And maybe SF wheelwrights were simply paid less than average. Even still, $90 in 1880 seems unlikely for an average American wheelwright.
TL;DR
Wheelwrights in the 1880s almost certainly made far less than $90 a week. Probably not even $45 a week.
Found an obscure quote by Christiaan Huygens predicting the industrial revolution a century before its inception and predicting the airplane over two hundred years before its invention:
The violent action of the powder is by this discovery restricted to a movement which limits itself as does that of a great weight. And not only can it serve all purposes to which weight is applied, but also in most cases where man or animal power is needed, such as that it could be applied to raise great stones for building, to erect obelisks, to raise water for fountains or to work mills to grind grain .... It can also be used as a very powerful projector of such a nature that it would be possible by this means to construct weapons which would discharge cannon balls, great arrows, and bomb shells .... And, unlike the artillery of today these engines would be easy to transport, because in this discovery lightness is combined with power.
This last characteristic is very important, and by this means permits the discovery of new kinds of vehicles on land and water.
And although it may sound contradictory, it seems not impossible to devise some vehicle to move through the air ....
While ultimately land, water, and air vehicles wouldn't be powered by Huygens's gunpowder engine, it remains a remarkably prescient forecast. It should also give AI researchers and other futurists some hope in their ability to predict the next technological revolution.
Georgists, mandatory parking minimum haters, and housing reform enthusiasts welcome!
Recently I've run across a fascinating economics paper, Housing Constraints and Spatial Misallocation. The paper's thesis contends that restrictive housing regulations depressed American economic growth by an eye-watering 36% between 1964 and 2009.
That's a shockingly high figure but I found the arguments rather compelling. The paper itself now boasts over 500 citations. I've searched for rebuttals but only stumbled across a post by Bryan Caplan identifying a math error within the paper that led to an understatement(!) of the true economic toll.
This paper should be of great interest to anyone curious about housing regulation and zoning reform, Georgism, perhaps even The Great Stagnation of total factor productivity since the 70s. (Or just anyone who likes the idea of making thousands of extra dollars annually.)
If there's interest, I'd like to write a full-length post diving deeper into this paper and examining its wider implications.
Good post George. But I'm surprised by this assertion:
You could imagine a country deciding to ban self-driving, autonomous drones, automated checkouts, and such, resulting in a massive loss to GDP and cost to consumers. But that cost is expressed in... what? restaurant orders? Starbucks lattes? Having to take the bus or, god forbid, bike or scooter? slower and more expensive amazon deliveries? There’s real value somewhere in there, sure, where “real” needs could be met by this increasing automation, but they don’t seem to be its main target.
That's hard for me to fathom. Self-driving cars, autonomous drones, and automated checkouts will have a far greater impact on society and the economy than just GDP stats and slightly lower-cost consumer goods. Mass adoption of self-driving cars alone would make big waves. The option of having cheap transportation anywhere on demand is a major boon for people in poverty. As autonomous vehicles become more commonplace, consider how many parking spaces in America could be replaced with more stores, housing, etc...