Founder, The Roots of Progress (rootsofprogress.org)
Posts
Wiki Contributions
Comments
I think you're right about “dark matter,” and precision machining is exactly the first example of it that leapt to mind. E.g., Watt was having a hard time getting his improved steam engine to work reliably, because without a very good fit between the piston and cylinder, steam pressure would be lost. The problem was solved by Wilkinson, who had developed a special technique for boring canons that could be applied to cylinders for engines. This story is told toward the beginning of Simon Winchester's book The Perfectionists (sold in the UK under the title Exactly, I think).
I gave a related example about the non-obvious importance of precision manufacturing in my essay “Why did we wait so long for the threshing machine?”
Another one that comes to mind is chemical synthesis. Think about how much in the chemical and pharmaceutical industries relies on our ability to synthesize chemicals. And yet, this is rarely discussed even in books on the history of technology. Every once in a while I marvel that we can just synthesize molecules. How do we do that? And how did we learn to do that?!
Or, consider the semiconductor industry. To even invent, say, the transistor, we needed the ability to make n-type and p-type silicon. I haven't dug into it yet, but it must have required sophisticated materials processes to perform the appropriate doping of boron and phosphorus, which are present in the silicon in minute quantities.
One more: When I looked into the history of smallpox vaccines, I found that there was a lot of iteration after the initial vaccine to improve safety, storability, and transportability:
Small amounts of vaccine could be stored for a short time on ivory points, between glass plates, on dried threads, or in small vials. But the virus would lose its effectiveness quickly, especially when subject to heat. When King Charles VI of Spain sent a vaccination expedition to the Americas as a philanthropic effort in 1803, the crew took 22 orphan boys: one was vaccinated before they left, and when his pustule formed, a second boy was vaccinated from the first, arm-to-arm; and so on in a human-virus chain that sustained the vaccine during their months-long voyage across the Atlantic.
Degradation, especially from heat, is a general problem affecting organic material. There are two basic solutions: refrigerating (or freezing), and drying. Before refrigeration, or when it was expensive or otherwise impractical, such as in tropical regions during the World Wars, drying was necessary. The challenge is that the simplest way to dry a material is to heat it, and heat is what we’re trying to protect the material from. Further, drying would often cause proteins to coagulate, making it difficult to reconstitute the material.
The solution, developed in the early 1900s, was “freeze drying”. This technique involves rapidly freezing the material, then putting it under a vacuum so the ice “sublimates”: that is, water vapor evaporates directly off the ice without ever melting into water. A secondary drying process (involving mild heat and/or a chemical desiccant) removes the remaining moisture, and the result is dry material that has not been damaged in structure. If properly sealed off from moisture in the air, the material will last for a long time, even when subject to heat, and it can easily be reconstituted by adding water. Freeze-drying was first applied to blood transfusions in the 1930s; Leslie Collier, in 1955, found that it allowed the smallpox vaccine to last several months even at 37° C (98.6° F), which was suitable for tropical climates.
Think about all of the underlying technologies that are required to invent and scale up something like freeze drying. Progress is highly interconnected; it compounds.
Thanks Gale! In a nutshell, what are the most important takeaways from those pieces?
What's a good example of slowing a technology that is likely to be harmful?
Re “It's Time to Build”; I was also a bit surprised to see that here as a separate item, for the same reason. But, I was also surprised to see Schmidt Futures as a separate item—it's a bit hard for me to understand how a single entity can be an idea machine unto itself? Nadia is coming at these things at a very granular level, and I find that interesting in itself.
Eli Dourado:
Exciting geothermal news today!
I’m pleased to advise and help unveil Project Innerspace, a new nonprofit focused on removing the technical obstacles to Geothermal Anywhere by 2030. Check out the site, and follow @innerspace2030.
Hmm, I think it is supposed to tick up by 2. Are you sure you're getting a strong vote in? You have to click and hold for a while until it takes.
A single commissioner would be too constrained I think. It's not just the NRC holding back nuclear: it's also state-level restrictions, the Yucca Mountain problem, environmental review, community opposition, etc.
Kwasi Kwarteng, UK Business & Energy Secretary and MP for Spelthorne:
We need more nuclear! Today I'm launching our £120m Future Nuclear Fund to entice more developers to invest £billions in new power stations. More nuclear developers = greater competition = lower costs. After 30 years of delay, we're cracking on!
https://twitter.com/KwasiKwarteng/status/1524993089861033986
Well, the point of a lot of this is to look at outputs as a function of inputs. That is what Bloom 2020 is looking at. You need some measure of inputs (they basically use R&D spending, deflated by the wage rate) and some measure of output (GDP, transistor density, crop yields, etc.) and then you figure out the quantitative relationship.
If solar panels or genome sequencing don't look like this, that would be very interesting! My guess would be that they do.
Thanks. I generally agree with all these points, but do they change any of the conclusions? These complexities aren't represented in the models because, well, they would make the models more complex, and it's not clear we need them. But if it made a crucial difference, then I'm sure this would get worked into the models. (It's actually not uncommon to see models that break out different variables for each invention or product, it's just that those details don't end up being important for high-level summaries like this.)