As part of my fellowship at IFP, I’ve been embarking on a longer-term research project that seeks to produce a retrospective of the development and deployment of mRNA vaccines during the COVID pandemic, and extract lessons for the future about accelerating scientific and technological progress. As this effort gets underway, I’ll be posting reflections, thoughts, and other research notes from the project to
The Frontier of Scientific Plausibility
I want to share some related concepts here to help describe this piece of the model of the science and innovation process.
global technological frontier
maps of science, landscape of science
exploratory engineering (by Eric Drexler)
unsolved challenges
futuristic visions (see the Visioneers book) and these examples https://medium.datadriveninvestor.com/futurists-have-never-been-wrong-f1ef4d2674b8
exploring technology system stable domains (states) (by Matt Webb)
goals/challenges (from “Pump” Carpenter to DARPA)
ideal technology (by Pobisk Kuznetsov, Genrih Altshuller and others)
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then we have this frontier of scientific plausibility
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and then we have trajectories of technology development
from tech without science
to technology readiness and the valley of death
then TRTS evolution, logic of tech development
then of course modeling technological progress and the question of predictions (such as described in this article)
the Jeff Funk model of what drives improvement in tech (doesn't cover non-linear complex stuff)
complex interactions (compare https://www.youtube.com/watch?v=cD8vibuQYSs , https://www.youtube.com/watch?v=PikURl7i7ak with https://youtu.be/7UB3SHBaMsw)
progress in tech as solving of contradictions (TRIZ)
Hope this is useful.
Cool! very interesting macro analogy
Great story, great concept. Will be using that in my model of the science and innovation process.