[HN Gopher] Math Built the Modern World
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Math Built the Modern World
Author : vwoolf
Score : 12 points
Date : 2024-02-01 18:42 UTC (4 hours ago)
(HTM) web link (worksinprogress.co)
(TXT) w3m dump (worksinprogress.co)
| 082349872349872 wrote:
| Note especially the image "the calculating paradigm":
| https://lh7-us.googleusercontent.com/wG_lVbOftwaPOzjxlhT-6V5...
|
| All magic is supposed to work on this principle: one starts with
| a real-world problem, applies some ("sympathetic")
| correspondences to arrive at a magical representation, and
| manipulates that representation ("pins in the voodoo doll") in
| order to apply it and result in a real-world action.
|
| However, mathematics seems to be the only* subset of magic where
| the (in the case of mathematics: Galois) correspondence back to
| the real world proves effective!
|
| * marketers and politicians may disagree
| roenxi wrote:
| As theories go I like it, but I don't think the headline and
| conclusion are supported by the article. The meat seems to be
| that math was important, but materials science and manufacturing
| technique to achieve greater precision was most critical.
|
| > The pioneers of the Industrial Revolution valorized
| precision...
|
| This phrase to me is the key of the whole thing. They weren't
| excited about what we would recognise today as maths. They wanted
| accurate manufacturing and measurement.
|
| That does naturally dovetail into improved mathematical
| technique, but I think it is incorrect to say that math is the
| driver here. Precision is the driver. That has remained true to
| today by the way (most precise manufacturing? semiconductors).
| Animats wrote:
| > As theories go I like it, but I don't think the headline and
| conclusion are supported by the article.
|
| Right. What the author doesn't really pick up on is how
| engineering developed. Before 1800 or so, science and math were
| not routinely used by people who built stuff. Edison tended to
| deride mathematical theorists, although he hired some.
|
| Early navigation and astronomy required math, but that was
| mostly measurement, not design. The first thing that really
| required math in the engineering was the steam engine. It's
| possible to build a steam engine with no understanding of
| thermodynamics, but it will be a really crappy steam engine.
| Watt's early engines were about 2% efficient. Carnot, in 1824,
| published "Reflections on the Motive Power of Fire", which, for
| the first time, addressed engine design in terms of heat,
| pressure, efficiency, heat transfer, etc. Around the middle of
| the 19th century, Joule and Kelvin finally got a decent
| mathematical theory for heat engines. Engine designs improved
| substantially and efficiencies went up. At last, direct use of
| math in engineering was really paying off.
|
| Early electrical work was trial and error. Sort of. Edison
| publicly derided theorists, but he had some on his payroll.
| When AC came along, more theory was needed. Now calculus was
| required. Westinghouse and Tesla got involved, and generators,
| motors, and transformers started working much better. (I've
| pointed out before that Tesla's real contribution was that he
| figured out how to get AC electric motors started.) Good motors
| require electromagnetic fields in strange shapes, and intuition
| fails for that. You need math.
| 303uru wrote:
| More of the "everything uses maths so everything is maths!"
| trend.
|
| The Industrial Revolution was fueled by more than just
| mathematical advancements; it was equally driven by empirical
| experimentation, practical innovation, and socio-economic
| factors. Innovators like James Watt relied heavily on trial-and-
| error and hands-on experience, not just mathematical models.
| Technological breakthroughs such as the spinning jenny and power
| loom stemmed more from mechanical ingenuity than from direct
| mathematical applications. Moreover, the rise of capitalist
| economies, availability of investment capital, and political
| stability played crucial roles in facilitating industrial growth.
| These elements, combined with a consumer culture, suggest that
| the revolution was as much about socio-economic transformation as
| it was about a mathematical paradigm shift.
|
| Additionally, the revolution cannot be seen solely through the
| lens of mathematics, as it underplays the significance of
| scientific understanding and multidisciplinary collaboration.
| Scientific theories in physics, chemistry, and biology provided
| essential underpinnings for technological advancements. The
| development of efficient steam engines, for example, was closely
| tied to the understanding of thermodynamics. Furthermore, the
| Industrial Revolution was a result of collaboration among
| mathematicians, scientists, and craftsmen, blending theoretical
| concepts with practical applications. The evolution of education,
| encompassing both mathematical and practical skills training,
| also played a pivotal role in preparing the workforce for
| industrial challenges. Thus, the revolution was a multifaceted
| phenomenon, influenced by a blend of practical experience,
| scientific knowledge, and socio-economic developments.
|
| I recently read "Lost in Math" by Sabine Hossenfelder and I'm
| seeing some similarities here. Hossenfelder's book critiques
| modern theoretical physics, particularly its reliance on
| aesthetic criteria such as beauty and simplicity in maths, which
| she argues can lead physicists astray from empirical science. The
| idea that the most elegant or beautiful mathematical equations
| are the best or most accurate representations of the physical
| world has almost become comedy.
| ecshafer wrote:
| I think the issue here is that it neglects how much overlap there
| was between being a Physicist and Mathematician in the
| 1600s-1900. I don't think anyone would say Newton, Gauss, Euler,
| Lagrange, etc. were not mathematicians and physicists. Very often
| Astronomy, Optics, Mathematics, etc. were just part of the same
| fields. Now we have more delineation. And even with mathematics
| and science, you still need trial and error and engineering to
| actually make machines.
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