Comments by "John Luetjen" (@jehl1963) on "Sabine Hossenfelder"
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Excellent discussion of the subject. Thank-you. A couple of points merit mentioning though, to bound the discussion and provide some perspective. 1) Just because scientists newly discover something does not make it new. Only the observation is new. The biologica phenomena (in the case) has probably been going on for millennia. 2) If scientists, doctors and medical professionals, and engineers all do their jobs diligently and professionally, society will work through it. But this does require the relevant members of society to master the discrete and challenging subjects of math, physics, biology, and other "hard sciences". 3) Finally, life has always been, and remains fatal. Stopping death is not achievable. If it is not Bird Flue, it will be COVID, heart attack, inhaling smoke, or maybe a crazy neighbor or jilted lover. The important thing is the quality of life. While focusing on your own quality of life only impacts 1 person, being gracious and contributing to the quality of life of others impacts countless people, and two or three around you doing this will impact you more than you yourself can achieve. What does this have to do with bird flu? Wars, disease, famines, and suffering will always be with us. Don't be alarmed. Focus on doing what you can, and helping those around us.
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Very interesting and well presented. Having been a "Travelling Salesman", and managed inventory in warehouses, I think I'm qualified to provide a real-world response to the idea of using quantum computing to calculate the ideal solution to those problem. Yes, it can and and will do so, "...but at the end of the day..." it's most likely not going to make a world-changing improvement? Why? Because of diminishing returns, and the corollary to the idea of "diminishing returns", which is "other factors".
Diminishing returns: Having planned my daily sales routes using different software packages, I quickly came to the conclusion that it is far simpler -- and just as effective -- to avoid planning bad routes. Mathematically -- if there are N! possible routes for N stops to be made, there are usually just a few "bad" routes. For example always moving from one stop to the furthest available next stop. Don't do that! Once you have eliminated the bad routes, the rest of the routes often have very similar values, and the downside risk of picking any of them is very small. So "at the end of the day", it doesn't matter which you pick since the difference between them may only be a few minutes of travel time. And given that any particular customer visit may have a variance of 10-15 minutes, saving a minute in travel time will not make a difference in the time that you arrive back at the hotel at the end of the day.
This brings me to the "other factors". In a world where optimization yields diminishing returns, other factors can quickly trump the benefits of sophisticated optimization techniques. In the example given above, a talkative customer, or maybe some unexpected news of a potentially big deal (which is why I was visiting customers in the first place!) may cause me to chuck my day's plan in order to spend more time with that customer. In the case of warehousing, you may spend countless hours calculating the ideal locations for parts based on their size, weight, value and projected activity level, only to be faced with stocking the next fad product (Look! Pet rocks! A Mood ring! Slime!!!) which will suddenly cause you to throw the whole scheme out and start again. It is impossible to predict the next fad product, in either the commercial realm, nor in industrial products. There is a world of unknowns out there waiting to jump up at some unpredictable time and ruin your ideal solution. So maybe the best solution is to not get too heavily invested in any solution, and instead focus on avoiding the stupid solutions. This could be summed up by saying "Just don't do anything stupid". There are evolutionary benefits to just not getting yourself fired/killed/eliminated, and living to fight another day.
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