Unfortunately, no other possible equilibrium point of the COVID evolution had been observed until now. On the contrary, more COVID variations appeared. I guess, soon or later, people as a whole will learn to use masks, and then better protection gears.
I would like to recommend the emacs’ org mode and some discussion about its relationship with GTD technique.
Even (1),(2) and (3) were proven true in the future, it was not apocalyptic scenario. People only need to wear serious respirators while not at home. It was not a big deal in my opinion.
I understood that there would be strongly against toward serious respirator. A picture of kids wearing scary respirator is kind of unthinkable to me. However, it is the only equilibrium point that I did not see any scientific uncertainties.
Besides the theoretical consideration, in reality, mine workers had used respirators to protect their lung for years.
Herd immunity may not be reachable since we did not know how long the immune effects could last for infected people.
It is not a joke; Also, English is not my mother tongue. However, the above proof is the only proof of the possible ending of COVID-19 since (as I posted in another topic):
“Everybody wearing a respirator could be one of the equilibrium point of the social evolution under the COVID-19, though may be not the only one. Unfortunately, I did not figure other equilibrium point yet. To my best knowledge, nobody gives other end point of the social evolution in a rigors way. ”
If anybody could proposed other equilibrium point of social evolution, I would be more than happy.
The outlook of kids with a respiratory is kind of scary, as shown in HK. I did not see any other issue with this strategy.
Everybody wearing a respirator could be one of the equilibrium point of the social evolution under the COVID-19, though may be not the only one. Unfortunately, I did not figure other equilibrium point yet. To my best knowledge, nobody gives other end point of the social evolution in a rigors way.
In amzon, the 2097 filtering is more expensive than before. But still available.
I bought 3M respirators and filters several months ago. I did not use it since I worked from home and did not go shopping. Those devices are more cheaper than N95 mask.
If a researcher was given 1000X more data, 1000X CPU power, would he switch to a brute-force approach? I did not see the connection between “data and computation power” and the brute-force models.
Such a great article! I thought the AlexNet that led to the recent AI break through could be viewed as a discontinuity too. The background and some statistics result are well summarized in below link.
The graph evolution system are of:
[a] easy to be stated
[b] Turing complete
Conway’s Game of Life also has the above two properties.
From the perspective of mathematical logic, string replacement systems could be as powerful as a full functional computer. The proposed graph evolution systems are of the same power too. The author provided many well explained good features of the system and I was persuaded to try to think some science topics from the viewpoint of “graph evolution”.
If in future the author or others can obtain new physics findings by using this system, then evidentially the new “fundamental ontology” had some advantages.
However, at this moment, I did not find any provable advantages of this system comparing with other string replacement system yet. I would like to view this work as a thoughtful and well explained scientific investigation ----but the value to people is not proved yet.
Ref: The power of string replacement was well explained in the last article of the book: <The essential Turing>
A wrong model could be useful if the action (based on the module) can compensate the models’ error effectively. Usually, you need to know some properties of the model’s error.
Even a wrong model could be very useful. For example, the earth is flat. That wrong model setup the question correctly and so that people could start thinking the shape of the earth.
Below is a simplified COVID-19 framework:
Data acquiring ---> social engineering based on model ----> better result
Yes. A better model will be definitely helpful. However, (as pointed out indirectly earlier by someone else), to my best knowledge, there were no good and robust model for large lag dynamic systems. Such kind of model could lead to Chaos and random like result easily. Thus, I believed that increasing the data acquiring capability was the key (South Korea’s approach).
A lesson from last 30 years AI development: data and computation power are the key factor of improvement.
Thus, IMPHO,,for obtaining a better model, the most reliable approach is to get more data.
Can we reduce the issue of “we can’t efficiently compute that update” by adding sensors?
What if we could get more data ? —— if facing such type of difficulties, I would ask that question first.
Also, people can design a specific application environment to reduce the bad effects resulting from the error of the model.