Also, people can design a specific application environment to reduce the bad effects resulting from the error of the model.
Yandong Zhang
Karma: 7
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.
(1)
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.
(2)
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).
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.
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.
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.
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.
In amzon, the 2097 filtering is more expensive than before. But still available.
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.
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.
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.
[Question] Equilibrium point of the social evolution under the selective pressure of COVID-19?
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.
https://orgmode.org/worg/org-gtd-etc.html
I would like to recommend the emacs’ org mode and some discussion about its relationship with GTD technique.
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.
After the two horrible years, any new thoughts?
Simple calculation suggests the transmission rate contribute much more to the life of loss than the mortality rate. Any measures improve the transmission will cancel the vaccines’ linear contribution to the death rate. The first priority of the vaccine should be prevent transmission, not mortality rate.
For training new graduates from computer science major, I often asked them to develop a simple website to predict the UP/DOWN probability of tomorrow’s SP index (close price), by using any machine learning model. Then, if the website reported a number that was very close 50%, I would say: the website worked well since the SP index was very close to random walk. “What is the meaning of the work!” Most of them would ask angrily. “50% visitors will be impressed by your website. “
I apologize if you feel the story is irrelevant. In my opinion, 50% prediction definitely is meaningful in many cases. It depends on the audience’s background. For example, if your model tell people, the probability of the disappearing of COVID-19 in tomorrow is 50%, we will be more than happy.