We are using a combination of a small number of people + software + servers and robots.
We are promoting a new era of company management.
I hope to share some of the process in this section.
Every week, we have a meeting called the Executive Officers Meeting, where only the executive officers and chiefs of management are present.
The board members do not participate at all, only the person in charge of the field.
In fact, I have never asked for this meeting to be conducted in this format.
Occasionally, I'll throw out a question about how to change the flow or mindset of the entire company.
There was no set agenda other than that, and they seemed to be talking about what they should talk about at this time.
As the number of people in the company increases and social conditions change rapidly, the methods that worked well in the past suddenly no longer work.
I'm hoping that the teamwork at the field level can quickly clear up such issues, but I'll leave that to their senses.
Later on, when I catch a glimpse of what they talked about at a management meeting where executives also gather, I can feel something.
Just like in a mystery novel, where mystery leads to mystery, there may be a "hidden cause" for seemingly unconnected events (see quote below).
The Brain Learns
This is how the brain learns
Inspector Gregory of Scotland Yard asks, "Is there anything else I should be aware of?
Holmes. - It was one of those strange dog things that happened at night.
Gregory - The dog didn't do anything at night.
Holmes - That's the weird part.
Sherlock reasoned that if the dog had spotted an outsider, it would have barked.
The fact that he didn't actually bark means that the culprit must have been a familiar person, not an outsider. ......
With this deduction, the great detective narrows down his search and then uncovers the identity of the real culprit.
You may be thinking, "What does that have to do with learning?" The point is that learning is also reasoning, just like Holmes is doing.
Learning, in short, is the process of identifying the hidden causes of a phenomenon in order to derive the most plausible model that governs it.
In the real world, however, observations rarely turn out to be true or false, and can only be indeterminate and probabilistic.
This is where the root of the work of Master Bayes and the Marquis de Laplace comes into play.
Bayesian theory teaches how to reason with probability, and what logical formulas must be applied when the data is not complete and probabilistic about whether it is true or false.
I believe that as long as everyone is able to sense the unusual and fluctuating nature of the world, we will be fine.