A closer look at the memory-chip sector

This afternoon, before the U.S. stock market opened on Monday this week, the bulls in the “storage sector” began to pounce madly on the bears. As a storage ETF “DRAM” that was just launched last week, it rose by almost double digits before today’s market opening. $MU, which I was betting on and was very optimistic about, also experienced a considerable return in value. When I saw this, I was as happy as if I had made a right bet, but also as calm as rationality. For me, I would not be surprised no matter how the market closes tomorrow. Judging from the weekly, monthly and even quarterly lines, this stock has considerable room for growth.

I mention this to reflect on my earlier judgment. When the storage sector began a collective and substantial correction last week, many people have actually basically lost their most basic rationality, whether they admit it or not. As soon as I saw the stock price drop and the less rigorous “sell news” (a storage paper published by Google), I instantly felt that their moat was gone, and I didn’t want to do research before making any comments.And so what I saw as a golden buying opportunity was missed…

When I first saw the Google paper, I didn’t have much fear, but my first action was exactly the same as before. I ran to ask AI to make an English research report for me to see, and then I made a decision. So I did it! Hey, what a coincidence! The first report after my research was that Micron Technology had lost its moat. I was really stunned for a long time before I started to regain my composure and continued to investigate again in a different way. As a result, the second English survey report held the opposite view to the first survey report! This suddenly confused me even more, but there were other things to do at hand and I was more inclined to the second research conclusion, so I slowly forgot to continue fact-checking.

Until today, when I finally had time to do some manual research while riding the subway, I unexpectedly discovered that Google’s paper had been published last year, and not long before the report was officially launched, Google’s parent company spent heavily on a lot of storage hardware. To put it more bluntly, that report only gave an extremely optimized optimization plan for the algorithm. It only optimizes the accuracy of stored content and improves efficiency, but it has no substantial impact on the rising storage requirements required for the development of the entire AI. So I went to look at the U.S. stock market, and the storage sector began to rebound sharply during the pre-market period.

This made me think of many things at once:

• For example, when someone started to say that storage is useless during the market decline, I immediately reflected on whether my stock selection logic had been subverted. I found it was useless but could not come up with any firm arguments to refute it, so I gave up. Is this approach worth continuing in the future?

• As I see the truth more clearly, I find that what the AI ​​says is not necessarily correct. This makes me more skeptical, especially towards the AI ​​that almost caused me harm. So maybe how can I put in place the necessary precautions to prevent a similar incident from happening next time?

• When asking AI, are you asking the right question? I think it’s very lacking, so how can we fix this bug in time?

Finally, after asking around for a while, I came back: the self-check list is crucial! Whether I’m asking questions and communicating with AI, or selecting people or institutions I’m about to work with, I actually need to have the most basic standards to strictly regulate some of my “actions.” This kind of self-examination list needs to be listed continuously, because the more detailed you reflect on yourself, the closer you will be to making perfect choices…