I recently noticed that the logic behind AI trading has changed significantly.

It used to be a simple combination of technical analysis and algorithms, but now, the weighting of market psychology and fundamentals has clearly shifted.

Behind this change is the continuous update of AI model training data.
It’s now reflecting not only past patterns but also real-time market sentiment more accurately.
As a result, levels previously considered as bottoming points are no longer necessarily buy signals.

What I find particularly interesting is that AI trading systems are no longer viewing "excessive declines" as simple buying opportunities.
Instead, they are analyzing the "quality" of the decline.
For example, they are beginning to distinguish between declines caused by deteriorating fundamentals and those caused by mere liquidity events.

In fact, these changes have a major impact on bottoming strategies as well.
The old rule of "buy when breaking technical resistance" no longer works as straightforwardly.
To target the bottom, you need to understand what the AI is learning and which factors it is weighting.

Personally, I believe this trend signifies the market’s maturation.
To judge the timing of a bottom, it’s no longer enough to rely solely on technical analysis; you also need to consider macro trends and the intrinsic value of projects.
That’s why, if you’re trying to catch the bottom in today’s market, you need to think more deeply about whether the asset is truly worth buying.