To you who still want to win with automated trading. The one thing I can promise is
※ This serialization is written by the seller of “GENSEN-AI” (Product ID: 82348).
From 19,136 kinds of AI, only the currently effective models are automatically selected.
If the market changes, simply reselect. Learn AI in bulk on your PC → filter by the latest market → place only the surviving AIs with one click.
▶ View product pageGogoJungle (Product ID: 82348)In this serialization, I have written about how numbers in the industry are fabricated and the design behind ours. The final installment summarizes what can be promised as the seller and what cannot be promised as a cutoff.
I will start with what cannot be promised. I cannot promise that you will win. Future performance, monthly return, or win rate maintenance—none can be promised. If a seller promises these, that promise itself is a sign of retreat mentioned in earlier articles.
There are four things I can promise.
First. The learning runs actually on your PC. You can verify the process right before your eyes.
Second. The AI’s internals are generated as ONNX files, and you can inspect the structure with Netron. It is not an “AI” whose contents cannot be shown.
Third. The results are not tallied by my image but are mechanically aggregated by your MT5 as the denominator. I’ve removed any room for cosmetic numbers by the seller.
Fourth. When the AI stops being effective, you do not need to wait for my update. Restart learning, filter by the latest market, and reselect. This process can be completed entirely on your end as many times as needed.
In short, what I promise is not performance, buta means to verify and a method to rebuildfor you. It may not be flashy, but without these two, entering the world of automated trading leads to the four patterns described in earlier articles and the beautiful curves of averaging down and martingaling becoming your opponents. Instead, please trade with reasonable tools.
The product page contains all details of the mechanism and price. Make your judgment there. This serialization ends here. Thank you for reading.
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