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@xg_laohao24:
xg_laohao24
Open In TikTok:
Region: US
Sunday 26 July 2026 07:28:51 GMT
755
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3
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No Watermark .mp4 (
11.83MB
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No Watermark(HD) .mp4 (
5.24MB
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Watermark .mp4 (
10.88MB
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Music .mp3
Comments
BP7678 :
I could see if they wr bothering someone!!
2026-07-26 08:52:38
0
Me Z :
I can save her
2026-07-26 17:32:20
0
Buck Brundridge831 :
OKEDOKE
2026-07-26 11:03:58
0
To see more videos from user @xg_laohao24, please go to the Tikwm homepage.
Other Videos
I pointed the crawler at my own prompts instead of the web. There are 195 prompts, and each one is treated as a decision point rather than plain text. Every prompt is evaluated through a structured set of questions: - Is it relevant? - Is it grounded? - Is it ambiguous? - Does it require approval? Each evaluation produces a probability score. The routing logic is intentionally deterministic—it has no opinions of its own. - p ≥ 0.95 → route directly into the execution/code path without invoking an LLM. - p < 0.95 → escalate to Claude Sonnet 5.5, the only model responsible for reasoning. - Anything that appears to require human approval is automatically handed off to me. In one execution: - 168 of 175 prompt decisions were resolved automatically. - 133 terminated within deterministic if branches. - 24 were escalated to Sonnet. - 11 ultimately required human approval. One interesting observation: the token "ask" received an approval-confidence score of 0.544. Since the system lacked sufficient confidence, it deferred the decision instead of hallucinating. The average confidence across the entire run was 0.925. Everyone is crawling the web for additional context. The real context has been sitting inside the prompt all along—it just hasn't been interpreted correctly. #xuhuong #AI
#foryou #trending #kashmir
Nhìn em anh thấy mờ mờ, nhìn gần mới biết em mờ ê mê 🫠
"অন্য কিছু করতে চাইলে মন থেকে ভালোবাসো বন্ধু, মন ভাঙার নিয়ম তো আজকাল ঘরে ঘরে।")
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