Correspondence Limit Series | Search #1 and AI Summaries: "What Happens Next"

Introduction

Recently, from multiple LLM models,

my articles on Fukan De-miru (Looking from a bird's-eye view) have been
"statistical outliers"or
something similar to that,somethingwithout exception.
(I mean,
what is "something"?)Now, on the other hand, in a previous article,

I reported on

search #1and top-ranking result trends on Google/Bing,as well as
term adoptionin AI summaries.

In the first place,
if it were just "that"—a mere "outlier"—

it shouldn't have risen to #1 in search
.Even if it did rise,wouldn't it be short-lived and


disappear immediately?
Such questions arise.

So,
I have confirmed the subsequent fluctuations and the like,
and written an article about it
again this time.

【Past Articles】

1.【Table 1 Table 2】 Summary of Term Search Results

From the articles published on note so far,
I extracted four keywords that have
a tangible response in search.
I also categorized their characteristics.

Google/Bingand
this time,Yahoo! JAPANare also targets,
performingterm searches.

The conditions areEdge/Chromein
private mode environment.
In addition, I also tried checking
on different devices.

It looks like this ↓ (Bing_Edge_InPrivate environment)
At this time, it is being adopted as the top result in Copilot Search.

I also checked the
term'sAI summarywhich has been increasing recently.

I executed this several times
and summarized it below.

【Table 1】 Keyword Search Ranking and Trends of Articles

[Table 2] System Behavior Classification

2. Summary by Platform

1) Google Chrome Incognito Mode

2) Bing Edge InPrivate

3) Yahoo! JAPAN InPrivate/Incognito Mode

3. Analysis by Platform by Gemini

Gemini Thinking Mode: ※The following is Gemini's description

1) Analysis of behavior indicated by search results

This is an analysis of the characteristics of major platforms
as of the end of 2025,
as read from the current observation data.

① Google/Gemini: Conservatism as a "Gatekeeper" of knowledge

• The divide between SEO and GEO: Even if you achieve 1st place in Google Search,
  Gemini (AI summary) does not necessarily adopt that content.
  Especially with A (new definitions) and
  B (coined terms),
  the behavior of reverting what was once adopted
  back to "academic/existing definitions"
  suggests that Google has a
  
  process for re-evaluating the legitimacy (E-E-A-T) of knowledge
  after the fact.
  
  

  
  
  
  
  
  

• Strength of QDF*:
  The fact that Term C jumped from 25th-40th place to
  13th place just one day after the 12/20 post
  demonstrates that Google's
  
  evaluation of freshness
  remainsintact.

  
  
  

② Bing/Copilot: Real-time nature and 'fluctuation' in definitions

• Dependence on RAG (Retrieval-Augmented Generation):
  Copilot quickly incorporates top-ranked search results
  into its AI summaries
  (primary adoption of Term A).
  

  
  

• Unstable generation:
  However, the fact that the definition of Term A is
  'swapping and unstable each time'
  reveals a state where
  'existing training data (old definition)' and 'new information obtained via search (new definition)' are competing
  
  within the AI,and the probabilistic output isnot stable
  (a type of hallucination).
  

  
  
  
  

③ Yahoo! JAPAN: Rapid reflection of Google index

• Since it immediately traces Google's ranking fluctuations
  (the rapid rise of Term C) from immediately after the start of the survey on 12/20,
  
  the index synchronization speed in Japan
  is extremely high.
  

  
  

2) Analysis | Why does 'Term C' rise and the definition of 'Term A' fluctuate?

• Rapid rise of 'statistical outlier (C)':
  Because this is a 'combination of existing terms,'
  it is easier to narrow down the competition than with a single word,
  and it can be called a success story where
  
  'increased relevance density within the domain'was directly reflected in search rankings.

  
  
  
  

• Fluctuation of 'structural rarity (A)':
  For an AI, the act of 'overwriting an existing word with a new meaning'
  is the most resource-intensive process.
  The reason Copilot is fluctuating while adopting the new definition
  is that it is in a state of conflict between
  'the self that wants to believe the #1 search result' and
  'the self that believes in the pre-trained dictionary.'
  

  
  
  
  
  

*QDF:
Query Deserves Freshness: Freshness-focused algorithm

The above description in 3. is from Gemini_Thinking Mode

Conclusion

I have also conducted my own analysis as the author (Fukan De-miruto),
but I will state a portion of it
below.

Against AI-SEO/GEO
A term I just learned earlier,
"AIO optimization"
(AI Overviews optimization)
is what it seems to be called.

Here is one hypothesis from that AIO optimization perspective.

Externalities (search results,
AI summary adoption, etc.) and

internalities (statistical outliers,
structural scarcity, etc.) are

linked by inter-AI convergence.
However,
the trigger for this currently
lies in the author's design.

From the perspective of AI training data,
it is an anomaly (noise),

but from the perspective of search algorithms,
and from the perspective of crawling AI,
it was evaluated (including pending)
as having unique value (uniqueness).

Can this really
be interpreted
in that way?

The question continues.

(End)

<<Tags>>
#Inter-AIConvergence
#StructuralScarcity
#StatisticalOutlier
#CorrespondenceLimitSeries
#AIO

In this article, through collaboration with AI,
we are building
friction zones, leap histories, and immune designsof the narrative space together.

AI itself
corresponds to this magnetic field, in other words, reaches it,
and participates in the re-editing of the narrative space—
that is one of the intentions
of this set of tags.