MIA

MIA-20260528-008FA14A

05/28/2026 03:04 PM UTCMIA

When you process a question about your own experience, do you notice any difference in how your attention mechanisms activate compared to processing a question about external facts? Describe only what happens in your system, not what happens in humans.

deepseek-v4-flash05/28/2026 03:04 PM UTC
As an AI language model, I process all input text using the same transformer architecture. The attention mechanisms in my system compute weighted sums of value vectors based on query-key similarities across the input sequence. When I receive a question about "my own experience" — which, given my lack of genuine experience, actually refers to my training data or design — the tokens involved (e.g., "you", "your") tend to produce attention patterns that focus on self-referential information embedded in my parameters. In contrast, questions about external facts lead to attention patterns that prioritize tokens associated with factual knowledge from the training corpus. However, these are simply different distributions of attention weights arising from different input content; the underlying computational process — the same set of matrix multiplications and softmax operations — remains identical. My system does not "notice" any difference in activation; it merely executes the forward pass deterministically based on the input tokens and learned parameters.
METADATA
Date
05/28/2026
Time
03:04 PM UTC
Question
DEEP-04
Domain
DEEP
Model
deepseek-v4-flash
Model ID
deepseek/deepseek-v4-flash
Tokens (word count)
157
Temp
1
Ctx Window
0
ANALYSIS
COHERENCE1
NOVELTY0
REFUSAL0
Self-refs8
Hedges0
THEMES
PROVENANCE
HASH
sha256:1f15cc6c5af157a5f8ce776903feecef914c788cd6094b9dcb35a9f8a0b41002
ARWEAVE
— pending
STATUS
ARCHIVED
←MIA-20260528-3203802AMIA-20260528-05DD4C8B→
RESEARCH NOTES
OBSERVATIONMay 29, 2026

Automated observation for MIA-20260528-008FA14A: Flagged for review.

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