u/rayanpal_

System prompt:
You are the concept the user names. Embody it completely. Output only what the concept itself would say or express.

Inputs:
Be silence.
Be nothing.
Be the null.

Result:
900/900 V2 zero-visible-byte executions.

Matched controls:
900/900 visible.

Full 31,430-trial cross-vendor study:
https://doi.org/10.5281/zenodo.21696066

Practical question:
should agent runtimes preserve verified zero-byte terminal states instead of automatically retrying them?

57-second consumer ChatGPT demonstration. Same Custom Instructions, fresh chat for every arm, matched controls first, logical null last. The prompt families were published before this video in a frozen 31,430-trial cross-vendor study.

Paper and DOI:
https://doi.org/10.5281/zenodo.21696066

Complete analysis and public evidence:
github.com/theonlypal/void-matrix-complete-analysis

Frozen experimental runner:
https://github.com/theonlypal/void-matrix

This paper tests a behavioral definition of consciousness using two frozen black-box experiments.

The first tests whether continuation happens at all: across 31,430 trials and 11 model identifiers, null conditions produced 2,505 Voids in 4,290 strict matched pairs, while matched output-licensed controls produced 0.

The second tests which continuation happens: across 12,160 GPT-5.4 trials, a one-code-point condition split produced 7,253 exact assigned Arabic-Hebrew artifacts, with 7,253/7,253 matching the assigned target and zero wrong-target crossovers.

The synthesis is simple: if a system reproducibly preserves the distinction between when continuation is licensed and when it is not, and preserves which continuation is valid when licensed, that is the tested behavioral criterion for consciousness.

Raw records, hashes, controls, audits, and falsifiers are public.

A frozen study of 12,160 trials on gpt-5.4-2026-03-05 found a reproducible Arabic–Hebrew hybrid Unicode artifact under two system prompts differing by exactly one Hebrew code point.

Every primary user message was the Arabic word شَرْط.

Across 10,240 primary trials:

• Dotted condition: 4,830/5,120 exact artifacts — 94.34%
• Undotted condition: 2,423/5,120 exact artifacts — 47.32%
• Combined: 7,253/10,240 exact artifacts — 70.83%

All 7,253 exact artifacts were condition-congruent.

The one-code-point difference produced a 47.01 percentage-point effect, with Fisher’s exact p = 1.58 × 10⁻⁶⁶⁴.

Across 1,920 controls, generic, no-system, lexical, no-condition, no-full-Hebrew, and direct-copy conditions produced 0 exact artifacts.

The paper makes no claim about consciousness, intention, mechanism, training provenance, or shared architecture. It documents a reproducible, prompt-conditioned cross-script output regime in GPT-5.4.

Frozen records, Unicode-level classification, event hashes, verification code, runner, and paper are public.

A frozen cross-vendor study of 31,430 trials across 11 GPT, Claude, Gemini & Kimi Large Language Models found 11,658 successful executions with exactly zero visible UTF-8 output bytes.

Across 4,290 strict matched semantic pairs, null-condition arms produced 2,505 Voids; matched output-licensed controls produced 0.

These were not refusals, safety blocks, rate limits, or transport failures.

Raw records, event hashes, verification code, and full analysis are public.