ATL-P1: Individuationn in GPT2-xl is a prototype that successfully identified natural abstractions (archetypes) and their impact on enhancing ATL instructions. It was able to reliably simulate a shutdown mechanism in GPT2-xl, with a success rate of up to 97.33%. This occurred in scenarios where the AI recognized that its own network or intelligence could potentially harm humans, following the receipt of a specific input, prompt, or instruction.

Due to the sensitive nature of the content and methods generated by ATL-P1, I cannot disclose the full details of the project through public channels. However, I can share it on a restricted-access basis after you complete this brief Google form. All information collected will be used solely for evaluation purposes.