A mechanism that discards "contradictory" data points to maintain internal consistency.
#MachineLearning #CognitiveBias #Cybersecurity #RecursiveAI #DigitalPsychology zip configuration or the ethical implications? Deluded_v0.1_default.zip
A recursive loop that prioritizes internal model weights over new sensory input. A mechanism that discards "contradictory" data points to
The v0.1 release focuses on the . We utilize three primary modules: Deluded_v0.1_default.zip
Early testing on the v0.1 "default" set suggests that models with a "Deluded" architecture reach a state of 98% certainty on false premises within fewer than 500 iterations. We observe that once a "machine delusion" is established, traditional fine-tuning is often insufficient to rectify the bias. 5. Conclusion & Future Work
A metric that artificially inflates the model's certainty in its distorted outputs. 4. Preliminary Results