We should assume that every model has a backdoor of some kind.

The training process, like any distillation of distributed human-created input, presumes that the input is authentic and independent.

Studies have shown that a shockingly small number of consistently aligned data points in training can create a backdoor in a model.

It's prudent to assume that every model you interact with has a difficult-to-detect backdoor.