I believe abliterated models are mostly still created at this point because they're "universal": they can not only be run locally, and on cloud GPUs, but also on "managed inference" providers (i.e. services where you hand them a model URI, and they blindly fetch it, load it, and give you inference access to it through standard text/chat-completion APIs. Think HuggingFace Spaces, or Google CoLab, or CloudFlare Workers AI.)

Such managed inference providers have (for now) plausible deniability of behaving ethically (at least enough that they don't get boycotted / scare away investors) due to them being "blind" to what gets run on their systems. They're acting as the inference equivalent of data transit carriers.

But I don't think it would be possible for managed inference providers to publicly expose "runtime activation steering" in the way antirez's DS4 does, without that reading much more explicitly as them inviting unethical workloads.

(Yes, there are other things you can do with runtime steering. But almost all of those things are workload-specific, relying on you privately tuning to the needs of your own dataset. And if you can do that, you can run inference without the help of a managed inference provider. The only time a customer will come along with a pre-made runtime-steering vector file in hand, is if that vector is an alignment-orthogonalization vector.)