Wait, so we should poison AI data to force AI sex toys to only allow edging?
Comment on Tech brands are forcing AI into your gadgets—whether you asked for it or not
blackbelt352@lemmy.world 6 months agoLol why wait, Lovense is already touting AI driven patterns.
Zorsith@lemmy.blahaj.zone 6 months ago
tal@lemmy.today 6 months ago
Filtering out bad data from their training corpus is kinda part of the work that any company doing machine learning is gonna have to deal with, sex toy or no.
tal@lemmy.today 6 months ago
What are they using as input? Like, you can have software that can control a set of outputs learn what output combinations are good at producing an input.
But you gotta have an input, and looking at their products, I don’t see sensors.
I guess they have smartphone integration, and that’s got sensors, so if they can figure out a way to get useful data on what’s arousing somehow from that, that’d work.
googles
techcrunch.com/…/lovense-chatgpt-pleasure-compani…
Hmm.
Okay, so the erotica text generation stuff is legitimately machine learning, but that’s not directly linked to their stuff.
Ditto for LLM-based speech synth, if that’s what they’re doing to generate the voice.
It looks like they’ve got some sort of text classifier to estimate the intensity, how erotic something a given passage in the text is, then they just scale up the intensity of the device their software is controlling based on it.
The bit about trying to quantify emotional content of text isn’t new – sentiment analysis is a thing – but I assume that they’re using some existing system to do that, that they aren’t able themselves to train the system further based on how people react to their specific system.
I’m guessing that this is gluing together existing systems that have used machine learning, rather than themselves doing learning.
blackbelt352@lemmy.world 6 months ago
Lovense is basically just making a line go up and down to raise and lower vibration intensities with AI. They have tons of user generated patterns and probably have some tracking of what people are using through other parts of their app. It’s really not that complicated of an application.