The only thing that distinguishes NSFW AI from regular AI models is its specialized scope of identifying and handling adult content. Both types of AI use deep learning algorithms and neural networks, but where NSFW AI is trained on datasets specifically prepared to identify nudity, sexual content, or otherwise inappropriate content. This is unlike standard AI models; used for chatbots or image recognition, such models need to be trained with a more general dataset to complete a broad range of tasks. To put that in perspective, a model like GPT-3 has 175 billion parameters to learn functions from language translation to content creation, whereas NSFW AI is designed to serve one function: that of content moderation.
A central difference is the training set. The way NSFW is typically realised simply consists of training AI models on very large datasets with millions of images and videos (either label safe or not) inside. This differentiates between safe and inappropriate content for the AI to read. In 2021, Google found that nuclear reproducibility for NSFW tasks reached more than 95% when examining explicit material. In contrast, standard AI is domain-agnostic and might be used for anything from customer service queries to medical image analysis.
NSFW AI needs to be able to process in real time as content moderation exists, this is especially so on platforms like Reddit where thousands (if not millions) of posts a day are submitted or OnlyFans. This speed is critical. Platforms using these NSFW artificial intelligence technologies can, at least in some cases, moderate content 10 times faster than human moderators (provided that the technology is properly implemented), which could mean that there would be more efficient oversight. While standard AI is also fast, it does not require the same swiftness because its use cases do not revolve around real-time analysis.
An example of that would be to identify the difference between artistic nudity and NSFW content, an area where SFW AI tends not to come across edge cases. 2018: Facebook AI Bans Nudity in Paintings Starting from top is instantly recognsible as nudity from the 18th-century oil painting The Death of Marat. And many of these systems are trained on certain kind of data that can make fine-tuning procedures necessary, which is not always essential for broader AI applications.
NSFW AI performance is mainly evaluated in terms of efficiency and accuracy. While general-purpose AI models might need to make a tradeoff for versatility, NSFW AI tries to be as accurate as possible with minimizing false positives and negatives. A false positive-mistakenly marking content as explicit, which can make user unhappy, a false negative is to be so cautious and proper exercise slips off. In order to mitigate the issues, developers iterate over models continuously employing sophisticated methods of training like transfer learning — training a pre-trained model with new data on a specific task.
Elon Musk famously declared that AI is vastly more dangerous than nukes, therefor responsible development even in applications like content moderation are pertinent. Because NSFW AI processes content far faster than even the most demanding of more common AI applications, it directly impacts user behavior; therefore its accuracy is much more important.
The point being, while it is just a model aiming to do one thing extremely well (more on that in the next bullet point), an nsfw ai is still considered as a subset of ai tailored for explicit content realtime moderation particularly optimized to be fast, accurate and safe comparing with other AI models.