One major class of these systems includes adult content categorisations from `Not Safe For Work` (NSFW) images, sub domain specific Thumbnail classification that represents a significantly large share among machine learning solutions. As the need for online protection increases, organizations spend fortunes on creating next-gen NSFW AI mechanisms that can identify and screen inappropriate content automatically. Such algorithms use large datasets which can have millions of images describing different explicit content to allow the AI's ability in identifying nudity, violence and other not suitable for general audiences categories. The training of these kind of complex models may cost anywhere b/w $10,000 to even up to $100,000 depending on the scope as well as accuracy required for that application.
Most NSFW AI algorithms are convolutional neural networks (CNNs) that simulate the image-processing capabilities of the human brain. CNNs work by analyzing image pixels layer-by-layer for patterns associated with explicit content. This technique depends on data sets such as ImageNet and open images, both containing billions of tagged pictures that can be used to train nsfw classifiers. These datasets are frequently used by companies like Google and other tech giants to improve content moderation, with AI as the gatekeeper for platforms that have large numbers of users. The technology has been applied crucially on most of the social networks, and even in companies such as Facebook or Twitter have relied on live monitoring tools powered by AI to keep their community rules.
Adding to that, NSFW AI is not limited to images but also video and text. Linguistic patterns are now detectable by NLP algorithms which tell an AI that suggestive or explicit content has been shared. For example, OpenAI's GPT models have been used in a number of extensions and applications with an accuracy over 90% identifying explicit text in a few seconds (content moderation) [25]. Moreover, some giants like Apple and Microsoft are already investing in this area to illustrate the importance for keeping digital marketplaces safe.
Social media is not the only illustration of NSFW AI applications. These tools are now being data via the internet by online retailers and content hosting platforms, even education technology providers to create safe environment for users. These models are constantly being improved, with lower error rates every year resulting in a compound of increased efficiency and reliability. To quote Google CEO Sundar Pichai, “The potential is way overdone on what’s possible,” he said.“And the real risk isn’t that Skynet will come online or something; it’s more like we stay where we are today and stagnate.” The broader industry is pushing to use AI for safer online experiences, as reflected in his statement.
Automating what was once a human intervention that cost billions to moderate is just another feature of safe-for-work AI. In the past, it cost an average of $50k (a month) for manual content moderation at large scale operations and so having a good solution such as NSFW AI will be on your side in order to cut down costs. This helps small startups and large enterprises to keep the platform integrity in an effective manner. The NSFW AI integration is a huge step in digital clean up on the whole.
If you are a person who wants to go deeper on this subject then resources like nsfw ai will ensure that AI based solutions used in content moderation and safety have walked forward.