NSFW chat botsAccording to this site, NSFW (not safe for work) chat bots use specialized machine learning algorithms that create artificial human-like conversation. These datasets contain millions of text interactions and help the bots understand language structure, nuances in languages, and contexts. In the language space, we can use models like OpenAI's GPT-3 which are trained with billions of parameters so that they have enough information to both understand and generate responses that look human. They work together to decide what the responses do, how accurate they are and which ones are relevant. Training these models requires gobs of data, often hundreds and gigabytes, to match the complexity that we see in more modern nsfw chat bots.
NSFW chat bots heavily rely on natural language processing (NLP). NLP helps the bots not only understand the text but also provide responses as needed in terms of tone, style or context following a conversation. One actual example of this is SextingMe, which has highly-engineered NSFW chat bots that are so advanced they can have natural conversations with users. These bots are built to react in the milliseconds needed for chat simulations, and simulates real-time interaction which is important for end user attention as well. Efficiency for these bots is often scored based on speed of response (often in the range to milliseconds) and duration interacting, some of which can carry on conversations that last minutes without breaking coherence.
The cost to create and upkeep such chat bots is rather substantial. Companies spend a fairly significant figure per bot (between $100,000 to $1 million depending on the complexity of the bot and scale of deployment); Building GPT-3 is estimated to have cost OpenAI ~$12 million in total: computationally (model training + fine-tuning), and datamoney spent to acquire licensing data. Nevertheless, these costs are also generally reimbursed by the ROI. Tinder is another example where chat bots that use NSFW tend to increase user retention and engagement by 20-30%; this shows how using a NSFW chatbot can be useful for any platform trying to engage more with their user base.
NSFW chat bots also serve as promising tools for bot makers to start conceptualising the significance of user intent and custom set responses. That may mean using sentiment being analysis, where a bot reads the sentiments in the user messages and then modulates your response. This technology usually takes one or more layers of neural networks which output the user input and generates a proper response. Sometimes, these bots are even faster and more accurate than traditional customer service.
There are some additional ethical and legal questions companies must consider as well before deployment of NSFW chat bots. These will include making it easy for users to maintain privacy and security, which is particularly important because the interactions are intimate. The companies are regulated by legislation such as the General Data Protection Regulation (GDPR) in Europe, which oversees data privacy and insists on managing personal information responsibly.
Taking a shadowy part of the Internet and bringing it to life through cutting edge technology, NSFW chat bots are an interesting innovation that position works in user interaction, while also asking important questions on privacy handling. More and more we can see integrations of this technology in websites, likely with nsfw chat bots style platforms.