There are significant differences in core technical parameters between AI sex chat and traditional chatbots: The parameter scale of the AI sex chat model driven by GPT-4 amounts to 1.8 trillion, and the training data volume exceeds 45TB. However, ordinary customer service chatbots (such as Zendesk) are usually based on the BERT model (with 110 million parameters), and the training data volume is only 1-2TB. The 2023 Gartner report shows that the emotion recognition accuracy of AI sex chat reaches 78%, much higher than the 52% of general chatbots, and the response speed is faster (median 1.2 seconds vs. 2.4 seconds). For instance, the AI sex chat function of the platform Replika processes an average of 150 million messages per day, among which conversations related to intimate topics account for 37%, while the bank customer service chatbot only processes approximately 30 million transactional requests (with a sensitive word density of less than 5%).
The commercialization models are significantly different: The paid conversion rate of AI sex chat (15%) is five times that of ordinary chatbots (such as 3% of e-commerce shopping guides), and the average annual consumption of users reaches 145 US dollars (20 US dollars for ordinary chatbot users). The Anima platform has increased its ARPU (average monthly revenue per User) to $16 through dynamic emotion adaptation (such as a 25% increase in the frequency of emotion fluctuation detection), while the ARPU of the educational chatbot CourseBot is only $4. The financial report of Match Group in 2022 shows that the profit margin of its AI sex chat business is as high as 42%, far exceeding the 28% of its traditional dating application. However, the compliance cost of AI sex chat is higher: The European Union fined a certain platform 2 million euros because it failed to filter 12% of the non-compliant content (the content review misjudgment rate of ordinary chatbots is only 2%).
The user behavior data contrast sharply: The average daily interaction time of AI sex chat users is 27 minutes (with a peak period accounting for 43%), and the 7-day retention rate is 48%, while the average daily usage time of medical and health chatbot (such as Ada) users is only 4 minutes, and the retention rate is 19%. According to the data from App Annie in 2023, the frequency at which AI sex chat users trigger sensitive words is 12 times per thousand words, which is seven times that of legal consultation chatbots. For instance, among the users of the AI sex chat on the Japanese platform SimSim, 72% are male (65% are aged 18-34), while the gender distribution of enterprise-level chatbot users is more balanced (54% are male). From a technical perspective, AI sex chat requires additional investment in federated learning (privacy protection costs account for 18% of the budget) and real-time biometric recognition (such as a 72% accuracy in voice emotion analysis), while general chatbots mostly rely on rule engines (development costs are 30% lower).
In industry cases, Replika saw an annual increase of 120% in the number of users due to its AI sex chat function, and the payment rate rose to 12%, while the growth rate of the retail chatbot Tars was only 25%. In 2021, Meta shut down the BlenderBot project, partly because its semantic bias rate (18%) in emotional interaction was much higher than the 9% of AI sex chat. In the future, AI sex chat will rely more on multimodal technologies (such as a 3D virtual image rendering frame rate of 60fps), but ethical controversies (such as 27% of users worrying about data abuse) will still limit its scalability speed, while general-purpose chatbots focus on efficiency optimization (such as reducing costs to $0.5 per thousand requests).