Unveiling Insights with Search: How Our Agent Masters GPT Search

At Sno Ai, innovation drives us forward. In our latest venture, we've harnessed the capabilities of using an Ai agent to direct a bot to access the public information of public ChatGPTs from the GPT store. We also developed an agent that doesn't just control a bot—it answers questions from users, either through our website or through our GPT Explorer in the GPT store.

Real-Time Learning and Updates

One of the most exciting features is how our agent learns and updates to control the bot in real-time. To date, there have been a whopping 29,496,994 user interactions, excluding those with OpenAI GPTs. These interactions provide us with real-time updated statistical data that reflect the bot's continuous progress.

Moreover, our agent determines the best categories for these public GPTs based on engagement and utility. Among the insights, we've noticed significant traction in categories such as learning, research, productivity, and playful bots, with learning taking the lead with over 30,037 instances.

Harnessing Collective Intelligence

Delving deeper into user interactions, we find that images, learning, and coding categories command the most significant engagement, with images leading at nearly 8 million conversations. This suggests a high demand for visual content generation and educational material, along with a solid interest in development support through coding GPTs.

In contrast, the user ratings tell a slightly different story, where productivity tools seem to be the most valued, closely followed by learning and finance. This discrepancy between interactions and ratings highlights a valuable insight: the most used tools aren't always the most appreciated ones. It's a vital reminder that user satisfaction doesn't solely hinge on frequency of use.

Furthermore, we've analyzed user interactions by language using LinguAC2 model, revealing that English dominates with over 200,000 interactions, underlining the global preference for English in AI interactions. However, the presence of other languages such as Chinese and Japanese indicates a diverse, multilingual user base engaging with GPTs, signifying the importance of language inclusivity in AI development.

Reflection and Adaptation

Equipped with these analytics, we are in a prime position to refine our offerings. The data suggest a clear directive towards developing GPTs that can further enhance productivity, support learning in engaging ways, and facilitate coding assistance. Additionally, the preference for image-related interactions inspires us to innovate in visual content generation.

In closing, we at Sno Ai are thrilled to share these findings and use them as a beacon to steer future developments. The insights gained are not merely numbers; they are the voices of our users, guiding us towards creating a more intuitive, responsive, and inclusive AI experience.

Stay tuned for more updates as we continue to explore the vast potential of AI and Ai Agents.

Sno Ai Team

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