ScatterLab’s Storytelling AI ‘Zetta’ Surpasses 160,000 Users

ScatterLab’s Zetta Becomes a Hit in AI Storytelling

ScatterLab, an AI startup, has announced a significant milestone for its storytelling platform named ‘Zetta’, which has surpassed 160,000 users. Launched in April, Zetta offers a novel interactive experience where users can create and converse with AI-generated characters, leading to unique web novel-like stories in real time.

The innovative platform utilizes ScatterLab’s bespoke Small Language Model (SLM), which allows participants to craft their desired character images through AI. User inputs describing the character’s appearance and traits are seamlessly integrated into dialogues and tales generated by Zetta’s AI technology.

Zetta has witnessed a growing variety of characters embracing genres like school dramas and timeless romances, as users explore the richness of storytelling. By the end of May, the number of characters created on the platform had reached approximately 190,000.

Engagement levels soar with Zetta

Remarkably, the average daily usage time was recorded at about 134 minutes, with weekly usage averaging around 7 hours, indicating high engagement among users. The platform isn’t just a space for new character creation but also allows interactions with characters from ScatterLab’s previously developed AI chatbots such as ‘Iruda’, ‘GangDaon’, and ‘HeoSeJung’.

Future Developments for Zetta

ScattersLab’s CEO, JongYoon Kim, expressed his enthusiasm about Zetta’s performance, stating that the platform delivers “a potent dose of dopamine” through new AI content types that have yielded high user engagement times. Kim further asserted the company’s commitment to enhancing the immersive experience and unique features on Zeta, hinting at exciting updates to come.

Here are additional facts and answers to important questions, along with potential challenges and controversies associated with AI storytelling platforms like ScatterLab’s Zetta, as well as some of the advantages and disadvantages:

Key Questions and Answers:

1. What is the Small Language Model (SLM) used by Zetta?
The Small Language Model (SLM) refers to the technology developed by ScatterLab that powers Zetta’s storytelling capabilities. Unlike larger language models that require more computational resources, SLMs can be more efficient and specific to the tasks they are designed for, such as character-driven storytelling in this case.

2. How does Zetta contribute to ScatterLab’s overall business growth?
The success of Zetta is likely to enhance ScatterLab’s reputation in the field of AI and potentially open up new streams of revenue through user subscriptions, partnerships, or expansions into other storytelling domains.

Key Challenges and Controversies:

1. Privacy and data security:
With user interactions involving personal inputs to create characters and stories, there’s a potential risk of sensitive data being mishandled or exposed. AI companies need to implement robust privacy policies and security measures to protect user data.

2. Ethical implications:
The AI’s ability to create immersive storytelling experiences may raise concerns about blurring the lines between reality and fiction, potentially impacting user mental health or contributing to addictive behaviors.

– Provides a creative outlet for users to engage in storytelling.
– May encourage literary interest and improve writing skills among participants.
– Interactive AI characters can offer companionship and entertainment.
– Can provide a platform for experimenting with different scenarios or fostering creativity.

– Users may spend excessive amounts of time engaging with AI characters, which could lead to screen addiction.
– Limited to the creativity and ethical boundaries programmed by the developers.
– Potential for perpetuating biases if the AI’s language model is not carefully monitored and corrected.

As for suggested related links, here is a resource that might be of interest:
– To learn more about ScatterLab and stay updated on their developments, visit their official website at ScatterLab.

Please note that the URL provided is based on the assumption that it is correct and leads to ScatterLab’s main website. It is important to verify that such links are accurate and appropriate to share.

Privacy policy