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Title
Delivering AI-powered entertainment that captivates users for hours
…o Login Contact Us Try Databricks Customer Stories / Scatter Lab CUSTOMER STORY Delivering AI-powered entertainment that captivates users for hours 3 Months To build a proprietary LLM with Databricks 1.5 Million Users Secured i…
Description
Scatter Lab used Databricks' flexible GPU clusters to build a proprietary Korean-language large language model in three months on a limited budget, powering its AI companion chatbot platform Zeta, which reached 1.5 million users within nine months with over 12 hours of average weekly engagement.
…r a more immersive experience. Built LLMs of various sizes in just three months By leveraging Databricks’ GPU resources and optimized training system, Scatter Lab overcame the challenges of limited budget and resources and was able to build proprietary LLMs of various sizes in just three months. Scatter Lab’s “Zeta has surpassed 1 million user-created characters and current…
Company
Scatter Lab
…rity and Trust Ready to get started? Get a Demo Login Contact Us Try Databricks Customer Stories / Scatter Lab CUSTOMER STORY Delivering AI-powered entertainment that captivates users for ho…
Country
South Korea
…months. Scatter Lab’s “Zeta has surpassed 1 million user-created characters and currently has 1.5 million users in Korea alone. In Japan, the new service has a total of 150,000 users. In particular, users a…
Industry
Media & Entertainment
…multi-language support and fine-tuning with user data. Share this post Details Industry : Media & Entertainment Use Case : Data Science Cloud : AWS Product : Agent Bricks Ready to get started…
Problem
As a startup, Scatter Lab lacked the GPUs, experience and know-how to train large language models, had a budget of less than 1 billion KRW compared with typical LLM training costs, and could not secure the 1,024 A100 GPUs it needed from cloud providers due to increased global demand, while an external LLM API could not meet its conversation-quality, data-security and cost-effectiveness requirements.
…a startup, building their own LLM presented a number of practical constraints. Scatter Lab had a large amount of Korean-language data, but lacked the GPUs, experience and know-how required to train large language models. The budget was also quite limited, at less than 1 billion KRW, compared with the typical cost of training a large language model. Scatter Lab requested a minimum of 1,024 A100 GPUs from multiple cloud service providers to secure GPUs, but was told that they were unable to supply this amount of GPUs due to increased global demand. The company also lacked the experience to address possible obstacles during lan…
…need for a proprietary LLM to ensure research freedom and feature development. In terms of data security, the robust data protection and privacy controls established by their legal team and external counsel could not be met by using an external LLM API. In addition, using the external API for conversational inference was expected t…
Solution
Scatter Lab adopted Databricks, which offered GPU clusters flexibly on an hourly basis with A100 and H100 options, provided LLM training hyperparameters optimized for data size and model scale, and ran a 24/7 monitoring system with automatic recovery, enabling Scatter Lab to build proprietary LLMs of various sizes in just three months.
…abricks To overcome these limitations, Scatter Lab adopted Databricks solution. Databricks offered GPU clusters flexibly, allowing Scatter Lab to reserve and use GPU clusters on an hourly basis, as opposed to the six-month subscription commonly required by other cloud service providers. Databricks also addressed resource scarcity with multiple GPU options, including the A100 and H100, and thousands of dedicated GPU clusters for LLM training. In addition, Databricks has a wealth of LLM training experience and know-how from working with dozens of clients, providing hyperparameters optimized for data size and model scale, and supporting the latest and fastest training scripts. Databricks’ 24/7 response and monitoring system checks training progress in r…
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Business value
Scatter Lab's Zeta platform surpassed 1 million user-created characters and reached 1.5 million users in Korea plus 150,000 in Japan, with users engaging for about 12 hours a week or more.
…to build proprietary LLMs of various sizes in just three months. Scatter Lab’s “Zeta has surpassed 1 million user-created characters and currently has 1.5 million users in Korea alone. In Japan, the new service has a total of 150,000 users. In particular, users are using Zeta for about 12 hours a week or more. Junseong Kim, Strategy Manager at Scatter Lab, said, “The combination of Scatte…
Technology
Agent Bricks
…st Details Industry : Media & Entertainment Use Case : Data Science Cloud : AWS Product : Agent Bricks Ready to get started? Try Databricks for free Learn more about our product Talk…
Headline outcome
…captivates users for hours 3 Months To build a proprietary LLM with Databricks 1.5 Million Users Secured in just nine months after launching 12 Hours Of average weekly engagement on Zeta Scatter Lab, a conversational AI…
Use case type
Conversational assistant
…rs with AI services that have excellent storytelling and conversational skills. The AI chatbot, powered by the proprietary LLM, is able to synthesize various factors, such as the context of conversations, the personality of characters and the us…
AI capabilities
Conversational AI, Large Language Models
…ential to building a high-quality LLM,” Jongyoun Kim, CEO of Scatter Lab, said. Scatter Lab has built their own LLM based on the Databricks solution, enabling them to provide users with AI services that have excellent storytelling and conversational skills. The AI chatbot, powered by the proprietary LLM, is able to synthesize various f…
Deployment model
Cloud
…hare this post Details Industry : Media & Entertainment Use Case : Data Science Cloud : AWS Product : Agent Bricks Ready to get started? Try Databricks for free Learn more…
Deployment options
cloud
…hare this post Details Industry : Media & Entertainment Use Case : Data Science Cloud : AWS Product : Agent Bricks Ready to get started? Try Databricks for free Learn more…
