US cloud-based data company Snowflake has launched its enterprise-grade large language model (LLM) called Arctic. 

According to Snowflake, Arctic is designed specifically for complex business use cases and can reliably retrieve and generate information based on user requests. 

Snowflake has made the LLM design process transparent through disclosing the provenance of training data

Sridhar Ramaswamy, Snowflake’s CEO, described the launch as a “watershed” moment for the company’s AI team. 

“By delivering industry-leading intelligence and efficiency in a truly open way to the AI community, we are furthering the frontiers of what open-source AI can do,” Ramaswamy said. 

“Our research with Arctic will significantly enhance our capability to deliver reliable, efficient AI to our customers,” he stated. 

Alongside Arctic’s launch, Snowflake is releasing coding templates to accompany the LLM, with the intention of making it easier for Snowflake’s customers to deploy Arctic quickly. 

Arctic will be available on Snowflake’s cloud service Cortex and on Amazon Web Services (AWS). 

AWS vice president of compute and networking, David Brown, commented that Snowflake and AWS were aligned in the belief that generative AI could transform customer relationship management. 

“With AWS, Snowflake was able to customise its infrastructure to accelerate time-to-market for training Snowflake Arctic… And with plans to make Snowflake Arctic available on AWS, customers will have greater choice to leverage powerful AI technology to accelerate their transformation,” he said. 

A 2024 survey conducted by research and analysis company GlobalData suggested that around 27% of companies already have a high adoption rate of AI into their workflows. 

GlobalData forecast that generative AI would be the fastest growing segment of the AI market, achieving a global revenue of $33bn by 2030.