Systems | Development | Analytics | API | Testing

The nursing profession is in crisis. According to McKinsey, over 30% of surveyed nurses said they may leave their current patient care jobs in the next year, and for inpatient nurses it’s higher at 45%. Meanwhile, the average professional tenure of nurses dropped from 3.6 years to 2.8 years between 2020 and 2023. These alarming trends have healthcare systems on red alert. Ninety-four percent of surveyed health system senior executives said the nursing shortage is critical.

This blog series covers how to run, train, fine-tune, and deploy large language models securely inside your Snowflake Account with Snowpark Container Services This year there has been a surge of progress in the world of open source large language models (LLMs). This world of free and open source LLMs took yet another major step forward just this week with Meta’s release of Llama v2.

At Snowflake, we’re helping data scientists, data engineers, and application developers build faster and more efficiently in the Data Cloud. That’s why at our annual user conference, Snowflake Summit 2023, we unveiled new features that further extend data programmability in Snowflake for their language of choice, without having to compromise on governance.

The potential of generative AI and large language models (LLMs) for enterprises is massive. We’ve talked about this opportunity before and at Summit 2023, we announced a number of capabilities that come together to help our customers bring generative AI and LLMs directly to their proprietary data, all delivered through a single, secure platform.

The world is undergoing a remarkable transformation fueled by data. Organizations have accumulated silos across their data infrastructure to support various workloads, languages, tools, and formats because of technology limitations. These silos can have major consequences in the form of greater operational burden, security vulnerabilities, increased total cost of ownership, incomplete insights, and reduced agility.

Containers have emerged as the modern approach to package code in any language to ensure portability and consistency across environments, especially for sophisticated AI/ML models and full-stack data-intensive apps. These types of modern data products frequently deal with massive amounts of proprietary data.