Introducing Snowflake Cortex AI: Build generative AI applications with fully managed LLMs and chat with your data services

Introducing Snowflake Cortex AI: Build generative AI applications with fully managed LLMs and chat with your data services

Generative AI is rapidly becoming integral across various sectors and industries worldwide. As organizations and their products increasingly embrace this technology, Snowflake has also stepped up to join the movement.. Snowflake introduced Cortex AI on November 1, 2023, during their Snow-day 2023 event. Cortex AI is a fully managed service designed to simplify the use of large language models (LLMs) and AI for all users, enabling the creation of generative AI applications and providing advanced functionalities like vector search and LLM-powered experiences such as Snowflake Copilot and Universal Search. In their recent update, on June 4, 2024, Snowflake announced new advancements to Cortex AI at their annual user conference, Snowflake Summit 2024. These updates further enhance the capabilities of Cortex AI, making it easier for enterprises to build AI-powered applications with added security and governance.

I recently attended the event, and the features and functionalities presented were impressive. As a data giant, Snowflake has simplified the integration of LLMs, addressing many of the challenges typically encountered when designing such solutions.

To reduce the occurrence of incorrect responses, known as hallucinations, large language models (LLMs) can be enhanced with private datasets. One of the most effective methods for achieving this without modifying the model itself, such as through fine-tuning, is the Retrieval Augmented Generation (RAG) framework. RAG improves the accuracy of the model’s responses by providing it with a set of relevant documents. These documents act as a source of context that the model can refer to when generating answers, thereby grounding its responses in reliable information. This approach not only enhances the credibility of the output but also ensures that the responses are more aligned with the specific data and requirements of the user’s context.

Using CORTEX AI in Snowflake allows you to efficiently and securely develop a comprehensive RAG application. This means you can build the entire application stack without the need to set up connections, handle technical infrastructure, or be concerned about data security beyond Snowflake's controlled environment. It simplifies the process by keeping everything within Snowflake's secure framework, ensuring your data remains safe and compliant without additional complexities.

Below diagram illustrate simple flow of RAG architecture and how retrieval works.

Image references from Microsoft & Snowflake

From perspective of Snowflake the RAG will work in the same way. Below diagram provides a simple flow of RAG based interaction in Snowflake Cortex AI leveraging generative AI

Source - Snowflake

Snowflake Cortex AI is a service that's fully managed, aimed at making technology accessible to everyone in an organization, regardless of their technical skills. It offers access to top-notch large language models (LLMs), allowing users to effortlessly create and launch AI-driven applications. With Cortex, businesses can integrate AI directly into their controlled data environment, swiftly expanding access and governance policies to include these models.

Snowflake has a wide range of AI enabled services and has built up a mature ecosystem for leveraging generative AI. Below are the services and a quick overview of it.

  • Cortex Analyst : This feature provides users ability to interact with structured or tabular data using natural language, allowing them to find answers faster, self-serve insights and save valuable time. This feature empowers the non-SQL users to quickly fetch the data.
  • Cortex Search: This service provides document or text search and enables us to query business documents which will be semi - structured or unstructured data.
  • Cortex Fine-Tuning: Easily and securely customize large language models (LLMs) to improve accuracy and performance for specific tasks using serverless fine-tuning in Snowflake. These fine-tuned models can then be managed through the Snowflake Model Registry.

Image source - Snowflake

Snowflake customers are strongly impacted by adopting AI and are pleased with the results.

“Snowflake Cortex AI has changed how we extract insights from our data at scale, using the power of advanced LLMs. Our teams can now quickly and securely analyze massive data sets, unlocking strategic insights to better serve our clients. We’ve reduced our processing times by 40x with the power of Snowflake’s new AI features.”  —Jennifer Brussow, Director of Data Science, Terakeet

Please inbox me or DM me for any help or collaboration to implement & designs generative - AI based solutions or integrations. I am reachable at (@email - sujeetkumarsingh.1988@gmail.com)


Note - This blog post has been written based on new releases and demo presented by @Snowflake team in July-2024 event.

#GenerativeAI #Snowflake #CortexAI #AIApplications #LLMs (Large Language Models) #GenerativeAI #MachineLearning #ArtificialIntelligence #DataAnalytics #TechInnovation #DataScience #TechTrends #CloudComputing #EnterpriseAI #OpenAI #Microsoft #Copilot #GoogleAI #Google #NVIDA

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