AI News

Snowflake’s AI Breakthrough: Introducing New Managed Service Features

Data cloud company Snowflake this week launched Snowflake Cortex, a managed service which it said enables organizations to more easily discover, analyze and build artificial intelligence (AI) applications.

It said the new offering, which was launched at  the firm’s Snowday 2023 event and is currently in private preview, “gives users instant access to a growing set of serverless functions that include industry-leading large language models (LLMs) such as Meta AI’s Llama 2 model, task-specific models, and advanced vector search functionality

“Using these functions, teams can accelerate their analytics and quickly build contextualized LLM-powered apps within minutes. Snowflake has also built three LLM-powered experiences leveraging Snowflake Cortex to enhance user productivity: Document AI (private preview), Snowflake Copilot (private preview), and Universal Search (private preview).”

Document AI helps enterprises use LLMs to “easily extract content like invoice amounts or contractual terms from documents and fine-tune results,” while Copilot “brings generative AI to everyday Snowflake coding tasks with natural language. Users can now ask questions of their data in plain text, write SQL queries against relevant data sets, refine queries and filter down insights.”

Universal Search contains LLM-powered search functionality so that users can “find and start getting value from the most relevant data and apps for their use cases, faster.”

Sridhar Ramaswamy, the company’s senior vice president of AI, said, “Snowflake is helping pioneer the next wave of AI innovation by providing enterprises with the data foundation and cutting-edge AI building blocks they need to create powerful AI and machine learning apps while keeping their data safe and governed.

“With Snowflake Cortex, businesses can now tap into the power of large language models in seconds, build custom LLM-powered apps within minutes, and maintain flexibility and control over their data — while reimagining how all users tap into generative AI to deliver business value.”

Other announcements related to AI included:

  • The launch of new features the company said “make it easier for developers to build machine learning (ML) models and full-stack apps in the Data Cloud. Snowflake is enhancing its Python capabilities through its programming library, called Snowpark, to boost productivity, increase collaboration, and ultimately speed up end-to-end AI and ML workflows.”
  • New ways to eliminate silos and bring AI and app development directly to enterprise data.

“Having a strong data foundation is the key to a successful AI strategy, and Snowflake’s latest innovations ensure that our customers have the ability to leverage data and harness emerging technologies in secure and governed ways,” said Christian Kleinerman, senior vice president of product at Snowflake.

“Snowflake is making it easier for users to put all of their data to work, without data silos or trade-offs, so they can create powerful AI models and apps that transform their industries.”

Also launched at the event was the Powered by Snowflake Funding Program, which intends to invest up to US$100 million toward “the next generation of early-stage startups building Snowflake Native Apps. As part of the program, Amazon Web Services (AWS) will provide up to US$1 million in free Snowflake credits on AWS over four years to startups building the apps.

“A new way to deploy enterprise applications is emerging as companies look to bring their apps and application code closer to their data,” said Stefan Williams, vice president of corporate development and Snowflake Ventures. “With our venture capital partners and AWS, the (program) will accelerate this new era of software development.”

Snowflake’s Toronto engineering hub has led the development of the Snowflake Native App Framework with which startups build their apps.

A detailed explanation of how Snowflake defines private preview, public preview and general availability can be found here.

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