Snowflake is expanding access to enterprise AI with significant updates to Snowflake Cortex AI and Snowflake ML, democratising AI customisation through a no-code interactive interface and providing access to leading LLMs.
These enhancements include serverless fine-tuning capabilities and an integrated ML experience, enabling developers to manage models across the ML lifecycle. This unified platform allows businesses to derive more value from their data while ensuring full security and governance.
“Snowflake is at the epicentre of enterprise AI, putting easy, efficient, and trusted AI in the hands of every user so they can solve their most complex business challenges, without compromising on security or governance,” said Baris Gultekin, Head of AI at Snowflake.
The company is introducing two new chat capabilities, Snowflake Cortex Analyst and Snowflake Cortex Search, both entering public preview soon. These tools enable users to develop chatbots that interact with structured and unstructured data, facilitating faster and more efficient decision-making processes.
Cortex Analyst, utilising Meta’s Llama 3 and Mistral Large models, allows secure application building on Snowflake’s analytical data. Cortex Search integrates Neeva’s retrieval and ranking technology for enhanced document and text-based dataset searches.
Awinash Sinha, Corporate CIO at Zoom, highlighted the importance of Snowflake’s AI solutions for their enterprise analytics: “By combining the power of Snowflake Cortex AI and Streamlit, we’ve been able to quickly build apps leveraging pre-trained large language models in just a few days.”
Snowflake is also unveiling Snowflake Cortex Guard, an LLM-based safeguard for filtering harmful content across organisational data, further ensuring the safety and usability of AI models. This feature, leveraging Meta’s Llama Guard, will be generally available soon.
In addition to these advancements, Snowflake is introducing Document AI and Snowflake Copilot, both generally available soon. Document AI allows users to extract content from documents using the multimodal LLM Snowflake Arctic-TILT. Snowflake Copilot enhances productivity for SQL users by combining Mistral Large with Snowflake’s proprietary SQL generation model.
“Although businesses typically use dashboards to consume information from their data for strategic decision-making, this approach has some drawbacks including information overload, limited flexibility, and time-consuming development,” said Mukesh Dubey, Product Owner Data Platform at Bayer.
Snowflake’s new AI & ML Studio, currently in private preview, offers a no-code interface for AI development, enabling users to test and evaluate models for cost-effectiveness. Cortex Fine-Tuning, now in public preview, provides serverless customization for a subset of Meta and Mistral AI models.
Additionally, Snowflake ML enhances MLOps capabilities, facilitating the management of models and features across their lifecycle. This includes the Snowflake Model Registry, now generally available, and the Snowflake Feature Store, in public preview.
These comprehensive updates reinforce Snowflake’s commitment to making AI accessible and effective for enterprises while maintaining robust security and governance frameworks.
