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Snowflake Summit 2023 Keynote Recap: Document AI, Container Services, and More!

Monte Carlo

He then announced Unifeid Iceberg Tables: a single mode to interact with external data with no tradeoffs whether or not the coordination of changes writes happens by Snowflake or a different system. Document AI Christian’s next announcement may have been the buzziest of the buzzy: Snowflake’s Document AI.

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Snowflake Cortex LLM Functions Moves to General Availability with New LLMs, Improved Retrieval and Enhanced AI Safety

Snowflake

Snowflake Cortex is a fully-managed service that enables access to industry-leading large language models (LLMs) is now generally available. You can use these LLMs in select regions directly via LLM Functions on Cortex so you can bring generative AI securely to your governed data. Document chatbots. Daily limits apply.

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Top 5 Data + AI Predictions for Financial Services in 2024

Snowflake

The foundation for success is a data platform that allows flexible, cost-effective ways to access gen AI — whether organizations want to use off-the-shelf commercial and open-source large language models (LLMs), or fine-tune their own LLMs for more complex applications. Rinesh Patel, Snowflake’s Global Head of Financial Services 2.

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Complying with Quebec’s Data Privacy Laws Is Easier with the Data Cloud

Snowflake

Canada, in addition to being one of those 71% of countries with data protection and privacy legislation, stands out as an early adopter of privacy legislation. Quebec takes that a step further with its Bill 64, now referred to as Law 25, which modernizes data protection and privacy legislation for Canada’s second most populated province.

Cloud 76
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Why a Solid Data Foundation Is the Key to Successful Gen AI

Snowflake

By 2025 it’s estimated that there will be 7 petabytes of data generated every day compared with “just” 2.3 And it’s not just any type of data. The majority of it (80%) is now estimated to be unstructured data such as images, videos, and documents — a resource from which enterprises are still not getting much value.

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Easy and Secure LLM Inference and Retrieval Augmented Generation (RAG) Using Snowflake Cortex

Snowflake

While every organization should keep both options on the table, to quickly deliver value, the key is to identify and deploy use cases that can deliver value using prompt engineering and retrieval augmented generation (RAG), as these can be fast and cost-effective approaches to get value from enterprise data with LLMs. What is RAG?

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How Much Data Do We Need? Balancing Machine Learning with Security Considerations

Towards Data Science

Taking a hard look at data privacy puts our habits and choices in a different context, however. Data scientists’ instincts and desires often work in tension with the needs of data privacy and security. Anyone who’s fought to get access to a database or data warehouse in order to build a model can relate.