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For years, companies have operated under the prevailing notion that AI is reserved only for the corporate giants — the ones with the resources to make it work for them. But as technology speeds forward, organizations of all sizes are realizing that generative AI isn’t just aspirational; it’s accessible and applicable now.

People often ask me, “Why did you join Snowflake, and why did you choose to work on developer productivity?” I joined Snowflake to learn from world-class engineers and be part of the highly collaborative culture. These have been the secret sauce to Snowflake’s rocket-ship growth. Snowflake was embarking on a remarkable transformation of developer productivity, and I had to jump on the rocket ship as it was taking off!

AI is here to stay. While 2023 brought wonder and 2024 ushered in widespread experimentation, 2025 will mark the year that retailers get serious about AI's real-world applications. But it’s complicated: AI proofs of concept are graduating from the sandbox to production even as major AI innovators face competition from newer upstarts. At this point, the pace of AI evolution is outstripping the news cycle.

Generative AI’s potential to drive innovation, improve efficiency and create competitive advantages is enormous. However, the ability to fully realize the benefits of generative AI hinges on one crucial factor: data strategy. “Data Strategies for AI Leaders,” a report co-written by MIT and Snowflake, underscores how organizations must invest in robust data foundations to succeed in the AI era.

Across all industries, generative AI is driving innovation and transforming how we work. Use cases range from getting immediate insights from unstructured data such as images, documents and videos, to automating routine tasks so you can focus on higher-value work. Gen AI makes this all easy and accessible because anyone in an enterprise can simply interact with data by using natural language.

We are excited to bring DeepSeek-R1 to Snowflake Cortex AI! As described by DeepSeek, this model, trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT), can achieve performance comparable to OpenAI-o1 across math, code and reasoning tasks. Based on DeepSeek’s posted benchmarking, DeepSeek-R1 tops the leaderboard among open source models and rivals the most advanced closed source models globally.

Migrating from a traditional data warehouse to a cloud data platform is often complex, resource-intensive and costly. At Snowflake, we believe every organization should benefit from an easy, enterprise-grade and collaborative cloud AI and data platform — and should be able to make that transition as fast and automatic as possible.

AI is proving that it’s here to stay. While 2023 brought wonder and 2024 saw widespread experimentation, 2025 will be the year that the public sector gets serious about AI's applications. But it’s complicated: AI proofs of concept are graduating from the sandbox to production, just as some of AI’s biggest cheerleaders are turning a bit dour.

With the advent of generative AI and large language models (LLMs), enterprises are racing to unlock as much business value as possible from their data assets, including apps and models. Unfortunately, these data assets are often locked away in silos across multiple cloud service providers and solutions, as well as across different partner, customer and vendor ecosystems.

We are entering a new era for marketing and advertising agencies. From evolving consumer expectations and increasingly stringent privacy regulations to the rise of AI, the landscape is shifting rapidly. To remain competitive, agencies need to reimagine how they operate. The winners will be those that adopt forward-thinking data strategies, build trust with partners and clients, and leverage AI to deliver real-time insights and personalized campaigns.