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Building a Powerful Multimodal RAG Application with Pixeltable: From Local Dev to Production
In today’s AI landscape, handling multiple types of data – from documents to videos to audio files – has become increasingly crucial. Yet, building applications that can seamlessly process and analyze this diverse data remains challenging. That’s why we’re excited to share our latest sample application that demonstrates how Pixeltable simplifies multimodal RAG (Retrieval Augmented…
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The AI Data Infrastructure Should Be Declarative, Multimodal, and Incremental
Transform how you build AI applications with Pixeltable, an open-source framework that unifies data storage, versioning, and model orchestration under a simple table interface. Instead of wrestling with data pipelines and infrastructure plumbing, you can focus on what matters: building amazing AI applications that leverage your models and algorithms while Pixeltable handles all the undifferentiated…
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Building Multimodal AI Applications with Pixeltable: The Data Infrastructure for the AI Era
Managing multiple data types in AI applications typically requires juggling multiple specialized tools and writing complex integration code. Pixeltable solves this challenge by providing a unified, declarative interface for building multimodal AI applications while automatically handling incremental updates and versioning.
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The Snowflake for AI: How Pixeltable is Revolutionizing Machine Learning Development
Just as Snowflake transformed data warehousing by making it simple and scalable, Pixeltable is revolutionizing AI development with a unified, declarative approach. Here’s how leading teams are using it to build better AI applications faster.
