Weaviate Podcast Maximilian Werk on Jina AI's Neural Search Framework
May 3, 2022
Maximilian Werk, Engineering Director at Jina AI, dives into the intricacies of Jina's neural search framework. He explores the importance of executors and the DocumentArray for optimizing operations. Listen as he shares insights on fine-tuning workflows and the challenges of labeling for search. They also discuss how multimodal documents can revolutionize data handling and the evolution of Jina into a microservice architecture. Maximilian’s expertise offers a glimpse into the future of search technology, making it a compelling listen for tech enthusiasts.
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Modular Stack With DocumentArray Core
- Jina organizes neural search with modular components: DocumentArray, core (deployment), hub (shared executors).
- DocumentArray standardizes multimodal, network-optimized data for all pipeline stages.
Share Or Privately Package Executors
- Share reusable executors on the Jina Hub to save development time and reuse models like CLIP or custom preprocessors.
- Keep private executors private when they include business-sensitive logic and still benefit from hub packaging.
Executors Wrap Operations Not Replace Them
- Executors wrap DocumentArray operations and abstract network, deployment, and scaling pain away from ML engineers.
- Heavy preprocessing helpers live in DocumentArray while executors focus on orchestration and portability.