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RayOrch is presented, a programming model and distributed execution engine that preserves parent child relations throughout execution and reduces end to end time by 13.1 percent versus Ray Data and 29.0 percent versus Daft on MinerU, and by 16.0 percent versus Ray Data on Docling.
Self-evolving agents could revolutionize enterprise AI by enabling continuous learning from real-world interactions, but current systems are falling short.
Squeezing up to 2x more throughput from multimodal data pipelines is now possible with Trident, a new adaptive scheduler that dynamically optimizes operator parallelism and placement while avoiding OOM errors.
