newsletterJune 19, 2026·Towards Data Science

I Tried to Schedule My ETL Pipeline. Here’s What I Didn’t Expect.

What I thought was a scheduling problem turned out to be a portability problem first The post I Tried to Schedule My ETL Pipeline. Here’s What I Didn’t Expect. appeared first on Towards Data Science.

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•What I thought was a scheduling problem turned out to be a portability problem first The post I Tried to Schedule My ETL Pipeline
•This story was reported by Towards Data Science, covering developments in the newsletter space.
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Python 3.14 and its New JIT Compiler

A technical overview and some benchmarks The post Python 3.14 and its New JIT Compiler appeared first on Towards Data Science.

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Building a Custom GStreamer Plugin for NVIDIA DeepStream

Why Custom Inference in DeepStream? The post Building a Custom GStreamer Plugin for NVIDIA DeepStream appeared first on Towards Data Science.

Towards Data Science

Parse Scanned PDFs for RAG with EasyOCR: Free OCR Gives You Words, Not a Document

Enterprise Document Intelligence [Vol.1 #5quinquies] - Same 1974 scanned PDF, two engines. EasyOCR recovers text. Docling recovers text + sections + figures. The structural gap makes one output usable downstream and the other one a flat string. The post Parse Scanned PDFs for RAG with EasyOCR: Free

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GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step Would Stop Bouncing Off the GPU

The PCIe transfer latency is silently bottlenecking your agentic inference. Here is how building a custom device-resident vector search kernel bypasses the CPU to unlock deterministic microsecond tail latencies. The post GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step

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I Tried to Schedule My ETL Pipeline. Here’s What I Didn’t Expect.

Key Takeaways

Related Articles

Python 3.14 and its New JIT Compiler

Building a Custom GStreamer Plugin for NVIDIA DeepStream

Parse Scanned PDFs for RAG with EasyOCR: Free OCR Gives You Words, Not a Document

GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step Would Stop Bouncing Off the GPU

Discussion

I Tried to Schedule My ETL Pipeline. Here’s What I Didn’t Expect.

Key Takeaways

Related Articles

Python 3.14 and its New JIT Compiler

Building a Custom GStreamer Plugin for NVIDIA DeepStream

Parse Scanned PDFs for RAG with EasyOCR: Free OCR Gives You Words, Not a Document

GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step Would Stop Bouncing Off the GPU

Discussion

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Python 3.14 and its New JIT Compiler
A technical overview and some benchmarks The post Python 3.14 and its New JIT Compiler appeared first on Towards Data Science.

Towards Data Science
Building a Custom GStreamer Plugin for NVIDIA DeepStream
Why Custom Inference in DeepStream? The post Building a Custom GStreamer Plugin for NVIDIA DeepStream appeared first on Towards Data Science.

Towards Data Science
Parse Scanned PDFs for RAG with EasyOCR: Free OCR Gives You Words, Not a Document
Enterprise Document Intelligence [Vol.1 #5quinquies] - Same 1974 scanned PDF, two engines. EasyOCR recovers text. Docling recovers text + sections + figures. The structural gap makes one output usable downstream and the other one a flat string. The post Parse Scanned PDFs for RAG with EasyOCR: Free

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GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step Would Stop Bouncing Off the GPU
The PCIe transfer latency is silently bottlenecking your agentic inference. Here is how building a custom device-resident vector search kernel bypasses the CPU to unlock deterministic microsecond tail latencies. The post GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step