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From Messy Documents to Structured Data with Docling
Docling takes documents in whatever inconsistent format they arrive in, and converts them into one unified, structured representation that both people and AI systems can work with reliably, rather than everyone downstream having to guess at what a wall of extracted text actually meant.
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SuperWhisper s1-mini: The 600M Parameter Model Built Just for Transcription
This is a summary of, and insights into, what I found digging into the recently-released Superwhisper S1 family of voice-to-text models.
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Gemini 3.5 Transcribe vs OpenAI’s GPT-Transcribe
Here's how each got to where it is, a real use case and working code for both, and a side-by-side on the numbers that actually matter.
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What I’ve Learned About DeepSeek Harness
KDnuggets team member Shittu Olumide tested out DeepSeek Harness. Here's what he found.
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Everything Claude Opus 5.5 Actually Ships With
This article pulls together every verifiable number and detail from Anthropic's announcement, the platform documentation, the system card, and independent coverage, so you have one place to check the facts.
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5 Prompt Optimization Strategies That Actually Improve LLM Output
This article covers five prompt optimization strategies such as: prompt optimization, prompt engineering, LLM output quality, few-shot prompting, chain-of-thought, structured outputs.
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What’s So Good About ChatGPT Work? Here’s What I Found
This article walks through how ChatGPT Work specifically earns its reputation, where the underlying models genuinely hold up against the competition, and where the honest limits are.
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How I’m Using Google Opal for Even More AI Automations
Opal is Google Labs' no-code tool for turning natural language into working AI mini-apps, built on top of an internal framework called Breadboard. Here's how I learned to use it best.
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5 Python Techniques for Efficient Resource Orchestration
This article explains 5 Python techniques for efficient resource orchestration and sticks to what's stable today, 3.11 and later for the core techniques, with one 3.14-specific tool called out explicitly as requiring that version
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Quantization and Pruning Methods to Make Your LLM Leaner
This article walks through what each technique actually does, why skipping them costs real money and real latency, and then gets hands-on with five specific methods people are running in production right now.
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