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Practical lessons on video, distribution, and measurement. Start with the question you need to answer, then go deeper when it helps.

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Voice Cloning on a 24GB GPU - What Actually Works in 2026
Real VRAM numbers, training times, and recipe availability for VoxCPM, Qwen3-TTS, IndexTTS2, and CosyVoice on an RTX 3090 Ti. Which models fit, which need LoRA vs full SFT, and the failure modes to expect.
LLM vs OCR Is the Wrong Debate - Here's the Actual Taxonomy in 2026
Most "OCR models" in 2026 are multimodal LLMs. The real questions are specialist vs general-purpose, end-to-end vs hybrid pipeline, and accuracy vs hallucination risk. A four-tier taxonomy with a decision framework for production teams.
OmniDocBench Is Saturated - What Our 1,331-Page Benchmark Reveals About Real OCR Failures

OmniDocBench hits 94%+ accuracy across top models, but document parsing is far from solved. Our 1,331-page benchmark on scan-heavy PDFs exposes the failure modes that standard benchmarks miss: hallucinated text, broken table structures, spaced-letter artifacts, and blank-page blindness.

Designing a Contract-First TTS Layer for Production Video Pipelines

Most teams evaluate TTS by demo quality alone. A production narration stack needs runtime contracts, cue timelines, artifact sidecars, and QA references so the workflow survives engine changes and timing drift.

How to Run an AI Video Model Bakeoff Without Turning It Into Vibes

Most AI video bakeoffs collapse into taste and memory. A production-ready comparison workflow needs clear comparison units, captured run context, shared QA gates, and side-by-side reports that survive the meeting.

What a Production-Grade AI Video Pipeline Actually Needs (2026)

Most AI video stacks obsess over generation. The real production system needs typed specs, inspectable render artifacts, layered QA gates, and runbook discipline before anything ships.

GLM OCR vs PaddleOCR vs DeepSeek: Workflow Guide 2026

Compare GLM-OCR, PaddleOCR-VL, DeepSeek-OCR-2, Hunyuan and Mistral by speed, grounding, blank-page handling, deployment and workflow fit.

How We Benchmark OCR Models on Scan-Heavy PDFs

A practical methodology for benchmarking OCR models on scan-heavy PDFs: corpus design, scoring, visual audit steps, failure modes, and the routing rule that emerged from a 31-PDF internal pilot.

Hardening Agents in Production - Locking Down the Attack Surface

A live conference-note draft on why agents are already in production, why autonomous workflows create a larger attack surface than most teams expect, and what a real security control plane must do.

Systemic Decision Rot - Why AI Governance Must Move Beyond Model Safety

A conference-note essay on why AI risk is not just about hallucinating models, but about how organizations transform AI outputs into summaries, recommendations, and institutional decisions without enough verification.

The Agent-to-Agent Internet - Evaluation Arenas, Algorithmic Governance, and the Dark Web of AI

A strategy memo on what happens when AI systems stop mainly serving humans and start negotiating, evaluating, and transacting with each other - and what content, media, and AI ops teams should build now.

China AI Model Access Guide (2026): Requirements, Compliance, and Risks

A neutral, operations-first guide to accessing popular China AI platforms in 2026: when +86 numbers are required, when email login works, and what legal, privacy, and policy risks teams should evaluate before setup.

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