ML Lead · AI Architect · Edge & Cloud
I build AI that ships — from the edge to the cloud.
On-device inference where privacy and latency decide it; scalable cloud serving where reach and throughput do. Architected on the economics, not the hype — and shipped as open-source tools engineers worldwide actually run.
- Flagship OSSAnyLabeling3.4k★
- FocusEdge ↔ Cloud AIinference economics
- LabNeural Research Lab@nrl ↗
- ShippingSince 2016open-source by default
- 70+
- Blog Posts
- 25+
- Projects
- 5K+
- GitHub Stars
- 8+
- Years Coding
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Local-first AI, AI security, on-device Vietnamese voice, and what I am shipping next.
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The Bottleneck Moved to Review: My SDLC After AI Writes Most of the Code
When a machine writes most of your diff, the constraint stops being how fast you type and becomes how well you review. Here is the SDLC I actually run — the provenance audit, the sandbox, the CI backstops, and the three questions I ask every AI-authored change — plus the parts of review that don't compress and never will.
Plan Once, Then Act: When the ReAct Loop Is the Wrong Harness for Small Local Models
On small local models, the standard ReAct loop has a failure mode nobody warns you about: the model calls one tool, declares victory, and stops. What we measured across 12 GGUF models in EdgeVox, why we added a plan-once dispatcher, and how to decide which loop your task actually needs.
Building EdgeVox: Chaining STT → Local LLM → TTS Without Touching the Cloud
A first-hand build narrative of EdgeVox — a fully offline voice agent that chains speech-to-text, a local LLM, and text-to-speech on one device. The architecture in plain language, ROS2 integration, the latency budget, and the failure modes nobody warns you about.
I put an AI version of myself online, then tried to break it
Building a represent-me chatbot is a weekend project. Treating it like a production security surface is the part nobody writes about. Here is the architecture, the prompt leak I found by attacking my own bot, and the reusable suite that keeps it honest.
Vietnam's Sovereign AI Conversation Is Stuck One Layer Too High 🇻🇳
Vietnam already has the chips, three meaningful Vietnamese model attempts in flight, and the most binding AI law in Southeast Asia. The conversation about sovereign AI keeps demanding a 70B foundation model. The actual gap is one layer down — open evaluation, license-clean data, compliance-aware specialized models, and on-device runtimes that operationalize Law 134/2025 starting March 2026.
AI Is Making Us Faster Learners and Worse Thinkers at the Same Time
A 2025 RCT found students who studied with ChatGPT scored 11 points lower on a retention test six weeks later, even though their work during the sessions was higher quality. Better results, worse thinking. Here is what the cognitive science says, and how it changed my own AI habits.