
One AI Brain, Many Faces and Voices
Our presenter, her news-anchor self, and every character voice in our videos share infrastructure: one local LLM, swappable voices, swappable faces. The architecture that makes characters cheap.

Our presenter, her news-anchor self, and every character voice in our videos share infrastructure: one local LLM, swappable voices, swappable faces. The architecture that makes characters cheap.

Free, unlimited, private image generation at home, the ComfyUI setup we generate hundreds of images a day on, explained for a first-timer.

One local model, six daily superpowers, chat with your documents, digest long videos, summarize voice memos, build study guides, prep interviews, draft anything, all offline and private.

The complete recipe behind our presenter’s locked identity. Dataset rules, local AI Toolkit vs cloud Civitai training, the strength dials that matter, and the four rules we paid to learn.

Our whole stack, image generation, the LLM brain, everything, is reachable from a phone on the other side of the country, with zero open ports. Tailscale setup in fifteen minutes.

Every caption on our channel, including karaoke-timed lyrics, comes from faster-whisper running locally. Setup, word-level timestamps, and the two tricks that fix the words it always gets wrong.

The full blueprint for a local AI companion, speech in, talking face out. Every stage can run on your own hardware; this is the map, and every stage links to a hands-on guide.

Design a voice once, clone it forever: how we gave Aillex a warm, consistent voice with NeuTTS Air, zero GPU cost, zero per-word fees, fully offline.

MuseTalk generates lip-synced video faster than real time on a 5090, but getting it to BUILD on Blackwell is dependency hell. Here’s the exact recipe that works.

The brain is the biggest VRAM line-item and the biggest latency trap. How we run a 26B multimodal LLM via Ollama with sub-second warm responses, persistent memory, and free screen vision.