Building with AI: From Enterprise to Home Inference
A personal AI lab that bridges enterprise AI experience with hands-on infrastructure. Running production-class models locally to build, learn, and ship real projects.
Hardware setup
GPU
2× RTX 3090
48 GB VRAM combined
Model size
70B params
Llama 3.1 family
Hypervisor
ProxMox VE
Local virtualization
Projects
VPN Tunnel to Oracle Cloud
[Placeholder: Overview of setting up a persistent VPN tunnel between home infrastructure and Oracle Cloud free tier. Why this matters for secure access, hybrid compute, and cost-efficient GPU bursting.]
Secure hybrid network linking on-prem and cloud GPU resources at zero recurring cost.
Self-hosting Llama 3.1 70B
[Placeholder: How to run a 70B parameter model locally on dual RTX 3090s with vLLM — quantization choices, VRAM management, throughput benchmarks, and what workloads this unlocks without cloud API costs.]
Full 70B inference at home — zero API costs, full data privacy, usable throughput for real tasks.
AI Video Upscaling with Claude Code
[Placeholder: Using Claude Code to build a Real-ESRGAN + FFmpeg pipeline for upscaling archival video footage. The workflow, the prompting strategy, the quality tradeoffs, and the results on actual source material.]
Before
Original footage
After
AI upscaled to 4K
Automated pipeline upscaling archival footage to 4K — built with Claude Code in a single session.