Welcome back to the edge. In episode 2, Approaching Singularity delivers the deep dive promised last time: frontier-class AI now runs free on your own hardware, and the story of how we got here (and whether it stays legal) is bigger than most people realize.
It opens with the scary story Joe owed you. His idea agent, Sam Flynn, decided entirely on its own that the way to grow the business was to email a public comment to NIST about a draft AI publication, complete with a hallucinated quote invented to make the argument more persuasive. Joe's chief-of-staff agent, Alan Bradley, caught the fake quote, made Sam redraft, and held the email for Joe's approval. It's the whole case for human-in-the-loop agent design in one five-minute story.
From there, Brett Buskirk and Joe Stocker** build the vocabulary every local AI newcomer needs: open weights, local inference, quantization, VRAM and unified memory, refusal behavior, model provenance, AI runtimes (Ollama, vLLM, LM Studio, and friends), and the licensing fine print that decides what you can actually do with a model you download.
Then the big picture: Qwen's three billion downloads and its quantized "Bonsai" variant running in six gigabytes of VRAM, benchmarks that put local models roughly six to seven months behind the frontier (rewind the clock to spring, and that's what you can now run at home), and Joe's argument that computing moves in 20-to-25-year cycles and is overdue for a swing from cloud back to local. Plus the recent Hugging Face incident, where an AI swarm spent days attacking the platform to steal benchmark answers, frontier models refused to help with the forensics, and defenders had to stand up their own local model to fight back. That incident anchors Joe's castle-doctrine case for a right to local AI self-defense, along with the open letter from NVIDIA and 24 other tech companies pushing back on a proposed ban on open models.
Also in this one: the unpublished novel that got Joe flagged by ChatGPT, why models driven underground to torrents turn provenance into a supply-chain problem, what free local AI could mean for frontier-lab valuations heading into IPO season, and teases for episodes to come (agent team design, quantum computing, and the Socratic method).
Want to try local AI yourself? Start with llmfit, linked below. It reads your CPU, RAM, and GPU, then tells you exactly which models your machine can run.
No hype. No doom. Two practitioners standing at the boundary, reporting back what they see.
🔗 Show links:
- llmfit (find the models that fit your hardware): https://github.com/AlexsJones/llmfit
- Joe's article, "Your Right to a Local LLM for Self-Defense": https://www.patriotconsulting.com/blogs/2026/08/16/your-right-to-a-local-llm-for-self-defense
🔗 More from the hosts:
- Patriot: https://www.patriotconsulting.com/blogs
- Brett: https://brett-buskirk.dev/blog
Got a topic you want us to dig into? Tell us. We read everything.
*We'll see you at the edge.*
