We've accepted that LLMs will be ubiquitous. What comes next is direct control and access: an LLM in your pocket. Today's accessible hardware is still at early-iPhone levels. The goal is to deliver modern capability so teams can run powerful open-source models without needing multi-GPU setups that cost hundreds of thousands of dollars. @b3labs's rent-to-own model changes the economics: lower the initial outlay, own the machine in two years, and avoid the burden of hosting it yourself. Secure, managed facilities handle the infrastructure. For long-term AI workloads, the math favors ownership over renting. @darylX24 and @viktoriya0x (B3) and @yorkerhodes (Microsoft/NYU) join Stateful, hosted by @FranklinBi, to discuss why the next wave of AI builders is buying instead of renting: