The State of AI: Down the Rabbit Hole

In this episode of RRE POV, Raju Rishi and Will Porteous unpack two major forces shaping the future of AI: model distillation and the debate between open-source and proprietary models. They break down what distillation means, why it matters for model defensibility, and how open systems have historically reshaped major technology markets. From Linux and Android to the open internet, the conversation explores what past platform shifts can teach us about where AI is headed, and why founders and enterprises should focus less on model lock-in and more on durable workflows, data, and customer value.

Highlights:

(02:04) Explaining AI Distillation

(03:10) How Distillation Copies AI Models

(06:47) LLMs Trained on Everyone Else's Data First

(08:26) The Sunk Cost Problem in AI

(14:30) 85% of AI Queries Are Repeats

(19:47) Open vs. Proprietary Models Explained

(21:28) What Windows vs. Linux Teaches Us About AI

(26:33) AOL's Walled Garden Warning

(34:34) Lock-In on Apps, Not AI Models