This week Kate hands over the mic to Saron Berhane, who leads Blackbird's deep tech programme. She was recently in San Francisco and sat down with two Australians who had to move to the Bay Area to do the sort of work they wanted to do. Which is both their personal experience and one of their main arguments in this episode. Australia's problem in AI isn't compute. It's that the smartest people here go into quant trading or get on a plane, and nobody has built them a reason to stay.

Baseten is where they landed. It's an AI infrastructure and production-grade inference platform, the layer that lets engineering teams deploy, scale and optimise machine learning models. Sydneysider Tuhin Srivastava co-founded it, and it recently raised a$1.5B Series F led by Altimeter Capital, Conviction Partners, Blackbird and Spark Capital.

Mudith Jayasekara and Charlie O'Neill are Baseten's Co-Heads of Model Training. Before that they founded Parsed, a mechanistic interpretability lab that Baseten acquired. Mudith trained as a doctor. Charlie started in law and philosophy and wanted to study English literature. Neither took the path you'd draw if you were designing someone to run model training at a company like this, and both think that's the point.

The conversation is wide-ranging and deeply technical. Saron takes them through what's actually happening inside the open source ecosystem right now, which is stranger and more hopeful than the usual framing allows. Sitting underneath all of it is one question. When everything difficult gets commoditised, what's left? The training recipe is now roughly the same everywhere. Post-training has gone from a specialist problem to something a small team can attempt. The friction on running an experiment has mostly gone. What's left is taste, and having enough of the right people in one room.