open-source AI models

“Even an open model trained with open data, to me, is not that open, because when you have, like, three hundred billion parameters, and it's a huge black box, you don't understand why the output is what it is, is it really open? And so, I'm just putting a littl…”

“Open, obviously. You know, LLM are AI in general is an infrastructure in the future, and like every infrastructure, I'm just paraphrasing Jan, but is, is open. Open wins always with infrastructure. And so obviously I think the financial, the foundational model…”

“I think they're still lacking some products around like managing correctly load balancing customizing the models because you can do it with DIY solutions, but if you want to make it robust enough and scalable enough, it's actually not easy. And if you want to …”

“And I think in the next five years, open will always lag closed. And because open will always lag closed, because open just has fewer resources behind them and fewer incentives for people to go to go make things to be open as these things become more and more …”

“All the competitive models to the foundation models, all the open source models, bar not quite all, but most of are Chinese-based.”

“We're going to see a lot of smart teams going more and more towards open.”

“There's no way in hell that, you know, we're going to have 60 independent model companies in addition to all the open source and everything.”

“There's never been a time yet where the open source model has trumped a frontier model on innovation yet. They might be better at specialization, but they certainly don't compete yet in sort of Complex and being able to do complex tasks.”