Aaron Levie

speaker

937 appearances 2 recordings 1 series first heard Jul 2025 last heard 5 Sep

Aaron Levie’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Sep 2026 with 1.

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The a16z Show · Aaron Levie on Why Open AI Wins · 5 Sep 2026 podcast

We support every one of those stances.

You know, open models are I think is very important today ecosystem.

And I actually think it it pushes even

The closed model providers to innovate faster and be able to deliver more for the market.

So I think everybody is sort of a winner as a result of open weights.

To be fair to the other side of the argument, I think there's a category, forgetting kind of commercial and economic interests for a second, of some of the closed players.

I think there's a category that obviously has real arguments around the safety elements of open weights at some point in the future of capability.

I don't agree with that point of view, but I think it's like a healthy debate to have and to have conversations around.

around it, but I almost unequivocally take the stance that more open innovation and open weights innovation is good for AI broadly and the diffusion of AI.

Well, I don't know if I would make that argument.

I don't know where that line would exist.

I'm almost deeply on the side of I think it's very hard to make the argument that AI models should be trained on broadly the public internet, but another AI model can't be trained on the outputs of an AI model.

I think it's a very tenuous argument to make.

I don't see how you can kind of pull it off.

At the exact same time, I understand and if I were running a lab, I would want to like lock these things down as much as human.

Possible.

So I'd be trying to find every defensive mechanism to prevent the distillation of my models, but I don't know that you'd be able to kind of credibly argue that there's some ethical kind of line that is crossed simply because then you would be basically arguing against the underlying training runs of these models.

Yeah.

Most people didn't get to opt in or out of their data being trained on.

Maybe it's in some kind of terms of service from the underlying provider somewhere in the fine print.

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