them with that other angle, they can they can sort of steel man this side. >> Certainly. You can weaponize any term uh and certainly trust is is has been weaponized, that word. Um and the reason I say that is because it means something in based on the context and with your speech you're speaking about it. Uh often in AI, people like to conflate trust with safety um and those are not the same thing. Uh, and I'm happy to speak on safety, uh, you know, later on. But when it comes to trust, um, I I think that, you know, you hear a lot from closed model providers or uh, politicians or people out in the space who are advocates for or uh, against open source that you can't trust these open models cuz you don't know what went into them. Well, the same is true for these closed models, uh, even more so. Uh, the benefit of uh, uh, of of open models is that uh, we can very easily validate what is inside of them. Uh, they are you can there is a whole bunch of files with a whole bunch of matrices in there and you can view them and you can see the code that is running these models. You have implementations from Prime RL, vLLM, SG Lang, the provider themselves. These models are inherently trustworthy. You know much more about what's going on when you hit and talk to these models than you ever will what's going on when you hit an arbitrary API. Now, that being said, um, certainly there is fear that people can um, reduce uh, you know, the you can't trust that these models are writing safe code. Well, again, that is the same thing with any model. You need to you need to use your uh, your judgment and you need to make sure that you have the proper um, you know, safeguards in place and you're viewing the outputs of these models as the outputs of uh, an inherently random system that we are working very, very hard to make less and less random. I think that uh, a telling thing is a lot of people said, "Well, you can't trust Chinese models. You can't trust Chinese models. You can't trust Chinese models." That was often uh, for the last few years meant you can't trust open models. Well, as soon as uh, Anthropic had to put Fable away and people realized that, "Oh, our access to these frontier systems might not be universal anymore. Uh, there's probably going to be a lot of checks and balances. You had a tremendous number of enterprises and developers and companies start going to these new Chinese models because they could trust that they would always have access to them. Um and so when when it comes out of trust in the way I view that word as it relates to open models is do I know that what I am running and can I be as sure as possible that when I send something to this model that I am going to get the output that I expect? Um and the only way uh currently to be 100% sure that what you are getting is what you were expecting is by hitting an open model either that you are running yourselves or you're working with a partner like Prim Indelec or RC or Nvidia to validate. So that's my take on the word trust.