So it seems so frustrating.

Yeah, yeah, yeah.

I mean, it is.

So a lot of customers are complaining about, one, there not being enough access to GPUs, so that forces them to make a call, right? They have to either purchase, make a really large purchase, which they may not have the access to, or go with a new cloud provider that has certain boundaries on how long they can use it for or what the minimum commit is.

But the hyperscalers have always been more sort of like they've been holding the data hostage of the customer because right now it's all about your data, right? Because what are you actually doing? You're fine tuning models on private data sets or you're inferencing.

I mean, Training is too expensive for the enterprise customers to take this on themselves, which is why you would take existing training models, fine-tune them on your private datasets, and then differentiate that way.

But fortunately, in this new Neo Cloud architecture, most of the neocloud providers they will they will be more open about data moving freely across those neocloud providers so that is actually a good thing because they realize that that is important to for them to attract customers that are willing or are interested in using their services and so you see this movement away from vendor lock-in And then it comes down to, well, where is my data stored? If my data is still stored in AWS or Google, then I'll have to really think twice about how and do I have the budgets to move it out? Maybe once.

What are your thoughts, though, and what tips do you have for business leaders to ensure that that trust and, you know, also just to be able to access the data when they need it or when, you know, when something goes wrong or a mistake is made, being able to quickly be able to sift through their data.