One thing what I will also add is that you can take a technology which is differentiated but it is harder to stay differentiated. And I think that is where this partnership is really helping. So, I will take one concrete example.Lot of the companies now are moving into the inferencing thing. Inferencing is like you go to one of your favorite large language model and you're asking questions. It needs to keep that context and over time more and more context is being kept around so that it remembers what you a ...

When building a sovereign AI factory right now, right. It's very important to make it redundant, right. So, the way you would doing it in a country, you will have multiple sites and they will be redundant to one another, right.So, that if something happens like some of the events over the past 2 or 3 months and you lose potentially one of the data center, you're not losing all your production and all your access to data. You can just look at the current wars and what's happened, right. I mean, it can happen ...

How do I make sense of the data. How do I make sense of my documents. How do I find things fast and efficiently.And that's what we can deliver an easy button exactly for that. We take the hard part of finding the right hardware and putting it together on the software and deliver the whole thing as a combined package. You plug it in, turn it on, point to your data, and you're in business.That's what this partnership is about. This is why I think we have beginning a foundation of something very unique here wh ...

When you feed an LLM a massive multimodal file like a 100page legal contract, you're asking for a massive heavy lift. It takes about 20 seconds of intense computation just to generate the initial analysis. The model is storing its mathematical work as large tensors in what we call the KV cache.But GPU memory is premium real estate. If the user steps away for lunch or the memory reaches capacity, that context is evicted to make room for other tasks. With managed luster, rather than evicting the context, we c ...