Hi everyone, welcome to the Ravit show. We are here at Nvidia GTC and look with me co-founder and CEO of DDN. Alex, first of all, it's good to have you back on the show. Super excited to chat today.
Well, Ravit, it's wonderful to be with you. You always bring such energy and information into your show. It is super informative and super valuable to the industry. So, thanks for doing what you do.
Thanks, Alex. We always try and leaders like yourself always obviously get us all the great insight. So I'm excited to get started and I'm going to start with obviously the most talked topic here at Nvidia GTC that is AI factories. I want to know from you Alex in simple words what is AI factory and what does most of the enterprises get it wrong?
Absolutely. So an AI factory, the notion of it is it is something that you invest in, it's infrastructure that you invest in that is bringing value to you, that business and financial value that is being delivered is the only thing that matters. So an AI factory in order for it to be efficient, valuable to an organization needs to do two things: it needs to be easy to deploy so that an organization can very easily benefit from it very quickly, and it needs to deliver value that is very cost-effective so that the CFO can say yes this was a great investment. Let's keep expanding it. That's what an AI factory is. It is an infrastructure which delivers business and financial value to organizations no matter what industry you're in.
Yeah, I love it. When it comes to obviously enterprises, I think the first things first that they always care about is like the value that they get and AI factory with the infra that it has, it can bring to the table is phenomenal.
Yes. So I have another curious question for you. This bus where we are standing right now is a board move. I'm kind of wanting to know why did DDN decide the best way to explain AI factories and what was the reason behind putting this together because I know no one has ever done that.
So this is the first time I'm seeing it. I'm going to be seeing this all in the states. We're going to be traveling with it all over.
So I'm kind of curious to know why did this happen and what was the reason behind it?
Sure. So the reason is very simple. Exactly like you said, enterprises are scratching their heads and they're saying, 'I need to do AI. How do I do AI? What are the benefits that I get from AI?' So we thought, we're going to create a bus. We're going to put it on the road and we're going to take it to where the enterprises and the customers are. And we're going to show them, hey, this is what you can do. You're a financial services organization. You're a bank. You're a hedge fund. You're a pharmaceuticals company. You're an automotive company. Let us bring it to you so that you see in your environment what is possible. That is the biggest hurdle I think enterprises are struggling: what do I do with AI? And so showing it to them in a bus that comes to them as opposed to they have to come to a show we thought would be incredibly valuable. And Nvidia jumped on the bandwagon, they thought it was a great idea. So here we are, here's the bus, we're going to take it on the road, the AI factory bus.
I love it. I love it how you kind of do it for the enterprises out there and how y'all are helping the enterprise leaders to get from point A to point B. I've been, you know, obviously it's day two, you're at NVIDIA GTC, but I've been hearing so many different conversations. You're at the DDN booth, you're at the bus as well, and everyone's so excited about obviously checking the AI factory out there and what better than doing it for everyone where they are. So, thanks for doing this, Alex. I have another curious question and this is more a little technical, but I'm kind of wanting to hear because I talked to a lot of enterprise leaders and they are most curious to always learn more about the AI pipelines. So you were showing four AI pipelines: inference, rack, quant, genomics, and video analytics. Tell us a little bit more about it.
Sure. So let's take a couple of them. So we're showing a quant analysis pipeline. The quant pipeline demonstrates a few things that are very beneficial to organizations that are in financial services. It demonstrates an acceleration in taking very complex models, running those models, getting insight, and then being able to make better investment decisions that then benefit the investors. So, it's demonstrating in the real world a pipeline that can be deployed at a hedge fund, at a bank, at a financial services organization, and they immediately get the benefit. So, they immediately deliver better returns to their investors. So, that's one aspect. Another aspect of the FSI pipeline is risk management.
In financial services, you have to be in compliance. It's very important to be in compliance. So they're very regulated.
Yes. And so being in compliance is something that is extremely complex and time-consuming. So our pipeline enables organizations in the financial world to be in compliance and they can figure it out within minutes as opposed to hours. And then if you miss the compliance window the fines can be tremendous, can be hundreds of millions of dollars. So that is a practical real world benefit both in terms of risk management and in value creation. Same thing across all industries: pharmaceuticals, video, and so on. We're going to expand this set of pipelines across all industries so that organizations who are not necessarily familiar with AI but know their business very well can say, 'Aha, this is the huge benefit that I get in my industry by utilizing AI.'
Yeah. No, I like it. I like how you all have made it easy for the enterprises to think that oh AI implementation can be done in the most easiest way when our pipelines are sorted and when it comes to regulated industries like finance, healthcare, it just becomes more and more.
Absolutely. Bringing a new drug to market, getting FDA approval, it's a very long and complex process, very very expensive. So you have a pipeline that does that for you, you significantly shorten the window, you bring the drug to market faster, it benefits consumers faster and you lower the risk. You lower the risk of the FDA saying, 'Oh, no. This is not ready.' And then you have to go through another very very costly process. So, it is compressing time. It is adding business value. It is adding financial value. That's what AI needs to do. AI needs to transform all industries. We're making it a lot easier to demonstrate the value and implement it for these organizations.
Yeah. No, I love these use cases because what happens is most of the time the enterprise leaders are stuck in the implementation phase.
