Journey To AI Success with Ken Grohe, President & Chief Revenue Officer, WekaIO
Ken Grohe is SVP & Chief Revenue Officer, Taos. Additionally, Ken Grohe has had 3 past jobs including SVP & GM at Barracuda Networks. He got a BS in Business Management from Boston College.
Ken Grohe’s LinkedIn: https://www.linkedin.com/in/leveragegtm/
Ken Grohe’s Twitter: @LeverageSignNow (suspended)
Ken Grohe’s Website:https://www.taos.com
Podcast website: https://www.humainpodcast.com
YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag
Support and Social Media:
– Check out the sponsors above, it’s the best way to support this podcast
– Support on Patreon: https://www.patreon.com/humain/creators
– Twitter: https://twitter.com/dyakobovitch
– Instagram: https://www.instagram.com/humainpodcast/
– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/
– Facebook: https://www.facebook.com/HumainPodcast/
– HumAIn Website Articles: https://www.humainpodcast.com/blog/
Here’s the timestamps for the episode:
(00:00) – Introduction
(01:27) – WEKA as you probably know, and some of the folks that might be data scientists listening in, they had to strip a wekabite. So it’s 10 to the 30th power. That’s a good way to future-proof it. It’s all you can fit in a file system. A new way to do storage. It’s all software, it’s all service subscription through the people you’re buying from every day. So if you run it through AWS in the cloud or on premises with Hewlett Packard, it’s a great way to get things done and solve big problems. What WEKA is, is a modern and limitless parallel file system, that’s easy to deploy any scale in the cloud or on premises for the people in the data center, solve big problems.
(05:15) – 71% of corporate data goes unused, despite how much money was spent to create this information data. And it’s going on use. So that’s amazing. So the average sale for us is a petabyte and that’s two thirds of the time. It’s on premises. One third of the time, it’s in the cloud every time to go between the two.
(08:12) – I can certainly think if you’re in a university and at the end of the day, you want an AI project and I’ll cut to the chase, not just for the greater good, but to recruit great talent. So when you’re doing that and you’re recruiting that type of talent, you’re putting it into action. And that’s probably going to be on premises. We allow you to put the right data at the right place at the right time to get, manage your information across the entire life cycle. So you make the money when you need it, and then you don’t lose it when you really want to protect it for data protection.
(13:09) – Where you live in your hat in a COVID world, doesn’t matter. They kept going. When you think about it, traditional Hollywood shut down during the beginning of COVID. Because you couldn’t break the unions, you couldn’t get the talent, the labor, they, Brad Pitt’s Reese Witherspoon’s to go on site, you couldn’t see, you couldn’t create any of the content we watched. The tiger came and things like that. But what I’ve told students able to do is enable them to create content. The need to have a parallel modern file system with no limits, no compromise. It was so important because you’re going to bring all these engineers and all these scientists, you want to make breakthrough discoveries.
(16:22) –Some early in the career, 20 something, it says what am I going to do with the rest of my career? I heard AI is great. I’m telling you now the chief data officers are to learn. And as part of it, you may not earn that job right away, but think about, and put this individual’s going to be, and typically they’ve come from the HPC high performance compute environment or the academic environment. So what’s happened is a title has risen. It’s called chief data opposite. Some of it is compliance and there’s certainly a chief compliance officer in there, but more important, more exciting is building out new applications that grab market share and new revenue streams using that.
(20:28) – Storage is going to have a Renaissance or is we’re living in right now, part of AI.
(24:53) – I see three different paradigms. GPU’s being prevalent. NBME being everywhere in the network, but especially in the GPU and the server itself.
(27:27) – All the intended AI practices and initiatives, it was going to be a fallout that over 50% of them were not going to have ROI. And that’s unfortunate. Now that number has shrunk to less than 12% per the analysts we spoke with yesterday. You never want to have strengthened aptitude and intelligence, but you don’t have the ability to use it at that time. So the pro file system lets everyone use it all the time. We take care of the locking and the overriding, all the other management is part of it.
(29:52) – You can start as small as you want and go as large as you want, but bring the ability and the imagination to solve big problems. Because storage and more importantly, AI centric accelerated storage from WEKA is certainly huge. And I love I’m going to use an ops shoot of your bottomless. I’m going to call it limitless. So it’s kind of the solutions of limitless.
(31:01) – You want the right data at the right place at the right time. No in all the cases. So you can capitalize, you can make, go faster and go actually press your advantage. And wherever it might be, whether it be retail or manufacturing. The reason I say extensibility is for naming conventions, whatever file you create, you want that same name and convention whether you’re on premises, we on a cloud, we were an object store or whatever. And what’s great about WEKA.
(33:03) – The fast, eat the slow. If that’s the case, the ability to move the correct data, the right naming conventions based on the right policies, the right security allows you to happen. So we’re kind of known as the information life cycle management type company.
(34:14) – We were involved with vaccine development, obviously with those, most of those vendors did all suppliers do that through the cloud and we have a solution for them in the cloud but ultimately a hybrid solution as well.
(39:51) – We’re not a very sales dominant culture. We’re all about solving big problems and very technical by nature to get into your use cases. In fact, most of our people spend most of the time trying to move data scientists or people represent data scientists. So if you’re in that category, we’d love to help you out.