Howie, great to have you on the podcast here today. How's it going?
Jared, good to be here. I'm doing well. I'm excited to chat.
Let's dive right in. First off, would love if you could tell the audience a little bit about your background, and then we'll talk about some of the cool things you're doing at Gen, and then we'll dig deep into your thoughts on what's happening in AI today.
Yeah, so I'm a software guy for the last 20-some years. Early VMware guy. I've done a few startups in the recent decade. Also, I've been doing AI machine learning, and of course in the recent years a lot of the generative AI. Right now I'm the Chief AI and Innovation Officer at Gen. Gen is the former Symantec consumer business, you know, acquired a few other businesses and I combined and renamed to Gen. So, having a lot of fun. And my mission here is actually one is to hopefully put the company on the right trajectory when it comes to AI adoption, and the other thing is actually develop some interesting AI-native applications.
Now, one of the things I'd love to hear from you is, it can be about Gen, but even outside of Gen, a few things that really excite you about where AI is at today, and also maybe a few things that scare you about where it is today.
Yeah, I mean it's actually the same thing. What excites me is actually AI is finally on the trajectory of being pragmatic. What does that mean? Because we all have, you know, we have known AI for decades, and we know deep learning for more than a decade, right? So people have been doing AI deep learning for a while, but the reality is, other than a few very specific use cases, it's very hard to get AI into pragmatic adoption or deployment. When you look into why, it always takes 50 steps to get this AI right, and the 50 steps takes a lot of effort. What excites me is finally gen AI or foundation model basically shrinks that 50 steps to, I don't know, 15 steps or 10 steps. So from that point of view, because we basically get a model, the baseline, better, so that you can do less. But you also ask me what scares me. I think what scares me and the industry should be, it still takes 10, 15, maybe 20 steps to do it right. So don't underestimate to get AI done right. So a lot of time people just see a sexy demo and say 'Wow, let's do it' without understanding what's really behind that. So in a summary, what excites me is finally AI is a lot more pragmatic than before when it comes to adoption, but what scares me and everyone should be, it's still not an easy task.
Let's do something kind of fun here. What's a company you really admired, let's say back 10, 15 years ago, and how would you rethink that business if AI was at the level it's at today back then?
10, 15 years ago, you know, I mentioned earlier I was an early VMware guy. I left about, I don't know, 13 years ago. So VMware, I grew up at VMware, right? And that's a company I admired a lot. What would AI have done? So here's the thing: VMware was the leader, right, industry leader before the public cloud days. Software infrastructure, everyone was migrating to VMware. In some ways, I wouldn't say VMware missed the public cloud, but they didn't really thrive in the public cloud age. It's almost like Microsoft missed the mobile right in some ways, but they took, they got another act going. So I think VMware could have got AI going even though it missed the public cloud thing. So what does that mean? When it comes to AI, a lot of that is just automation, because managing infrastructure, managing security, managing storage, it just takes forever. So if you were able to adopt AI into the real management, the real day-to-day thing, that would have saved people a lot of time. I don't think we as industry have done very well, because we are always attracted to sexy demo and then celebrate prematurely. But it's one of those things, it's a company I admire a lot, and I think it's a company that could, even today, AWS, Google Cloud, they are getting AI into their cloud, into their management console, into their everything.
Let's kind of shift focus a little bit here. When you look at, what is your advice for companies that are looking to start to integrate and implement AI into their workflows? Let's kind of come up with a 90-day plan, right? So what would you give advice to executives, first 90 days they're not leveraging AI at all, what does that 90-day plan look like to get started?
