Open Source Meets AI | Red Hat's Scott McCarty

**Scott McCarty** (0:00)
This has to be one of the business requirements that technical people have to hold the model creators responsible for, right? And right now, I'm not sure if that feedback loop, how strong it is, we can get deeper into that, but there's challenges with, it does open source AI even exist, I guess that's another challenge.

**Conor Bronsdon** (0:17)
Oh, we're definitely gonna dig into that.
Hey, folks, we are back for another deep dive episode of Dev Interrupted. I'm your host, Conor Bronsdon. And today, we are jumping into the world of open-source gen.ai with Scott McCarty, Senior Principal Product Manager at Red Hat's Enterprise Linux platform. Scott's here to talk about how open-source AI can revolutionize enterprise DevOps, innovating while still solving key challenges around licensing and legal concerns. If you enjoy this episode or other episodes of ours, please just take a brief moment to rate and review Dev Interrupted on your podcasting app, whether that's Stitcher, Spotify, Apple Podcasts. It helps expose the podcast to other leaders who could find value from it, and it helps us land great guests like Scott. So Scott, let's get started on the state of AI and enterprise DevOps. AI is obviously creating huge possibilities for developers, and I'm sure many folks are kind of sick of hearing us say those words, AI, AI, AI. But when it comes to deploying these models commercially, there's still a lot of hesitation. Are they making money? Do I really need this? Is it as effective as I want it to be? What do you see as the biggest roadblocks keeping AI out of production environments right now?

**Scott McCarty** (1:35)
Yeah, I think obviously I'm the Red Hat guy, so I'm going to talk about open source. I think, you know, I'd say, well, much like the early days of open source, a big blocker is not sure, being not sure yet of like what does it all mean? What can I use? What can I get, what am I going to get sued for?

**SPEAKER_4** (1:51)
You know, what can I use, et cetera?

**Scott McCarty** (1:54)
It reminds me of the early days. I remember being like 1997, and I guess I'll tell a story. Like I started at NASA in 1999, and I remember I was the new kid, and I was young, and they were using Solaris and IRECs and all kinds of other things. And I brought Linux in, and I was like, yeah, we can just use this Linux thing. And they were like, and they had to get this approval process that went up through all these managers. And then six years later in like 2005, when I left, it was the other way around to still buy IRECs and still buy Solaris, you had to get an approval all the way up to the center director. And so like how quickly it flipped, right? Like six years, it completely changed. I think we're in a similar place with AI where it's like still kind of scary. We're not sure like, oh, did it pull data from Reddit? Did it pull stuff from, you know, did it pull some licensed, you know, or copyrighted text or copyrighted images or whatever? Like, so there's a lot of indemnification challenges. I'd say there's one big one.

**SPEAKER_4** (2:45)
But I'd also say there's like an actual use case challenge too.

**Scott McCarty** (2:50)
Like, there is, we are clearly in a hype cycle, obviously. Like two, three, about a month ago, I was at DevCon US, which is a Red Hat sponsored conference. It's kind of like one of our really engineering focused conference.

**SPEAKER_4** (3:00)
And we had a day zero.

**Scott McCarty** (3:02)
And I would say the vibe I got from probably 300 people from a bunch of different companies was like, don't say the word AI again.

**SPEAKER_4** (3:08)
There's a extreme lack of use cases.

**Scott McCarty** (3:10)
There's a lot of people saying, we just got to do AI. We don't know what it is. You know, like just figure out something.

**SPEAKER_4** (3:14)
I think that's a big challenge too.

**Scott McCarty** (3:16)
I think real solid use cases is a challenge right now.

**SPEAKER_4** (3:20)
Those are probably my two biggest ones.

**Conor Bronsdon** (3:22)
Well, Scott, I want to ask you about those legal and licensing concerns you mentioned. Obviously, this is a huge area of risk for Gen. AI. I mean, I think we've also seen some of the generated work that's happening in places like Disney today. This is gonna date the episode, but it was announced today that the actor who played Grand Moff Tarkin, his estate, and his good friend are suing Disney over the use of his likeness in Rogue One. So there's a lot of stuff happening here on the licensing front, both just simply on the generation side, as far as the video and pictures. We've seen fakes of Taylor Swift and many other celebrities, but also, if we dive into the enterprise model side of things, where are you training your data? Where are you getting that data from? Are you allowed to train off it? And so much more. So can you dive a bit more into what's happening there and where there are risks?