Kelly Randis [00:00:00]:
Technology is great and the advances in technology allow us to do so much right, find cures for different diseases and cancers and treat patients and find molecules and develop better equipment and motors and stuff. But it opens us up for all sorts of risk that wasn't there when we didn't have these systems.
Kelly Randis [00:00:19]:
Right.
Kelly Randis [00:00:19]:
The more we computerized, the more places we let people try and attack, the more bad things can happen.
Steve Swan [00:00:29]:
Welcome to Biotech Bytes, where we speak with IT leaders within biotech about the current technology trends affecting our industry today. I'm your host Steve Swan, and I have the pleasure today being joined by Kelly Randis, global head of it for Gamida Cell. Kelly, welcome.
Kelly Randis [00:00:43]:
Hi Steve, thanks, appreciate being here.
Steve Swan [00:00:47]:
Sure, sure. Thanks for joining us. So I always like to start out with just getting a quick understanding of you and your organization. So tell me a little bit about how you got to where you are and that sort of thing, and a little bit about your company if you like.
Kelly Randis [00:01:00]:
Sure. So I've been in it for 30 years at this point, right. Working in pharma for 27. So a lot of time in the pharma industry. Started working on computer systems validation testing and moved through the ranks. Developed mobile applications for the commercial team, then took over all of operations for the commercial organization, then went into enterprise architecture for a while for a few years, started up a center of excellence and innovation for Bristol Myers Squip and Celgene, and currently cellular therapeutic company. We have a product that was approved in April. I'm going to call it, for lack of a better term, a cure.
Kelly Randis [00:01:43]:
Don't, it's not a cure, but it is significant to help people with blood borne type cancers.
Steve Swan [00:01:50]:
Very cool. And so you help them build up their IT infrastructure and such, right?
Kelly Randis [00:01:56]:
Yeah, I came over in February of last year. They had no it. They were pretty much a startup in the US, even though they'd been around for a while in Israel. So came in, built out the firewalls, secured them, upgraded them from there, built out cloud environment, moved our stuff into Azure and AWS, implemented single sign on using okta, identity governance and workflows. So in the process of rolling that out, also in the process of integrating some of their systems, using Boomi to make it easier to pass data back and forth, right now that's missing. Basically changed the Microsoft licensing and made sure everybody had consistent licensing. So pretty much started from scratch and have built it out a little bit at a time.
Steve Swan [00:02:44]:
Well, so tell me, you know, a lot of the conversations that I've had with, with it leaders for biotechs and such. You know, we talk about different technologies and as they're, as they're coming or their thoughts and feelings. Right. You and I spoke about that too, in the past. Thoughts and feelings around technologies. What do you see, you know, because you've been doing this for more than a minute. Right. So what do you think? What do you see as far as trends that are coming in our industry or that are here, maybe even in our industry, that have made us better, smarter, faster, what we do?
Kelly Randis [00:03:13]:
Yeah. So AI is really coming in, right, to all different aspects of it, but also into the scientific world, making it maybe easier in the future to identify compounds. But in the IT world, it's already in place in some of the cybersecurity systems that are out there for monitoring. I know some of the service management systems are now incorporating AI to help you write knowledge articles and to give better responses to tickets when they close. So I think that's going to be a big one and already impacting certain areas, making sure that things are secure is going to be important.
Kelly Randis [00:03:52]:
Right.
Kelly Randis [00:03:52]:
That cybersecurity technology is always changing because the hackers are always getting better.
Kelly Randis [00:03:58]:
Right.
Kelly Randis [00:03:59]:
They continue to find a way to get in. So that's going to continue to evolve.
Steve Swan [00:04:04]:
Yeah, I've read a lot about that. The cybersecurity and the operation side of things, the monitoring.
Kelly Randis [00:04:08]:
Yeah. That's all very important.
Kelly Randis [00:04:10]:
Right.
Kelly Randis [00:04:11]:
I know just recently, right, there have been a lot of smaller companies getting hacked. One of the biggest things is phishing, right? There's a lot of phishing going on and the people that are sending the phishing emails are getting smarter and smarter. There's a phishing email going around right now and it says it's from Citibank. And the only way you can tell it's a phishing email is because the a in the word bank for Citibank is a different font. Everything else is legitimate, but it's a phishing. So you go and you give your information and then, you know, it could be devastating to your company. And I know of a company, you know, had one user get phished, put in their credentials, and then within 24 hours the company was being held for ransom after they paid the ransom. Now they're just under constant attack because the dark side of the Internet knows that they're going to pay out to continue to do work, right? So they're scrambling.
Kelly Randis [00:05:18]:
So you, you know, that's very important, but AI is not going to help with that. It might a little as things like mimecast and Zscaler and all that get a little smarter. But the best defense for that is our people, right? Making sure they are aware of what a phishing email looks like and how to avoid it. And, you know, just don't answer if you're not sure. Ask the question and monitor.
Kelly Randis [00:05:44]:
Right.
Kelly Randis [00:05:44]:
I got. I got an alert last week for somebody had done something that they shouldn't have done and was able to immediately shut them down.
Kelly Randis [00:05:54]:
Right.
Kelly Randis [00:05:55]:
Block, kill all their sessions, shut them down, get them on the phone, you know, check everything remotely on their computer, scan it, you know, reset their MFA, reset their password and resolve the issue before anything could happen.
Kelly Randis [00:06:10]:
Right.
Kelly Randis [00:06:10]:
But if you don't have all those systems in place, you're not. It's not constantly being watched. It's going to get in somewhere. So that's going to be important.
Steve Swan [00:06:19]:
Do we know, or. Again, this is just me thinking out loud. This doesn't matter almost to the discussion, percentage wise, any idea on how many folks or how many organizations are paying out on the ransomware? Is it a large percentage? Because I have no idea. I haven't read on that.
Kelly Randis [00:06:34]:
I haven't read about that either. I've heard of some, right. Through peers and colleagues and stuff. I'm sure that organizations, like, if we googled it, I'm sure we could find a percentage, but I don't know.
Steve Swan [00:06:47]:
But it's substantial. They're making money, right?
Kelly Randis [00:06:50]:
Yeah. Or they wouldn't be doing it. And once you pay out, once, you're just going to become a target because they know that you're going to be. You're going to pay out.
Kelly Randis [00:06:59]:
Right?
Steve Swan [00:06:59]:
Well, so I actually read a story about a hospital system that got hacked and they had ransomware. Then they paid. But what they. What they what. What the hackers did was they somehow got pictures of maybe sick patients or something and they kept posting around on the Internet till they paid. I was like, wow, that's insane. That's crazy. But I guess they.
Steve Swan [00:07:21]:
They go to. They do whatever they got to do, right?
Kelly Randis [00:07:24]:
Yeah.
Steve Swan [00:07:24]:
I mean, whatever they got to do.
Kelly Randis [00:07:26]:
So I read an article about a car's computer getting hacked because that is possible. Your cars, right? Your car has computers in it. And think about how cars get more and more sophisticated. You're a Tesla can upgrade your computer with the car sitting in your driveway. So if they can connect, hackers can connect.
Kelly Randis [00:07:49]:
Right?
Kelly Randis [00:07:50]:
And you talk about cars are. The brakes are getting controlled by a computer, right? Everything, right? So, not that it's ever happened, maybe a good topic for a SCi-Fi right? But somebody could hack into these automobiles, these self driving automobiles, and wreak havoc.
Kelly Randis [00:08:08]:
Right?
Kelly Randis [00:08:08]:
The more we computerized, the more places we let people try and attack, the more bad things can happen.
Steve Swan [00:08:15]:
I didn't even think of that anymore. Wow. That's crazy.
Kelly Randis [00:08:20]:
Well, wherever you have a computer, right? Wherever, yeah, sure. No, that's open.
Steve Swan [00:08:24]:
Makes sense. I just never thought of it. So I'm going back to the VW bug. That's it. I'm done.
Kelly Randis [00:08:30]:
I want a Freddie Flintstone car.
Steve Swan [00:08:32]:
Right, right. If someone wants to hack my, that. That'll be the equivalent of hacking my lawnmower, you know? So I'll go back. I'll go back to the VW and I'll be fine. You know, I won't get over. I won't get a speeding ticket either, because I won't be able to go faster than 63 miles an hour. So, yeah, yeah.
Kelly Randis [00:08:47]:
I mean, technology is great, right? And the advances in technology allow us to do so much, right? Find cures for different diseases and cancers and treat patients and find molecules and develop better equipment and motors and stuff. But it opens us up for all sorts of risks that wasn't there when we didn't have these systems.
Steve Swan [00:09:11]:
Yeah. And a lot of the CIO's I'm talking about are talking about AI, right? And they're talking about their use cases and things. And, you know, the holy grail, right, is on the scientific side because whenever you see, you know, the CEO's right, on C SPAN getting grilled by, you know, our government about the cost of their drugs, they're always citing the length of the research and discovery period and everything that's got to go on in the labs, which is legit. Right. But, you know, if AI can come along and shave six months, right, three months, a year off that, or help them at the same time, maybe even help them say, okay, maybe we don't do these kinds of experiments because this is, this is a waste of time. But we get to this, that's huge. That's a low hanging fruit, and that's kind of the holy grail for everybody, right. You know?
Kelly Randis [00:09:54]:
Yeah. From a scientific standpoint, yeah, that's huge.
Kelly Randis [00:09:57]:
Right.
Kelly Randis [00:09:57]:
If you can cut down on that research and development time, and then maybe the FDA can use it to cut down on some of their review time so that the cycles don't have to be as long, reducing cost, sort of like they did with the COVID vaccines, right, when it was a necessity. Find ways to do that regularly. AI I think if it gets to a certain point, can be critical for cybersecurity.
Kelly Randis [00:10:24]:
Right.
Kelly Randis [00:10:25]:
It can watch the traffic and get smarter about what's going in and pick up an anomaly that we would never see.
Kelly Randis [00:10:31]:
Right.
Kelly Randis [00:10:32]:
And protect us better. So. But I don't think it's there yet. I don't think enough people are doing that yet.
Kelly Randis [00:10:38]:
Right.
Kelly Randis [00:10:38]:
Like, because AI still needs the training, still needs the knowledge. Yeah. On the scientific. But I think there are a lot of really good use cases in technology.
Kelly Randis [00:10:52]:
Right.
Kelly Randis [00:10:52]:
Cybersecurity, but just, just in general.
Kelly Randis [00:10:55]:
Right.
Kelly Randis [00:10:55]:
I think AI as a jury versus humans would be a good idea.
Kelly Randis [00:11:01]:
Right.
Kelly Randis [00:11:01]:
Because that would remove bias. Although, you know, you have to worry about bias in AI too. So that's something you have to think about as well.
Steve Swan [00:11:11]:
Because the hallucination, synthetic, right?
Kelly Randis [00:11:13]:
Yeah. Because the people who are programming it or teaching it have biases and it will learn.
Kelly Randis [00:11:20]:
Right.
Kelly Randis [00:11:20]:
Look at what happened to Microsoft when they released that one a couple of years ago on Twitter.
Kelly Randis [00:11:25]:
Right.
Kelly Randis [00:11:26]:
Within an hour, it was making all sorts of inappropriate comments because somebody went in and retrained it. So I don't know that there's a way around that yet.
Steve Swan [00:11:37]:
Well, so one of my guests was talking about that and he was talking about his thought around that, that particular thing. Right. Making inappropriate comments. It would be for your validation testing or your, you know, whatever, your testing of AI to apply the same sorts of rules and parameters from an HR perspective. Right. That would be inappropriate for an individual. Right. So let's not allow AI to say that or do that, you know what I mean? And try and cut.
Steve Swan [00:12:05]:
I don't really know how that would work. Right.
Kelly Randis [00:12:06]:
Yeah.
Steve Swan [00:12:07]:
That's why I'm on this side of the camera. Right.
Kelly Randis [00:12:09]:
Well, AI is constantly learning, though, right?
Steve Swan [00:12:11]:
Yeah.
Kelly Randis [00:12:12]:
So every time you feed it information, it's learning. And that's what happened with the Microsoft example.
Kelly Randis [00:12:17]:
Right.
Kelly Randis [00:12:18]:
They had trained it to come up with certain responses, but the twitterverse at the time started sending all this inappropriate stuff. So they basically retrained it.
Steve Swan [00:12:30]:
Right.
Kelly Randis [00:12:31]:
And programmatically, you can probably put some constraints on it, but there's still that possibility, right. That you're not going to be able to eliminate all of that.
Steve Swan [00:12:43]:
Right. Because it, again, as everybody's saying to me, you know, data is the fuel for the engine, right? And if you give it bad fuel. Right. We could call it bad fuel. It's going to learn bad things. Right? So.
Kelly Randis [00:12:55]:
Yeah.
Kelly Randis [00:12:55]:
Yep.
Kelly Randis [00:12:56]:
And it learns from people and people have biases and, you know, and they try not to impose, you would hope their biases on AI rate. But it's not perfect. It's not perfect technology.
Steve Swan [00:13:09]:
Now, what I wanted to get back to real quick was on the security side. AI has to learn, and AI's got to learn from data, a dataset. Nobody else is going to share their data with you because you've got to use your own data to train your AI, right? Because it's security, right? That's just the nature of the beast. So AI's got to sit and continue to learn from your data, right? That's coming into it from your systems and your universe, which could take time, right? Which also, it doesn't see a change up. It sees curveballs all day. So it doesn't learn how to hit that change up. You know what I mean?
Kelly Randis [00:13:45]:
Yeah, no, I know exactly what you mean. I agree. Right. Sometimes in some cases, there's not going to be enough or a large enough volume of data to train it quick enough to be valuable. I mean, and the final technology, I think that's really making a big difference everywhere. Chat GPT. And the new GPT is that are being built off of chat GPT. I use chat GPT, I would say at least daily.
Kelly Randis [00:14:11]:
And I've written a couple of, you know, just play around GPTs. I know my nephew, I was talking to him, he built a raspberry PI and was using a chat GPT that he wrote to help him troubleshoot his Raspberry PI. So I think that will go a long way.
Kelly Randis [00:14:27]:
Right.
Kelly Randis [00:14:27]:
Because I could use chat GPT right now to write my emails and send it out or to create a presentation with certain data. So I think if it's used correctly, you'll be able to use it to focus on the stuff that's not as important and free the individual up to focus on the things that really mean the most.
Kelly Randis [00:14:45]:
Right.
Kelly Randis [00:14:46]:
But there have to be some safeguards put in place there, too, because people could use that for all the wrong reasons as well. But that's one that I see up and coming. Something like chat GPT. Powering an AI virtual assistant, right, on a website could be a great experience for someone.
Steve Swan [00:15:05]:
Right now, isn't that where copilot's coming in for Microsoft?
Kelly Randis [00:15:08]:
Right, in that Microsoft's a little bit behind. I think Apple's even a little bit further behind when it comes to chat GPT. I think Google is one of the most advanced there. Microsoft will. Microsoft would probably buy somebody to catch up.
Steve Swan [00:15:23]:
Yeah.
Kelly Randis [00:15:25]:
And Apple just hired. Apple just bought a company.
Steve Swan [00:15:28]:
They did. I read about it.
Kelly Randis [00:15:30]:
Yeah. They just bought an AI company, so I think they'll catch up fast. But right now I would say that Google's a little bit ahead of the game. I've used their, well, I think theirs is called Bard, Bart.
Steve Swan [00:15:39]:
Yeah, Bard, yeah.
Kelly Randis [00:15:41]:
So I've used theirs. I like the native chat GPT. That's my favorite so far. Seems to give me the best answers.
Steve Swan [00:15:49]:
So you've used them all, is what you're saying, or views? Most of them I've tried, yeah.
Kelly Randis [00:15:53]:
Yeah.
Kelly Randis [00:15:53]:
And I do tend to land with chat GPT most of the time because.
Steve Swan [00:15:58]:
Of their answers, because the usage of it or what is it?
Kelly Randis [00:16:01]:
Yeah, because of their answers and because of the multiple uses. So I used chat GPT to help me troubleshoot a problem the other day. We put in the error message and just work through different things, which was great, but on a personal level, I had a picture I wanted to blow up, but whenever I tried to blow it up, shutterfly would say, it's going to be blurry.
Kelly Randis [00:16:20]:
Right.
Steve Swan [00:16:21]:
The resolution too low pixelated. Yeah, yeah.
Kelly Randis [00:16:24]:
So I uploaded it into chat GPT and I said, fix the resolution of this so I could blow it up to 16 by 20. So chat GPT fixed the resolution of the picture. I went out to shutterfly, I blew it up. It came out gorgeous. So there's so many uses for it that I'm just a huge fan.
Steve Swan [00:16:43]:
I would have never thought of that. I would have given up and walked away.
Kelly Randis [00:16:48]:
Well, it was my daughter's wedding picture. I really wanted it blown up, but for some reason the photographer didn't use high enough resolution, so I couldn't blow it up. But chat GPT fixed that for me, so that's awesome.
Steve Swan [00:17:02]:
Good.
Kelly Randis [00:17:03]:
I used it the other day to, you can use it to help build things. I asked it to help me build a Powershell script to do something. I told them what I was trying to do and it gave me the Powershell script. So it's a huge time saver when you're working on a bunch of stuff and you can't remember how to do something or you need a one line script real quick, you just throw it in there and then it's done.
Steve Swan [00:17:28]:
Well, I think a lot of the programming, eventually it's not there yet, but a lot of the programming is going to be done if it's not already being done by some of the AI.
Kelly Randis [00:17:37]:
Yeah, some of it will, and it's going to make it difficult for people doing interviews because chat GPT was used in past the Google interview. So.
Steve Swan [00:17:49]:
Really?
Kelly Randis [00:17:50]:
Yeah, there's a whole article about that. You can read about it. That chat, GPT actually passed the Google interview. So if you're interviewing someone, I don't, you know, unless you're sitting right in front of them, which doesn't happen that often anymore. You don't know.
Kelly Randis [00:18:07]:
Right.
Kelly Randis [00:18:08]:
You don't know. They may be over here typing. What are you doing?
Steve Swan [00:18:13]:
Hmm, interesting. Okay, so now, any other technologies. I mean, that. That is going to be groundbreaking. Right. AI for all of us. And that's. Yeah, that's the big one that everybody's talking about.
Steve Swan [00:18:22]:
Any other technologies you think we should cover that are affecting our industry?
Kelly Randis [00:18:26]:
I think right now, those are the three at the top of my list.
Kelly Randis [00:18:29]:
Right.
Kelly Randis [00:18:29]:
That I'm the most focused on. I think they have the biggest impact all around.
Steve Swan [00:18:35]:
Yeah, yeah, no, they're going to have a big impact. They're just going to get bigger. I mean, you know, my other guests in the past that I've had on the. On the podcast, you know, they see this as the beginning of when the Internet came in, you know, 19, this is 1990 all over again, you know, where one guy said, we're rubbing sticks together to create fire, and it's just going to keep going from here. Yeah. You know.
Kelly Randis [00:18:55]:
Yeah. It's gonna get. It's gonna get bigger and bigger. We're gonna need people who understand it, understand how to train.
Kelly Randis [00:19:02]:
Right.
Kelly Randis [00:19:03]:
Still needs some work because we have to figure out how to eliminate that bias.
Steve Swan [00:19:09]:
Yeah.
Kelly Randis [00:19:10]:
Right.
Kelly Randis [00:19:10]:
Because that.
Steve Swan [00:19:11]:
But how do you do that? Because it's learning from us.
Kelly Randis [00:19:14]:
Yeah. I'm not sure.
Kelly Randis [00:19:16]:
Right.
Kelly Randis [00:19:16]:
But I think that that's a problem that has to be solved. The only other thing I think is gonna impact all of us is blockchain.
Kelly Randis [00:19:23]:
Right.
Kelly Randis [00:19:23]:
I think. I think at some point, from a security standpoint, if you could, you know, keep your files behind your firewall, but access through the blockchain.
Kelly Randis [00:19:36]:
Right.
Kelly Randis [00:19:36]:
Because the contracts that people have sent in blockchain have been hacked. But the blockchain itself is not hackable. And I know there's a bunch of companies I know ey is out there and a bunch of that are trying to resolve the identity access portion of the blockchain.
Kelly Randis [00:19:55]:
Right.
Kelly Randis [00:19:56]:
Which is key for pharma. But if that can get resolved, I think that that's going to change the way infrastructure is designed because it's the most secure.
Kelly Randis [00:20:07]:
Right.
Kelly Randis [00:20:08]:
And when you're dealing with patient health information, people's personal records, I would want it on the blockchain before I put it anywhere else.
Steve Swan [00:20:18]:
Now, is it most secure because things get segmented out. I mean, why is it the most secure?
Kelly Randis [00:20:22]:
Well, because it's replicated everywhere.
Kelly Randis [00:20:25]:
Right.
Kelly Randis [00:20:25]:
So it's replicated all over and it's all encrypted. You can't really break the encryption. And even if you did, you would have to break it on every single block in the chain at the same exact time and make the same change in order for it to stay.
Kelly Randis [00:20:44]:
Right.
Kelly Randis [00:20:45]:
So if you do something and you affect the block on one or a little. A bit on one block, when it comes back around to replicate, it's going to go, nope, that's bad. And it's going to put the right thing over there. So unless you were somehow able to coordinate that on the hundreds of thousands of systems that make up the entire chain, you can't hack it.
Steve Swan [00:21:09]:
Right, right.
Kelly Randis [00:21:11]:
So. And there's ways to use that to keep your data internal to you, but put pieces out on the blockchain to allow other companies or organizations to use it.
Kelly Randis [00:21:28]:
Right. So right now.
Steve Swan [00:21:29]:
So, like permissioning, like a JSON almost. Right? Yeah, yeah, yeah.
Kelly Randis [00:21:32]:
So you see a lot of car t companies, right? All of the hospitals are running a portal, right, that they can register the patient and fill in the information for car T. So the hospitals, I'm sure, don't want to have 30 portals for all these different car ts, right, but if there was a pharmaceutical blockchain, right, that could be separated so that each company could do business on it, and all you would know is that, say gametocell did a transaction, but you wouldn't know what that transaction was. Right, because you couldn't read it. The hospitals would only need to go to one place.
Steve Swan [00:22:10]:
Right, right.
Kelly Randis [00:22:11]:
So overall, that would make it easier for them, even for the patients, right. Because then they could have a. In their wallet, they could have a key that would unlock their records for the hospital.
Kelly Randis [00:22:23]:
Right.
Kelly Randis [00:22:24]:
They would have all their records on the blockchain. So say you were in Florida and you got sick and had to go to a hospital there. You give them the key and they have all of your medical records because they're on the chain.
Kelly Randis [00:22:38]:
Right.
Kelly Randis [00:22:38]:
So they're the only ones that can see it because they have that key. But then you should own your key, and when you're done there, you can revoke that key and modify that key and take it away.
Kelly Randis [00:22:48]:
Right.
Steve Swan [00:22:49]:
So, so it's no longer.
Kelly Randis [00:22:50]:
I mean, this is. This is all fictional, right? This is just all the way I see it working. I don't know if anyone else sees it working that way, but, like, when I look at watching. I see these with these use cases for it, right, where we can. We can protect things and just make it easier.
Steve Swan [00:23:08]:
Well, yeah, because one of my guests at one point, we were, again, back to AI. He was. He was playing around with it one day and up popped information on a competitor. You know, we're talking formula, we're talking scientific data. Wow, that's like screenshots. No, he did some screenshots and got it over to the company and said, you guys got to address this, you know.
Kelly Randis [00:23:29]:
Yeah.
Steve Swan [00:23:30]:
I'm assuming they did. I don't really know.
Kelly Randis [00:23:32]:
I hope so.
Steve Swan [00:23:33]:
I hope so, too. I hope so, too. So anyway. All right, well, so we covered a lot there, and I appreciate it. Thank you very much. You know. Now, is there anything more you want to hit on? Because I don't. I don't want to.
Steve Swan [00:23:44]:
I don't want to take up the rest of your day because I know you're busy. I know.
Kelly Randis [00:23:47]:
You know, I'm good. I appreciate being here. Thanks for having me.
Steve Swan [00:23:51]:
I have one last question I always ask people right before they go, live music. I'm a live music guy. I don't know how you are with live music, but I was, like, asking folks their favorite live concert they ever saw. Band that they've ever. You strike me as somebody that would have seen one or two shows.
Kelly Randis [00:24:08]:
I've seen one or two, and my favorite one was Pink Floyd at Nassau.
Steve Swan [00:24:12]:
Really?
Kelly Randis [00:24:13]:
Coliseum. When Nassau Coliseum was still there. Yeah. Nice small venue, nice mellow crowd.
Steve Swan [00:24:20]:
My oldest brother who talks about a Nassau Coliseum pink Floyd show, I don't know what year it was. I have no idea. He's six years old than I am, so, you know, mine was in the.
Kelly Randis [00:24:29]:
It was probably the same one, Steve.
Steve Swan [00:24:32]:
Yeah, it was probably the seventies, right? Was it in the late seventies?
Kelly Randis [00:24:36]:
It was in the eighties.
Steve Swan [00:24:38]:
He graduated high school in. In 79 or 80. He could have come home. It might have been in the summer when he was home from school.
Kelly Randis [00:24:45]:
Yeah. Yeah.
Steve Swan [00:24:46]:
So he talked about how phenomenal that was. Like he had a real plane. A real plane came in and flew into the wall or something. He said, like, it was crazy. He said it was.
Kelly Randis [00:24:55]:
Yeah.
Kelly Randis [00:24:56]:
Then.
Kelly Randis [00:24:56]:
And the big pig that just floated throughout the entire stadium. Yeah, it was. It was awesome. Yep.
Steve Swan [00:25:01]:
Well, that. That's awesome. Gosh, I went and saw Roger. Roger Waters, right? Yeah. Roger Waters recently. And, you know, it's just him. So it was kind of. He took all the guitar out and stuff like that.
Steve Swan [00:25:11]:
So, anyway, it was. It was okay. I still would have rather seen the show you saw. Anyway, thank you very much. Great to have you on.
Kelly Randis [00:25:17]:
Yep. Thank you. I enjoyed it. Have a good day.
