[Music] Hi everyone and welcome to another episode of Tech Unhinged where your technology meets human. Today I’m thrilled to have with me Gabriel Flores a veteran in facilities engineering and automation with four decades of experience across semiconductor labs, data centers, research labs and pharmaceutical facilities. Over the years, Gabe has worked on critical infrastructure projects for industry leaders like Intel, Google, and the Los Alamos National Laboratory, helping design and optimize some of the most technically demanding environments in the world. He’s currently the director of technology engineering at Excite Americas, where he oversees automation systems for mission critical operations. Gabe, welcome to the show. Thank you, Rivian. Well, we’ll start off, you know, with your journey and our first question. Gabe, you’ve had an incredible journey across some of the most high techch environments in the world. How did you first get started in this field of facilities automation? What sparked your interest in it? Well, you know, uh, as you went through my background, uh, I’ve been in the business uh, almost 40 a little over 40 years now, I think, and 70 about 30 of those years in semiconductor. Uh, but I look back when I look back, I say, yeah, how did I get started? Um, I remember when I was a young teenager, uh, my father was a, uh, HVAC technician and he took me on the job one day and this was, you know, back in the 1960s. Took me to a project and he was working on an uh, an air conditioning unit and he opened it up and I saw all these wires and relays and components and I’m a teenager and I didn’t know much. I said, “Wow, look at that. Looks complicated. I want to learn how how to how they do that. How do they do that? This thing looks like it does controls and I’m a kid, you know. So, that interested me. Uh I went to college. Uh I got a degree in mechanical engineering and back then uh they didn’t have a discipline in controls. Okay, nowadays they do. You can go to college, you can get a degree in control systems, but back then they didn’t, you know. So because control systems were still on the mechanical side, you know, I started, you know, so I got through the mechanical engineering school and during that time in the 80s is when I saw my first personal computer. Okay. And I says, “Wow, look at this. This is called a computer and you could do things on this thing. you could, you know, uh, do word processing mostly and look things, you know, and it was mainly that’s what it used to be for is word processing some spreadsheets and things of that sort for a personal computer. So I was like, okay, this is kind of interesting. And then we used to use it for uh data entry into the mainframe computers. I went through college got interested on the on the computing side more, you know, the mechanical engineering side. So when I got out of college, you know, I started working for a controls uh company, a small controls company, and I started doing design work with uh on drafting paper. Okay? Because everything was on paper. Okay? So pencil and paper, triangles and tsques and the like. Okay? And so I I started doing that. Then this application started coming out, this software, this stuff called AutoCAD. Okay? And uh and then you know it’s this AutoCAD and you could draft things and you can put in electronically on the on a computer. So I started doing that and we had to convince our management this is going to be the future. This AutoCAD thing and this doing stuff on the computer is going to be the the future. And so you know uh I remember AutoCAD 1.0 O loading operating system, DOSS operating system with stacks of of discs and uh you know so I started uh uh learning how to you know about operating systems and and putting it on uh loading the system on the computer and it took it it took a you know 30 minutes to an hour to load uh an operating system. Okay. And then it took a big stack of floppy discs to to load uh AutoCAD. Okay. And it took you know uh minutes and minutes to to render a drawing on on the on the computer. It took a lot of time and you know and then it just started growing from there. And I I remember uh working on building a graphics by by pixel you know pixel by pixel building graphics for an automation system and uh and it was on operating system called CPM86. So it just and then the you could see the microprocessor speed started getting faster and faster and uh you needed that speed to do more graphics, more automation, more detail and and the speed you didn’t want to wait anymore because I used to go get a cup of coffee to wait for the for the drawing to rerender, you know, and to zoom in and zoom out. It took, you know, minutes and minutes and minutes, you know, to go do that. So you had to go get a cup of coffee and come back and see if your drawing was zoomed in or zoomed out. Okay? And uh so you can see the evolution there you know and uh all that was interesting me I it was so I was a mechanical engineer and I was learning you know more about computing systems and how to apply it. Uh and gosh, you know, today there are smart devices, you know, with microprocessors built in. You have the internet of things, uh, you know, artificial intelligence, you know, and all that was just, you know, this microprocessor, you know, and here’s my I worked at at Intel for a long time. And so there’s Yeah, that’s a microprocessor. Okay. And with all the the wires not attached, okay, obviously they package them, you know, there’s they attach it to the uh uh to the socket uh where you you know and then you load it you know bring the socket into a computer into a motherboard and so forth. But you know that’s that’s a microprocessor. So that’s one uh uh you know iteration and there’s another one a smaller one. And uh you know this is from the 19 uh the 1980s. Okay. And can you have it as your keychain? That’s my keychain. Yes, I still have it. Oh my god. I still have it. Yeah. So, you know, uh the evolution of automation and such and and people’s journey and how you know what how people interact and uh start using it and become efficient using it. It takes time. It takes years. It takes time for people to adjust. But, you know, that’s kind of my journey. Yeah. I I sort of believe uh Gabes that we can clearly say that you’re living your childhood dream. Yes. I think so. I I think I I made it I made it work and uh I enjoyed I’ve been enjoying it ever since. Yes. Yeah. Yeah. And not many of us can sort of say that but we have an example. Yeah. I mean uh from the very beginning you know from automation you know uh from microprocessor bas based automation because I used to do like you know mechanical they used to do uh automate stuff through uh uh hydraulics or through pneumatics then it became electronics you know then microprocessor based uh uh you know automation you know and uh and now it’s not just microprocessor based you know because uh you know a lot of the some of even the AI nowadays is using uh you know risk risk risk B type processors. So they’re not full-blown CPUs and uh they’re able to do microtasks and the microtasks and the micro the smaller risk processes they take less power and energy to operate. So you know which is a big deal nowadays is you know uh we’re finding is that things are consuming a lot of power you know so that’s a big problem. So um Gabes that sort of brings me to my next question. Given your um decades of experience, how has the meaning and role of semiconductor fabrication facilities evolved over the years? Right. Right. So back in the 80s, you know, like I said, we you know, we did a lot of uh control and automation using uh mechanical uh uh devices and uh electrical devices. You’re performing logic using electrical circuits and relays, you know, and of course, you know, that’s the whole deal with a semiconductor now is the relays are microscopics, right? They’re they’re they’re they’re you know, a relay a gate in in a microprocessor, you know, is is, you know, you have to use a microscope to see the gate. That’s how small they are. But back, you know, when they started, you know, there you’re using relay and you’re calling it relay logic. Okay, so that was the electrical side. And then you had mechanical mechanisms that did that. So you know that was some of the earlier uh control systems and I I remember doing a you know a scrubbed exhaust system uh you know on a semiconductor was one of my first projects uh to automate it and we’re you know we installed uh you know a programmable logic controller. Okay. And a programmable logic controller it was just that it performed logic and you know it kind of replaced the relays. So, you know, you kind of replaced an electrical relay circuitry and and logic of ones and zeros with a, you know, with a, you know, with a a programmable logic controller, you know, so that’s kind of how it started. And then, you know, we started adding some monitoring, you know, some analog devices that to be able to monitor equipment. And so, it it was used a lot for monitoring. But, uh, because a lot of the u, you know, people again, we’re going back to that uh issue with people and learning. Oh, you know, these this electronic stuff, you know, it’s uh was mysterious and it, you know, you could you would load logic in and it would perform this stuff, but I don’t trust it. The technicians and a lot of people, they didn’t they didn’t trust it. So, they wanted backup systems. So, we would design uh you know these these automated systems, but they wanted something they could touch, you know, turn a dial, you know, move something. They they still wanted that human interaction. Okay. And even today I think I was reading is that you know some of the cars uh one of the major car manufacturers still wants to have some ability to touch and turn things on their on a on a modern car because humans still have a need you know some desire to touch things. Okay. So you know so I think that’s that’s there’s some human nature there that we you know you have to to understand and try to compensate for is is what people you know how people react how they work how they envision how they perform work and how they see things how they see the world right how do they view the world um and so that’s a lot of part part of automation so getting back to the semiconductor uh you know so we were building automation system the programmable logic controllers and then we were putting in these extra control panels that were with some non knobs and dials and gauges or whatever just in case the the operator had to manually control the process cuz they just were says hey if I need to manually control this process I need to be able to do this cuz I don’t know if I fully trust this this microprocessorbased controller okay but you know it um so we kind of started looking at that and then the facilities get started getting more complicated the processes started getting more and more complicated they wanted us to build things faster you know they wanted less you people, you know, people they need to fix things quickly because there these facilities are getting huge. These semiconductor facilities are getting larger and larger and larger and larger and more complex and more complex. So, you know, the human you just can’t operate it anymore manually. You know, it just it just at a point where just you started getting rid of, you know, anything that was manually because it just got in the way. Okay? And we didn’t need more complications, you know, with any kind of manual operation. Uh so you know so we had to do that and you know they wanted to reduce labor so it was time to market get it done can’t interruptions to production you know but because these semiconductor facilities you know they they started getting really complex uh you know they’re nowadays they’re tens to 20 billion dollars to build a a semiconductor facility uh back when I started you know in some of the earlier semiconductor facilities we were only talking about a billion dollars maybe$2 billion dollars to build a facility Okay, now we’re talking tens of billions of to build a semiconductor facility and you know so they started getting bigger and bigger and more complex. Uh you know the semiconductor uh facility they use dozens and dozens of of of specialty gases and chemicals. Uh some of these things are some of these gases are quite exotic. Uh they’re quite exotic. Some are quite dangerous. You know they’re they’re quite you know flammable. They’re they’re toxic. there and and you know that they use in the process for uh etching and and uh you know out these semiconductor wafers you know the material science is getting more exotic more complex okay u you know and we’re seeing that you know that the technology just leaps and bounds changing uh to get you know faster smaller and using less electrical power and less energy you know cuz like a semiconductor facility they can use over 600 megawws of power over 600 100 megawws. Uh, you know, some of these data centers, you know, they’re like 30 megawatts for like they call a hall, you know, of of for a data center hall. And they might have multiple halls on a on a data center campus. So uh you know this huge amounts of electrical power huge amounts of cooling okay like a semiconductor 100 150 to 200 tons of cooling uh because just to cool down because you’re putting in all this electrical power putting all this you know chemistries in and uh it’s there’s a lot of energy that is used um to to produce you know these little micro processors. Okay. It’s it’s huge. Was this one of the processors that you sort of um built yourself? Yeah, that was always in the facility, you know, was the reason it’s on my keychain, okay, is because it didn’t pass inspection, okay, the yield, it was it probably had a flaw and it was probably a reject. You know, you can’t be losing uh revenue by by, you know, you’re not making money on keychains, okay? And that’s where the automation is, you know, it has to be reliable. Uh, you know, uh, is, you know, because the cost to produce these things is is enormous. Interruptions to production is very costly. It it it’s in the millions of dollars per day, you know, if there’s downtime cuz these these facilities, they run 24 by7. They do not shut them down. There’s people working these things 24 by7 all year round. And so the systems have to be you know automated such that you know you can afford to do things while everything keeps running right you got to be able to make changes. Uh so there’s you know hot standby you know uh programmable automation controllers the SCADA systems are hot standby you know so they’re looking they want you to design you know our systems to be designed for 99.9% uptime. Okay, the meanantime between failures of components that we use, we measure them in years, multiple years. The mean time between failure for a component. So the reliability uh you know needs to be you know has to have really high reliability there. They can’t have they can’t afford an interruption to production because it is very costly. Okay, these facilities are huge and uh uh you know with with you know thousands of people operating them um and all the instrumentation that goes into these things you know thousands and thousands of IO points that go into uh you know operating these facilities and controls. So you know that’s that’s a semiconductor facility. Yeah. So Gabes you know for for our listeners who haven’t been sort of you know aware of this term which we’re going to be using a lot semiconductor fabrication facilities right if you could sort of quickly you know give me one two liners where you could explain the direct connection of semiconductor fab facilities with where technology is today right if you could just sort of put it in simple terms by making a connection here right well you know since You know the invention of the semiconductor uh you know it was to perform logic right and you know to assist humans right and getting you know making calculations quickly okay speed and and efficiently. So that micro they’ve been working on that you know the the 1940s and 50s and and then the 60s and you just see the advance this desire to perform calculations and then uh we started learning how to the humans started using the computer to just do simple uh word processing and and then uh you know writing software that does things then the internet came along right I remember when the internet came along that was fascinating you know is the internet wow I remember I had a you know people working in here in in my hometown and and we were building a facility in Europe and uh we could send them a message you know on the internet okay and we were able to send a message and then they called it later on they started calling it email you know you know and uh so then you know that’s then communications right so now it’s not just calculations anymore and it’s not just for you know controlling equipment now we’re using it for communications right so now this communication started coming along, you know, the the with the internet, people the writing emails, sending a photograph, uh, you know, um, watching starting to watch, you know, stuff on the internet, looking at and reading and then all, you know, it just started all the communication really started moving along and people could see, you know, because what people, you know, really like is is that, you know, people are addicted to communications and information, right? People, you know, are addicted to communications. They’re addicted to videos and and interaction. Humans still have that strong desire for interaction. So, we’re using it now for, you know, a lot of that is is to process, you know, just human communications. And the micro the semiconductor and that’s all from, you know, semiconductors, okay? Is processing information. It’s still about you know ones and zeros you know until uh you know um other kinds of communication comes along and computing uh you know like quantum computing and such that comes along you know that’s still uh you know a need and you know so the is is they’re getting smaller is you know we looked at the microprocessor here’s a larger one right here’s the one in the backside the one in the middle is a smaller and they’re getting smaller right because you want to be able to put that intelligence in everything that you can imagine you want to put intelligence into it and make it intelligent that device you know people you know wear watches or all these smart devices that you can start using now because you can make them very smaller and they’re wanting to make them smaller and smaller and using less power you know so again it’s the consumption of power still an issue is how do we power these these devices so we can we can sort of you know um reduce the size but we are not replacing the these anytime soon. No, no, I I think not. I think, you know, there’s there’s still thought is, you know, it’s still digital. Okay. Uh there are people doing research on analog, you know, analog computing because that’s nature works that way. And you’ll see some experiments, people doing experimentation, uh trying to mimic, you know, how nature operates. You know, how does an ant wander around and can carry, you know, a 100 times weight, right? A little little ant, you know, and it can carry the rock. They they’re carrying a rock around, you know, a little to them it’s a huge boulder, you know, we would think in in relation to ourselves it’s like a human carrying this big huge boulder around, you know, effort, you know, where did they get the energy to do that? You know, where did they get the energy? Where did they get the the intelligence? You know, what level of intelligence are they using to do some of that work? uh and uh to do the things they do uh whether it’s an ant or a bee or some other more you know uh as you go up the the chain there of intelligence of different animals and they’re you know they’re they’re using some form of uh reasoning and computing somehow okay uh so there’s research in that area I know uh maybe something will come along in years to come is how do they do that you know because they’re using very little energy you know they’re just using what’s available the sun or some other forms heat from the earth or what have you to provide energy to to perform these tasks um you know so I think that’s still a mystery to us is how that you know they’re able to do that and maybe one of these days humans will figure it out yeah so I sort of believe that you know in sci-fi um cinema that you know a lot of genz or millennials consume these days now they would show you the small chip which could be just literally added to your you know inside human body. So are those chips also the product of these um semiconductor facilities? Absolutely. Absolutely. I thought about that is that you know and um and I say thinking of what I would I allow that you know to put you know because I’m I I what frustrates me today is this the security it just drives me nuts you know is uh you know I have so many accounts and so many passwords and they’re changing and you know some softwares you try to use a you know a common key and sometimes it works sometimes it doesn’t it’s just so frustrating you know and I gosh would I embed something in you know that’s uh uh that would that would recognize my security that you know and authenticate me you know somehow you know and uh just so that I wouldn’t have to put up that you know uh you know that annoyance of all this security and and and passwords and accounts and things like that and I’m going god you know it’s available today you can do that but is are humans ready to do that you know I think a lot of people say ah no way I’m not going to do that uh you know and uh you there then there’s going to be people like myself I’m an early adopter type person right I’ll try things okay you know because you know being an engineer you you kind of want to you know experiment and things where see how they go and uh and it’s a learning process and uh you know just like I say it took decades to learn how to use a computer and become efficient where the computer was actually making a real good tool not just a a toy or an a curiosity and yeah you know no I mean today I mean nobody will leave their house without this computer. Yeah. No, no way that’s happening. Yeah. People sleep with it by their bed, under their pillow. I mean, it just I mean, it is a way of life. You can’t do without it. And it’s a great tool, you know, but but it’s taken year decade, you know, where people it’s like, “Oh, no, no. I I I don’t use a computer. Oh, no, no, I don’t want this and this and that.” To to today, like you say, it’s where you’re sleeping with it under your pillow, okay? Because you can’t do without it. But it’s taken decades to get there. It’s taken decades, you know, to so to make other advances. It just doesn’t happen, you know. Some things just doesn’t happen overnight, especially when it takes human uh you know, adoption, you know, uh to be able to change and do something different like putting maybe something in your body like a like a microchip, you know. Uh but people are putting pacemakers in there and they’re they’re putting in other devices in their bodies, you know, to make you live longer and make you function better. Before we delve further, um, Gabes, uh, automating facilities as intricate as semiconductor fabs is definitely not easy since you know how we discussed it at less. What are some of the biggest challenges you faced in deploying automation across critical infrastructure, right? And I kind of talked about, you know, uh, right, I was talking about early on, you know, we were doing stuff on paper and you’re putting in software using floppy discs and you’re convincing the management that this is going to be the future. This is how everybody’s going to do things and computer coming along. It’s all about convincing other people, especially decision makers and people with money, right, that they’re going to invest in this whatever this these this new idea is, this new equipment, this new smart device, you know, that oh, I can I can automate this stuff where you a human doesn’t need really touch it much anymore and oh, I don’t know if I can do that, you know, and so a lot of it is about uh making changes and and I talked about the expense and the complexity of a semiconductor facility. So change is, you know, is is is is tough for people to handle, especially people that are trying to produce consistent yields, right? You know, consistent results, predictive, you know, results and consistent product yield, you know, because their bottom line is they got to make money. So you’re going to make a change that could upset this process, right? You know, I’m making money today. So, um, you know, how are you going to, you know, how are you going to save me money, more money? So they have like an semiconductor uh you know a lot of the major manufacturers and and not just semiconductor a lot of companies nowadays that are because they’re automating and it’s not just semiconductor uh so it’s it’s it’s it’s what they call their copy exact philosophy right so they might have this this philosophy that like say you you know you repeat repeat repeat okay so that you have and you want to be exact so that any kind of change if I’m going to make that change I got to make it to everything okay so I can get consistent predictive results and so uh some of the challenges in making these changes is is what they call you know some of these they call the white paper process you have to write a white paper okay I have to prove to somebody you know a team generally a council or a board or something like that that that this change that I’m I’m proposing uh it has you know it has a return on investment okay it has a justification why do I want to do this it has a a return on investment uh it has an implementation strategy as how am I going to go implement this in a in this complicated facility um and you know what are the potential risks to production nobody wants to hear that but you know what what’s the potential of risk what’s the probability of failure you know what what is the probability of failure that I might have and so I I have to work all these details out okay go present it to a board and you know go collect some more data for me I want more data I want more data show me some more data you know is Why do I want to do this? And so, you know, the a lot of them turn on investments on some of these uh on industrial, it’s got to be like less than a year, you know, two years, three years. Yeah. They’re they’re not overly interested in two, three year paybacks, you know, because technologies are already changing within two, three years. Technologies are already changing. So, it has to have a pretty quick payback. Okay? So, whatever I’m doing for automation has to have a pretty good payback. I don’t want any risk to production. I don’t want any risk production. So how are we going to prove this out? So now I need also too is I got to be able to implement this this uh this idea and maybe on a pilot project. I have to have a pilot project, a test facility and so where I can manipulate this process and test things out maybe, you know, create some failures or simulations that simulate particular failures and such. And that’s hard to do. That’s hard to do. Where do I do that at? What facility? Who’s going to give me a facility to try this out on? Okay. One thing that has happened over the last year uh to two years is the US government uh they established this uh national center for advancement of semiconductors. Okay. They call it uh the natcast.org. or and it is uh an effort to assist semiconductor manufacturers uh and companies develop new technologies so that they have a factory you know and process they can try to test things out and simulate in a test environment that’s not going to impact production. Okay. Um so that’s something they’re trying out. Uh you know some of these companies there’s semi.org is another organization called semi.org or uh that helps you try things out and and test things that uh in different parts because this the semiconductor supply chain is is massive from you know all these exotic chemicals gases and the material science and all these things that uh you know these these tools that they run in manufacturing are the multi-millions of dollars each tool and I have thousands of these tools in a factory that’s why they cost billions of dollars you know so each of these tools you know they’re quite elaborate uh you know so testing and such is is is difficult. So you have to go test this collect data and uh so that you can uh have a compelling argument and and and a white paper to you know that that justifies this change. So you know that that’s I tell a lot of people I’m I’m not that smart. Okay? I I never thought myself I I’m not very smart. I know a lot of people are a lot smarter than me. But you have to be persistent. You have to be persistent and uh you got to be able to address uh concerns by your your peers, you know, uh that need to support you in making some kind of change. You got to you got to be able to close all their concerns, you know, to their satisfaction that you’ve addressed them regardless of how, you know, uh minuscule you might think they are or ah that’s that’s not worth, you know, don’t worry about that. Oh, it’s not that’s not going to happen or oh that’s a silly question. You know, that’s a silly you gota you got to gain cooperation. And so a lot of it your you know a lot of your work in that is just really dealing with people and trying to get them to come along with you uh and u agree with your and support you. Uh that’s a huge part of your job. It’s a huge part of your job regardless of what you you’re right or wrong or you know people do this because this is this is flawless. this is great technology, we ought to do it. It’s just it’s not that easy. You’re always convincing people. I was eventually going to come to um the question where I was going to ask you given that you’ve had both uh the wins and the rejections, you know, uh with the white papers and the approval processes. So, you know, given that you worked at large or ors like Google and Intel. So you know you you you must have had learned a lot of key lessons while navigating through the approval process. So while you were living in that time um except persistence, what other things helped you sort of get through that and then eventually you know um climb up your career ladder? Yeah. you know, um, like I said, you know, I’m kind of persistent sometimes, you know, so I, you know, I would come up with an idea and, you know, for automation, I says, “Oh gosh, I got to write a white paper.” And, you know, it’s funny is that, um, in the industry a lot of times that, uh, if you want to discourage somebody, okay, they’re, oh, they’re, you know, maybe they’re not, they don’t want to support you on this or they’re giving you a hard, you know, they want to make this change. Oh, this I don’t like this. Well, what I think you need to write a white paper and that’s like it’s like telling somebody, you know, uh I don’t know what’s it. It was like a real evil thing, you know. Oh, no, no, no, no, no. Not the white paper. I won’t do it. Won’t do it. All right. And there’s a lot of people just won’t do it. And I think a lot of it is because they’re it’s intimidating. Uh you know, it it’s I don’t know if you watch the movie the the Wizard of Oz, right? And Dorothy goes to the Wizard of Oz, right? and the the flames and the smoke, you know, so and she says, you know, and she they’re shaking. It’s like, oh my gosh, you know, we got to go see the Wizard of Oz. And it’s scary because, you know, you’re going before a board of of intelligent people. They’re asking you tough questions and uh you know, not just technical questions, but you know, a lot about implementation and uh you know, uh uh risk, you know, uh risk to production and and and a lot of them is about the people factor, right? is how you going to how are you going to implement this? How are you going to install it? How are you going to construct it? How are you going to do this? How are you going to do that? And you know, it is a lot of it is a lot. It’s very intimidating at times. So, you have to you know uh like I say is is you know just work through those issues. Uh you can’t take it personal. A lot of people they just they take it personal. They don’t want be seen that they failed right and uh they don’t like to be put on the spot you know. Okay. I I don’t have an answer for that but I will get back to you. you know, some people have a hard time with that, you know, and u so it’s a lot of the so you end up dealing more with human dynamics, you know, a lot of what you end up working with really is with human dynamics and I remember in college I I had all my credits and I thought I had all my credits together to graduate and I go to my my uh my adviser whatever and he says I’m ready to graduate because and oh no no he says you’re missing uh you know you’re missing a social science you’re missing a what do you mean well I took I got, you know, all these credits. I took extra, you know, into my further education. I got all these other stuff, but they’re all technical, he says. And uh you don’t have anything in the social sciences. You need to take something in the social sciences. We want you to be a well-rounded person. I didn’t understand that as a 20-year-old. I didn’t understand that, you know, uh when I was in my 20s. I just didn’t comprehend that, you know, until years later. and and you realize that you spend a lot of your time just working with, you know, it’s you it’s it’s uh and it doesn’t matter what uh industry you’re in. Uh you’re always working and with people and trying to either convince them, you know, that to do something or trying to get them to do something for you. Um you know, to work with you and cooperate, right? It’s, you know, trying to get gain cooperation. So, you know, a lot of the skills is not, you know, is is is is the engineering. It’s it’s really about gaining cooperation from people. Yep. Okay. And getting them to buy in to what you’re doing and to agree to what you’re doing and to support you. Okay. You know, uh you know, supporting your idea, you know, giving you money and funding, there’s all these different aspects of of support you need along the way to make something happen. Okay? M from tech from the technician in the field, you know, that’s doing something with his hands and installing it for you, you know, to to to the procurement people to finance to the management people that are going to give you support of labor, you know, to go do something because you I need labor to do something. So, it’s all about, you know, again, getting people to cooperate and and and and support you and then uh and buy into your idea. I mean one has got to know how to be people smart because ultimately the technology out there is making impacts and people are ultimately going to be using them right. So you know since AI is all the talk in the technology world now we see its um visible intersection with automation in very interesting ways. So while your focus has been on infrastructure rather than the um you know manufacturing execution system side have you observed any use of AI or advanced analytics enhancing um you know how the facilities are monitored or managed in today’s time well you know it’s interesting is artificial intelligence right AI artificial intelligence well a lot of automation is artificial intelligence right we’re using you know these microprocessor based controllers to do perform tasks for humans. Right? So it’s already we’ve been kind of in the automation industry at least in the automation industry we’ve been working with a form of artificial intelligence for you know many many years. Um you know but one of the things that uh you know you know what we’re seeing with the modern day artificial intelligence is you know the different the different ability to reason. Okay. And it’s um you know and and to form in some cases it can be considered opinions but it’s reasoning uh you know and it’s collecting a lot of data right so over the years you know we got all these control systems but one of the issues that they’ve always had trouble with is dealing with so much data in these huge facilities right 20 billion dollar facilities with thousands and thousands of IO you know IO devices out there all that data is coming in right and I can get uh you know on my computer systems. I can look at a trend log, you know, every taken every millisecond or every second, every 5 seconds, every 15 minutes, every hour and and plot it out, you know, over time. And look at all this data. Boy, that is it is a lot of work to try to analyze that data. Okay, it’s just so much data, you know, and that’s where the term big data came from. Well, okay, I got all these devices and I got all this data, but it’s information overload. It’s information overload. So then you ended up with inter information overload where where technicians started to ignore things, you know, and uh so why did you ignore this alarm? Oh, you know, you know, my pager, my you know, or my phone is just going off. It just beep beep beep beep and they just can’t, you know, it’s just information overload. So the, you know, so there’s been programs to try to reduce alarms, you know, to classify them to what’s important, what’s not important. Well, how do you figure that out? How does a human after a while you know uh make that determination okay as a technician now is that you know I didn’t design the system you know I was just I was trained to do a particular task but you know I don’t know how this all works and it was all put together okay well that’s where you know you know I can see some artificial intelligence you know where um you know I don’t want to go through a you know some sequence of operation document and read and read and read and read and I’m not in the field I just need to to know what I need to do to fix this thing. Okay, that’s where like you know maybe an AI assistant can you know read through the data you know well you know according to the trend logs of all this data it looks like you’ve had an upset every night at uh 1:00 in the morning and or something along that line and based on the sequence of operation you know these are your possible solutions okay that it could be possible errors that might be in the system okay well that might give me an idea of where to go look right all right because again we want to do this management wants it and done now. They want it fixed now. Okay? When it’s not fixed now, the next day is why aren’t you done? Why aren’t you done? You know what help do you need? You just tell me. I’ll give you help. I don’t know what else help you can give me because putting more people on the job. Humans, you know, just going to get in the way or you know, I I just need to analyze and I need time just to focus on this problem. And that’s, you know, I think that’s where, you know, an assistant, you know, I can see where, you know, they can analyze lots of data and try to assemble that and and consolidate it into something that I can go and narrow down and go look at without having to go through reading, you know, sequence of operations, operating manuals for a piece of equipment. Then all this IO that’s coming into the system from the automation, all this data that I had to go put graphs together and stuff like that to try to analyze it. Um you know those are that’s kind of uh that’s where you know artificial intelligence would be good at uh you know is those repetitive tasks that take a lot of data and well that’s that’s good at you know artificial intell you know I see that happening um you know so we start developing you know these these AI you know bots and co-pilots whatever to help us you know review logic review you know code issues or review you know I don’t know if you’ve ever read a code book, you know, the NFPA or, you know, the code books, you know, the international building code or what have you. Oh my gosh, you know, uh to go find something. This is a huge amount of time just reading and reading and reading and jumps reference to this, reference to that and you know and then and then you still have to use judgment, you know, to put all these pieces together to come up with a judgment, an engineering judgment, you know, and they already have certain some of that’s coming along. it is coming along is is is to providing assistance you know and that’s those are artificial intelligence assistants that are collecting you know on a subject that can try to assemble and shorten down this information into a smaller something that I can as a human easily you know absorb faster you know so without having to go dig for all this kind of stuff so you know there’s certainly opportunity to do that and and that I think make us you know move faster and and then again it’s just our our our our technology curve is just getting you know going to get faster and faster to make changes, you know, because we’ll be able to get data and analyze data faster, right? Yeah. And so just I think it will just accelerate things how fast things you kind of you sort of referred that how you know these things could probably happen, you know, given the idea of automation. Do you believe that they’re not currently happening within those facilities? No, I don’t think so. And uh again is when I was talking about the change, right, is challenges. It’s it’s a change, right? So somebody has to, you know, to build these these co-pilots and teach them, right? You have to teach an AI artificial assistant, right? Intelligent assistant, you got to teach it something, right? And uh and so where is it going to get the data from? So somebody has to, you know, there’s a lot of labor in collecting what you’re going to teach this assistant, right? Where is it going to get where is this it its source of information? Is your source of information in the right format that it can dissolve and understand? you know some of this information hasn’t been digitized in a digital format maybe you know so there’s a lot of work just to teach an assistant it just doesn’t happen you know I have all this data even electronically you know uh data that’s collected over supervis SCA system supervising control and data acquisition system again is it can I give that data to an assistant does it have the security to to grab this data you know how do I manage security because I just don’t want any you know artificial intg device collecting and seeing my data because some of that’s proprietary, some of that’s proprietary. I I you know, uh I can’t just be giving that data out. So, there’s a lot of complications, you know, uh yes, it can do that, but uh it’s that implementation, the risk reduction, you know, like say, you know, risk to to to proprietary data, you know, that you don’t want people, you don’t want to share, you know, you don’t want to share that information with your competitors, you know. So um you know there’s those type of complications. So you know it’s it’s it’s uh and all this has to be solved before somebody says okay just turn an AI assistant co-pilot loose on my facility you know no it’s back to that white paper thing. You got to prove to me that you know all these things you know it’s safe that it’s going to be I’m going to get a return on investment. You know how much is it going to cost me? you know, is my production cycle because you know, you know, there’s production cycles for every company whether semiconductor or what have you. You know, you know, they’re producing something and then at some point you got to stop reinventing the wheel and and trying to improve it. It may not be 100%. I got to I got to make money on this thing. I got to get it out the door. I got to sell it, you know, because if I don’t start selling it today, my competitor is going to start selling his, you know, and you know, I got to get to the market first. I got to get to the market first. So, you know, those are the are are significant challenges, you know, to to you know, you got to move fast. It’s might be a good idea, but maybe not but not today. Might have to wait till the next production cycle, you know, before we can maybe implement something. Yeah. Well, see, G that that sort of makes me, you know, um more curious given that how we see the advancement of AI on on the daily basis, right? Right. um you know listening you would still feels like that the big orgs you know who are the stakeholders or at the core of making the semiconductors they are still having a hard time juggling their tasks or the employee labor work to something that we call artificial intelligence today. It might be at the core of it in the old school way but the new wave has yet to come just like as you mentioned probably you know in the next production that could entirely be a new era for that matter. So what I’m trying to understand is that is it still just an idea for them rather than something that they should actually start using within their work and it’s still going to take them time. Yes. because I think you know like you like you said is it’s it’s kind of a buzzword today and uh a lot of uh you know uh management uh people are wanting they they they realize they got to do something and I think you know people have learned that you got to adapt adopt technology right I think we’ve learned that and um you know uh and then some of this stuff it sells buzzwords they they do sell they have market value right it’s a you know becomes a brand after a while right and brands sell they they know they need to do that but I think right now we’re having a lot we’re seeing that it’s finding the use cases right you know in theory it sounds cool but like I said earlier is that what level of effort is it going to take to implement it and is it am I going to get a return on investment you know so that’s the bottom line and I think so we’re still struggling with that and of course I’d like to is you know I would like to buy something off the shelf you know I don’t want to be the guinea pig I don’t want to you know to go through all the you know the growing pains and and the implementation pains and and everything else and then uh you know uh I pay I pay for that. I would rather have somebody else pay for that and then then I just adopt it you know. Yeah. And and just use it. Uh you know I think people would like that more than being the you know uh being the person that’s trying to figure it all out. Given Gabes that you have been at the you know at the core of when the semiconductors were taking place or when the technology and computers was were taking their place in the world. So given that you’ve seen every phase through and through and you’ve been at the core of it does the next evolution in the technology excite you or does it scare you? No it does. I I’m an engineer. Yeah, change excites me. I like change. Yeah, I wish, you know, I just wish it just doesn’t happen fast enough for me. So, I do like change, you know, and yes, I am excited about that. And you know, I am concerned about a lot of times with change that uh you know, it’s the people factor, right? Is what people are going to are willing to adopt, you know, you know, or not not want to adopt and and how are they going to use it. Okay. Yeah. And how are they going to use it? And because there’s a lot of, you know, we talk about all the good things, you know, that can come out of it. But again, you know, just just like, you know, this tool right here. It’s a really good thing, but it can be a really bad thing. Absolutely. Right. You know, we’re struggling right now, you know, with is is that, you know, there’s the misuse of it, you know, and uh that is creating other social problems, you know. So along with technology you know I think there’s going to be the human factor you know that I that’s the part maybe I’m more concerned about is how are humans are going to adopt it okay and there’s going to be the you know we all think about the good things and there’s the people you can hear a lot about you know uh the bad things oh that they’re going to it’s going to take over and and you can’t trust the AI because it can you know be manipulated to making bad decisions or bad recommendations for you and this and that. Yeah, those those all can be true. Again, those are, you know, things that we’re going to have to deal with and and and to be able to manage to qualify, you know, I have to, you know, to maintain my my PE license, you know, professional engineer and I’ve got to on a regular basis on a regular cadence, I have to uh maintain myation level, you know, I got to be continuously, you know, uh refreshing either refreshing myself or learning new technology so that I am current in the world. Okay, that and then that my judgment is still going to maintain my judgment, my level of judgment that I’m going to be qualified to make decisions on older things that I’m probably, you know, used to, but also on newer things that are coming along. Uh, I got to be able to make a good engineering judgment and I, you know, and that’s like reertification. And so I see you know where artificial intelligence you know where the certification you know that it needs just like a like a human that you probably have to reertify it on a regular basis that AI assistant is giving consistent you know and and predictable answers that are based on on good data that is based on good data okay that it’s been what it’s learning where it’s learning its information from okay just like a human where where you how are you teaching this thing you’re just like your kids you know they learn they learn from their adults right and they learn from what they see and hear and what have you. So that’s where humans learn. That’s how we learn. We can learn bad things. Humans can learn really bad things. Yeah, that is that is sort of exactly, you know, where our conversation is headed. Now being humans, we are constantly um you know, worrisome about the impact of the value addition that we do within this world. So you know, you did touch upon the idea of certain dangerous gases, right? and a lot of energy or heat being consumed. So when we talk about the idea of sustainability within semiconductor fab and data centers. So you know how do you see um automation in helping to reduce this particular energy consumption? Automation is all about making you know processes more efficient uh taking a lot of the you know the repetitive labor away from humans and you know sustainability like I was talking about you know the these dangerous gases well what goes into like a semiconductor facility what goes in got to come out and it comes out in waste it comes out in waste it comes out on waste water or it goes out the stacks and so whether it’s going out the exhaust stacks or it’s going out the water waste streams they have to be treated you know, we just don’t dump into the atmosphere these nasty chemicals and gases. You know, they can’t get them into the water supply. We don’t want to be breathing on them. There’s our neighbors, you know, to the semiconductor facilities, the neighbors, they don’t want to smell this stuff. They don’t want to see stuff coming out the stack. They don’t want to see that. They like, “Oh, I don’t like that. Whatever is coming out of there, I don’t I don’t like that. I bet you that’s bad for my health.” Okay. You know, the next concern is, God, we’re going to build all these data centers for this AI energy they’re going to use. The amount of energy, whether it’s electrical power, you know, a semiconductor facility uses millions of gallons of water per day. Millions of gallons. Not just a couple, millions of gallons of water. It’s not just dirty water off the lake or the nearest river. No, this is clean. ultra ultra clean purified water. So clean you know that that there’s no particles in it and you know so again what that goes in has got to come out it’s got to be treated. The automation systems the more efficient they can do this because you know the treatment of these systems takes other chemicals. Okay, it’s either other chemicals or energy like some of the exhaust, you know, treating us takes we we use high heat, you know, so we’re using say natural gas or electrical power to really heat and burn these gases, these nasty chemicals, burn the heck out of them. So before they’re released, they precipitate out of them other chemicals that got to be, you know, disposed of. So the less energy or the less chemicals that we can use to treat these systems okay the better it is for the environment it’s less cost you know to treat these system because it comes to the bottom line of production cost all right and you know the impact on the environment and sustainability automation system I mean you just you know you need again in order to treat something as a chemist oh yeah as a human I can go take a sample of maybe say it’s water waste water and I go and I analyze it and this and that. Okay, we’ll just put a little more of that or put a little you can put a little bit of less or maybe we’re not putting it at the right amount of time, you know, because, you know, maybe the stream is not steady. Maybe it comes in floods, it comes in waves of of water or what have you. So, you don’t want it, you know, you need to be treating it at the right time in the process, you know, with the right amount of chemicals. So if I can reduce that because my automation systems are evaluating not only doing you know simple P proportion integral derivative feedback control systems but it’s not just that it’s you know some of that might be more predictive and to be more predictive you got to have data and and who’s going to analyze the data something’s got to analyze the data okay and we’re back again to analyzing data and that’s where I think automation systems and uh even later you know as artificial intelligence will come along and to help us be more predictive and preventive than than reactive controls automation. Yes, you can do re you know reactive automation but it’s better for the environment better for the money bottom line if you can be more predictive. Gabes, you also serve as a board member at the new Mexico board of lenture for professional engineers which sort of puts you at the center of shaping engineering standards there. How does your role there influence the development of engineering standards particularly you know around critical infrastructure right right yeah so uh the board of engineers so we’re our mission is to is basically to pro protect the public is protect the public you know so that we have safe systems out there that are being built people are talked about the u reertification process right uh making sure people are qualified to do this type of work and that we have some kind of process to maintain their certification ation just like we’re talking about artificial intelligence. I think that’s going to happen. You know, you need to have the same maintain your level of proficiency. That is our mission. So, not only with my board with the state of New Mexico, but I’m also, you know, with the NCES uh which is a national organization in the US. So one of our responsibilities is to maintain consistency how we’re applying um standards requirements uh you know for the engineering discipline across uh the US and even with how people you know and other because it’s a world economy as well now so we’re trying to understand is how do we deal with you know engineering and products coming in and out of the country because it’s a world economy you know so you know what are other countries doing to certify their professionals adopt to their processes or they talk to ours and understand you know again in a world economy so we’re dealing with that and again is we got to deal with the the new technologies like artificial intelligence right is that it’s how is it being used in the profession of engineering I don’t want to you don’t want to just say well you know I I designed something with you without really reviewing it and it was all done by AI good to go okay again I think there’s that’s where the human comes in is that a human has this ability to analyze things sometimes you don’t nec necessarily need all the data, but based on maybe my experience and how I view the world and how I understand how the world works that maybe that response or that solution from AI is not I don’t agree with it. Okay. I think I want I want to check where it got its data from. Uh so there’s going to be times that you know as a professional engineer just like he does with any other software. I mean we have software that perform calculations for us and and such and if it doesn’t look right they call it the smell test, right? There’s also people do that too is if it doesn’t pass your smell test, then maybe you ought to take a a second look at it. Those are the abilities that that humans have, right? We have this intuition. We have these experiences, you know, and we have this ability to to talk to other people and socialize and u maybe go ask the right person. I’m not really sure about this. Maybe go, but I think I know somebody that knows somebody, you know, and uh we can probably, you know, we can do that. And we need to be able to to question data, right? So a professional engineer, you know, we still have need that ability to question the data. Okay? And if it doesn’t smell right, doesn’t look right, then I think we need to go look and you know, and check say where AI is getting its answers for or my other software that I’m using, uh, you know, because sometimes, you know, as I say, garbage in, garbage out. Board of Engineering and the National Council of Engineering Surveyors is that that is part of our responsibility is to to to help develop those standards and the expectations for engineers. Okay. Their code of conduct, their ethics, you know, is is that’s the other is like ethics, you know, where does AI come in, you know, with ethics because is ethic is a very sensitive thing. Sometimes it’s not real clear. Sometimes it’s kind of gray. Yeah, it can be kind of gray. But ethics sometimes is based on on people’s their either their religion their their belief how they view the world but might be ethical here may not be ethical somewhere else that’s something that humans you know is that uh not we have to teach ourselves can you imagine an AI how how do you give rules to an AI assistant when when my rules or my basis may be different from yours y you know my view of the world and your view of the world is a little different probably and you might not see the same thing the same way I do but I need to understand that I probably need to educate myself. I need to probably educate myself. I I’m lacking some education. So those are all uh issues that I think uh as professional engineers and you know uh we all have to deal with and try to understand and try to make a better world. Yeah. So Gibbs, what advice would you give to you know young engineers who are today entering this particular field you know of engineering both in terms of mindset and skills. Yeah. Well, you know, you come out of the school as a young engineer and think you’re going to change the world all at once. Okay. Yeah. For some reason, you got to convince people because a lot of times you may not have the money. Maybe some people do, but you know, a lot of us don’t have the money, you know. So, you need funding and you got to be patient. You know we talked about changing things what it takes to make change because a lot of times like say you want to come in oh I got ideas I’ve got ideas but uh it’s convincing other people uh collecting the data being persistent and using the tools you know that that are available and to you you know and using all the tools not just technical tools but improving your skill set and your knowledge of people and uh and social systems and and social interaction because you need to understand is is how people are going to uh use your your automation, use your equipment. Sometimes you can’t anticipate everything that that people might do. It may not be logical to you. It may not be logical. You know, again, as engineers, we want to make sure what we do is safe. Yeah. Right. So, you sometimes you have to study. You have to study what they do and how they how they they perform their work, how do they drive, you know, how do they how do they see the world, you know, and what do they look for? And so a lot of times it’s it’s really social science too is understanding that not just as an as an engineer you you know it’s just not just a technology. So I think uh getting into this business automation as it grows I I see it you know changing and psy adapting to the people you know. So I I think that’s going to be something you need to focus on and you know improve your skills in those areas. Yeah. So, you know, Gabes, you’ve already talked about a lot of lessons, but was there like one hardle learned lesson that has really stuck with you throughout your, you know, professional journey? A hard lesson was just uh writing white papers I remember is when is failure. It’s just, you know, it’s like, wow, you know, I failed, you know, and you’re not used to failing as an, you know, as an intelligent person going to college, you know, it’s like getting an F, you know, in school fail. Yeah, big flat F, fail. I mean, it’s hard. That was hard for me to comprehend, you know, that I failed at something. It’s not fail. It’s not failure, you know. It’s a learning experience. After a while, you learn it’s it’s a learning experience. It’s not failure. And uh as long as you think of it that way, you know, then you’ll continue to improve. Some of the people that, you know, that’s the ones like say would use that, oh, you got to write a white paper. Oh, I won’t do it. one because they’re they’re they’re afraid of failure. They’re afraid of failure, you know. So, I think I learned how to fail. I’m probably pretty pretty good at that now. That definitely is a learning curve and that sort of tells how you know you’ve made it till here so far. But then, you know, Gabes, given that you’ve got a lot of experience, four decades of experience in the field engineering, right? There are software engineers and then there are field engineers. So do you believe that you know software engineers get to have the more glam in comparison to the field engineers who are at the core of making things and that’s oh yes you know yes I yeah I do you know it’s it’s obviously there’s the you know there’s that’s just the nature of the business and back end right I yes I I know but obviously as you know you you know you do learn after a while is you can’t get anything done we were talking about making change right you can’t get anything done unless you have a field engineer that’s going to implement it for you. Yeah. Right. You can have a really good idea, right? You can be really really smart, but if you can’t get the cooperation from the people that are going to implement this, they can make you look really bad. They can make you really, really bad. I used to tell people, I says, you know, I can make a really fancy control system. I can make that system look really bad. Yeah. And I can make this really dumb, you know, control system. very archaic, you know, I can make it look really good. So, when I was a field engineer, I can I I would say that I love the field. I like getting out there. I like talking to the people, understanding, you know, again, their point of view, how they get things done, how do they like the design, what information are they lacking, what, you know, what would make their job easier for them, move faster, you know. So, in order to figure that out, you got to go talk to the people. You got to go out there and you got to talk to people, you know, and you got to be able to talk to them in a manner that uh that they’re willing to give you information. If you go out with a different attitude, some people just they don’t want to give you information, you know, let them let you they let them figure it out the hard way, you know, uh why should I help them, you know, those that type of attitude. You have to have the skills to go and and and talk to people to get information from them that’s useful to you and they’re going to be willing to do that and you got to you have to have the skill to do that. What do you think the world would have been like had there been no semiconductor, you know, fab facilities? Where would have we been today? Oh, well, some people might say that’s a that would have been a good thing. You know, you wouldn’t have to worry about your teenagers dealing with this, right? And the social media stuff and all the things that go along the complications that go along with it. It just created a new all these new challenges for society. You know, those are the downsides and you know, then you have to look at the upside. It’s like, oh my gosh. You know, I remember it’s like, oh, you know, trying to find a pay phone. Did I have a dime or a quarter depending on what year it was in my pocket? I used to carry in your wallet to make sure you had a a coin in your wallet to go make a phone call. Simple things, you know, people were, you know, you know, would die, you know, uh because they didn’t have lacking communication or ability to call emergency or there’s all these pros and cons, but it’s definitely not one-sided. there’s a lot of um you know complications and social issues that we got to deal with all any kind of automation and future automation coming along you know whether it’s going to be embedding stuff in us or having you know autonomous or robots so g from being a student to be able to work with big names like Intel and Google you know for for a larger time of your of your life what was it like you know what changed for you being you know knowing that now you’re you’re making impact at probably a very art scale. I talked about my humble beginnings and I always wanted no more. You know, one of these things about these new companies that come that come along in their initial phases, you know, they, you know, they had money to spend. You know, they had money to spend. And as an engineer, God, you need money to do things. You you need money to experiment. You need they need money to to to work on cool things, right? And to have cool stuff. So that’s that’s how I got involved with those companies is looking as a person outside looking at what are they doing inside that building. You know, I really I really want to know what they’re doing inside that building. It whatever it is, it’s got to be cool. Yeah. You know, it’s got to be cool and and and as an engineer, I just wanted to know what are they doing inside that building? And I want to be a part of that. I want to see and maybe I’ll like it, maybe I won’t. I’m going to learn something. And that was my key goal. I wanted to learn something. And uh you know and like I say maybe I’ll like it, maybe I won’t. So once you were on the inside, what changed? You know, like how did you feel about it when you were a Googler or part of Intel or Oh yeah. You know, because uh America for that matter. Yeah. Yeah. You know, like I grew up through I was uh you know, gosh, I was with Intel for 25 years, you know, and uh when I went to Google, you know, and uh it’s like, oh my gosh, man. I’m you know, I’m kind of I’m kind of old, you know. I was like, I wonder if I’m going to be able to to hang with these guys, you know, all these noolers, the nouglers at Google, you know, because uh they’re used to dealing with all these different things. And I remember getting be on the Google bus going to work and I’m on my computer, you know, working and uh because everybody’s on their computer working in the in the bus and uh oh gosh, I get to work and I’d be nauseated sick in the bus cuz it’s like a ship, you know, it’s moving like this, you know, and I talked to this one guy, God, he’s, you know, he was just out of college or whatever and he came in, you know, from San Francisco on 45 minutes on the bus and I go, gosh, I says, you know, I asked him one day, I says, you know, I, you know, I get I get sick. Uh, by the time I get to work, man, I’m nauseated. I’m about to puke every day. He says, “Oh, God.” So, it’s not just me. I said, I just thought, you know, maybe it was just it was just me, you know. He says, “No.” And, uh, I realized, too, it’s like, you know, my skills were pretty good. You know, my technical skills were good. Uh, you know, obviously my personal skills and and my social skills were good. You know, it was more about, okay, what are we doing today and what it needs to get done? uh and how do they do things you know what can I learn from this company you know what are they doing you know that I can learn that’s new and uh because they were you know oh they’re at the forefront they were spending a lot of money Google became part of our you know vocabulary you know is is the search engine you know and how did they do the search engine and what were they you know was all about you know you know automating the software and automating the the search and how it did that the algorithms you know and what were they doing in business how did they see the world changing uh and how were they going to imple implement change in the world, you know, again because you know, as I told you earlier, I like change. Have you have you sort of had any interactions with Gen Z engineers? Yes. Well, you know, uh I have kids and I have grandkids. All right. So, you know, I have, you know, kids that are in their, you know, uh their late 30s. I might even be 40 by now. I’m not sure. I I have to ask my wife down to in their 20 late 20s, I think. Uh my youngest. And then I’ve got uh grandkids that are, you know, four years old and 17 year old and I’m curious to see how they how are they’re using, you know, these tools, you know, these social tools, you know, again, this this computer here, you know, uh and other forms of of automation, you know, you because I love that, you know, how do they interact with their cars? What’s troublesome to them? You know, if the car breaks down, how are they going to fix it? How do they deal with that? And I’m curious about my four-year-old granddaughter, you know, and I watch her playing with her, you know, with her tablet, what she knows and how she’s being educated, not through just, you know, my daughter educating her and the school system educator, but you know, there people are learning, you know, being educated on their own, right? They’re being educated through uh, you know, through social media and, uh, and what’s online, right? And you know some of that is is good you know some a lot of it is good. So how is that going to affect their you know uh their education and their view of the world later on you know so I’m curious about that like to see how that goes you know the good things and and and the other the complications that come with it. Yeah. So can you just name any one innovation or trend for me in automation that you’re sort of keeping a close eye on in the future which will Yeah. You know, I’m I’m still I’m kind of disappointed. I’d like to see the the networking right now. It’s uh the digital communication. Okay. Yeah. Uh whether it’s Well, I guess may could be analog communication. I maybe that’s the because analog communication, there’s some real benefits with analog communication over digital. Some things that uh you know, the radio signals and such, analog signals are really good at. It’s that common level of communication we’re still lacking uh for devices, intelligent devices to seamlessly talk to each other, okay, without a lot of uh effort. We’re still lacking in that area there that we don’t have, you know, a real solid common platform for intelligent devices. I really want to see that go somewhere. I think that u you know communications I’d like to see more use of microprocessors whether they’re is it really microprocessors or is it going to be something else other than a microprocessor you know I think I I want to see you know I’d like to see where that’s going to go you know this quantum computing thing they’re working on it you know is that going to change computing altogether you know it gets back to that you know is it going to be closer to mimicking nature I think wireless as well is is the other area is still communications. Uh we’re still having trouble even with with hardwired communications uh or fiber or what have you, but uh is wireless communications. You know, there’s great things and there’s, you know, there’s a lot of improvement to be made there in in wireless communications. I’d like to see where that goes. And then the other thing is energy. All these things require energy. And like we were talking about earlier about nature, how does it do it? How does an ant, you know, carry boulders, huge boulders around? How are they converting that energy uh to do that? And how do we, you know, if we’re making intelligent devices, you know, IoT type devices and such, artificial intelligent devices, they all need power, some form of power of a thing. So, I’d like to see, you know, where that goes, power more efficiently, you know, to power these automated devices or else they don’t they can just they’ll just sit there, you know, they’re not going to do much if they don’t have power. If they can’t communicate, they’re pretty much useless. That’s true. So, Gab, we’ve had a lot of discussion around, you know, technology and semiconductors. So, other than engineering, what were some of the other hobbies or passions, you know, that you had in life? Or was it just engineering? No, you know, and maybe that’s another lessons learned for for uh young young engineers. You need to find a way to relax and to refresh. You know, you have to refresh. the body needs to get refreshed, you know, and you’ll find that once you’re refreshed, you’re more energetic and and and I think you can probably, you know, be more productive, come up with better ideas, be more enthusiastic, be more determined, uh all these things that takes energy. Again, it’s back to the energy thing, right? Is you got to, you know, our body needs energy. And I like to, you know, garden, you know, I like maintaining, you know, my yard and my house. You know, when something breaks in my house, I’m on it. I, you know, because it’s, you know, it’s it’s relaxing me to go fix something, you know, do something with my hands, do something with my eyes, feel, you know, feel feel the weather, feel the cold, feel the heat, smell, you know, explore. And when I do those things and when I go to work, I feel refreshed and I’m ready to take on the next challenge. You got to find a way to refresh yourself. Well, Gabes, uh, I think that this conversation has been incredibly insightful. You’ve taken us behind the curtains of what it really takes to build and maintain some of the most complex systems in technology. Thank you for breaking it all down and sharing the lessons you’ve learned along the way. It’s truly been a pleasure having you on the show. Thank you so much. Sure. I was glad to share it and hopefully somebody gets something out of it. [Music]