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<v Ryo Koyama>Hi, I'm Ryo Koyama. Welcome to Remotely Local, where we talk about all things that

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<v Ryo Koyama>are happening in the device world and physical AI. I'm very happy today to

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<v Ryo Koyama>have Sam Cox on who's CTO of Mountain Vector. Welcome Sam.

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<v Sam Cox>Good to be here. Thanks for having me.

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<v Ryo Koyama>So, for those who don't know what Mountain Vector does, uh why don't you give us a

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<v Ryo Koyama>little bit overview what the company does and um what's happening in

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<v Ryo Koyama>your particular space of the market.

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<v Sam Cox>Uh so Mountain Vector we do all things energy management from you know basic utility

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<v Sam Cox>bill management type stuff all

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<v Sam Cox>the way down to high level advanced analytics to breaking down you know solar

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<v Sam Cox>battery setups getting specific uh usage and savings numbers usage and

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<v Sam Cox>spend savings numbers against that. So lots of high level analytics in regards to

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<v Sam Cox>energy management a lot of AI different pro uh AI processing different

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<v Sam Cox>types of things for uh just making people's lives easier when it comes to that environment.

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<v Ryo Koyama>Now we we've talked a little bit in the past and one of the

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<v Ryo Koyama>things that I found really interesting is that you know energy has been around for a

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<v Ryo Koyama>long time and you know adoption isn't always as quickly done as people

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<v Ryo Koyama>think and so you know you you talked about dot matrix printers but it sounds like

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<v Ryo Koyama>you know part of the challenge isn't as simple as hey let's grab all

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<v Ryo Koyama>this data let's analyze it you know the way that it's portrayed in the media talked

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<v Ryo Koyama>about the dot matrix type of experience because it goes all the way

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<v Ryo Koyama>down to that.

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<v Sam Cox>Sure. Definitely. So, utilities are a very I mean, utilities have been around since

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<v Sam Cox>electricity's been around and getting them to do or to

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<v Sam Cox>adopt any new technologies is a very difficult feat because there's all these

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<v Sam Cox>integrated processes and things like that that have been, you know, people have been using for years. So, they

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<v Sam Cox>don't want to break things. So, they just kind of keep going with the same setup

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<v Sam Cox>over time. And what you'll find is a lot of smaller local municipalities,

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<v Sam Cox>they'll have these uh utility bill formats that are just, you know, paper documents

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<v Sam Cox>that you have to scan in. Um, but the format is something akin to a

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<v Sam Cox>dot matrix printer, right? Like you just have very poor quality account numbers,

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<v Sam Cox>very poor quality all of the data. It's

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<v Sam Cox>very difficult to read for a human. So trying to get all that stuff together such

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<v Sam Cox>that a computer can do anything with it. It takes a decent amount of effort.

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<v Sam Cox>And thankfully we have, you

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<v Sam Cox>know, AI tools and different things like that to help us these days.

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<v Sam Cox>Uh, but it's just trying to help move an industry that's very much stuck in the past into

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<v Sam Cox>any type of really to the 2010s even is just it's a feat within itself.

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<v Ryo Koyama>You guys are in the entire domestic US or how do you typically work?

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<v Sam Cox>Yeah, so we're in throughout the entire United States right now.

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<v Sam Cox>I think we're coast to coast. So we've got some spots in California all the way out to uh

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<v Sam Cox>Detroit, I think even Massachusetts area. uh we work with lots and lots of different

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<v Sam Cox>school districts, a few different industrial clients and a few

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<v Sam Cox>other utilities that we'll actually kind of work with to do specific uh things that they need.

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<v Ryo Koyama>Well, that was kind of a range because it sounds like you work, you know,

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<v Ryo Koyama>specifically with a lot of public schools all the way to industrial companies. And so I would imagine that

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<v Ryo Koyama>the whole environment looks very very different and it's probably not shocking

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<v Ryo Koyama>anymore, but there must have been some cases where you walked in and you just

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<v Ryo Koyama>thought, "Wow, this is not what we expected to do."

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<v Ryo Koyama>Any any fun stories in that arena?

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<v Sam Cox>Sure. I think um one of them we had an industrial customer that one

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<v Sam Cox>of their primary problems was getting the information out to their facilities

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<v Sam Cox>managers to be able to make energy

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<v Sam Cox>decisions based on locational LMP pricing, locational marginal pricing.

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<v Sam Cox>Um so you're tracking that you know 15-minute, five-minute

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<v Sam Cox>price signal uh live throughout the day and they want to know are we going beyond a

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<v Sam Cox>certain threshold so you know should we curtail operations should we

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<v Sam Cox>keep going how should we plan for this in the future so we're doing a lot of work

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<v Sam Cox>with them to like set up some things so they have more information in

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<v Sam Cox>terms of figuring out what to do next and we're also working on some more predictive

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<v Sam Cox>type things so that they can you know instead of reacting to the

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<v Sam Cox>present maybe start to plan out for the future a little

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<v Ryo Koyama>What I love about what you guys are doing as a company is that the media loves to talk about physical

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<v Ryo Koyama>AI and I think to the point where there's a c certain amount of uh probably

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<v Ryo Koyama>exhaustion about the topic but you know to me it's AI is obviously very

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<v Ryo Koyama>sophisticated everybody reads about it in the paper every day in terms of how

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<v Ryo Koyama>powerful it is in some ways very dangerous but at the same time what you

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<v Ryo Koyama>have to do and physical AI is really about taking the existing world and making it

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<v Ryo Koyama>be able to take advantage of

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<v Ryo Koyama>AI and obviously you know at Remote.It that's one of the things we pride ourselves

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<v Ryo Koyama>on is we kind of think of ourselves as kind of that that infrastructure there that allows that

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<v Ryo Koyama>connectivity to happen so maybe you know dig into you know sort of what are the

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<v Ryo Koyama>problems that you were facing and why you guys enjoy using Remote.It or maybe

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<v Ryo Koyama>what the use cases might look like

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<v Sam Cox>definitely I I think it's a great point you said like setting up the infrastructure

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<v Sam Cox>because everybody and their mom is like we have AI-driven

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<v Sam Cox>insights we have AI driven this AI driven that somebody's got to build the road if

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<v Sam Cox>you're going to drive on it right So setting up that infrastructure, getting that data from point A to point

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<v Sam Cox>B, that's super important for us. That's like our primary pain point is just getting

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<v Sam Cox>the data to the right place. So from a Remote.It perspective, what we're

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<v Sam Cox>doing is we have, you know, hundreds of devices deployed all across the country and

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<v Sam Cox>we're we're a small company based in New Mexico, you know, one state, I think

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<v Sam Cox>10 or 12 people. we don't have the resources to be deploying people all over the

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<v Sam Cox>country to go on-site if there's issues with our devices or

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<v Sam Cox>issues that we have to work with somebody to figure out.

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<v Sam Cox>So what we're doing with Remote.It is we're setting up all of our devices so that

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<v Sam Cox>they can be remotely accessed you know anywhere in

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<v Sam Cox>the country uh so that we can get on change configurations for things upload data

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<v Sam Cox>figure out you know what's going on if we're having problems and we're

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<v Sam Cox>taking all of that and then it's feeding right into our backend so we can do

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<v Sam Cox>different analytics uh live real-time spend calculations against um utility

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<v Sam Cox>rates things like that so it really just supports our ability to have that uh that

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<v Sam Cox>live metering infrastructure.

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<v Ryo Koyama>Yeah, I mean that's the one thing I mean it's

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<v Ryo Koyama>interesting because you know as a networking guy I always think about connection but

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<v Ryo Koyama>so much of it is now just about communication like you talked about it's like you know at any point in

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<v Ryo Koyama>time you know that's sort of what inspired the name of the podcast you know remotely

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<v Ryo Koyama>local and so you know you want to be in New Mexico and like you

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<v Ryo Koyama>know and I think your case Montana and you want to be able to see your whole

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<v Ryo Koyama>environment as if it's there and it sounds like that's a that's kind of it's

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<v Ryo Koyama>not only important it's kind of become fundamental because if you can't see the

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<v Ryo Koyama>world today you sort of have a problem and it sounds like that's part of what

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<v Ryo Koyama>you're able to take advantage using as a service.

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<v Sam Cox>Definitely. I mean if we didn't have Remote.It available I was going to have to

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<v Sam Cox>build it myself and this was this is four years ago that I was looking at

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<v Sam Cox>having to do this and I was you know thinking about reverse SSH tunnels and setting

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<v Sam Cox>up all this infrastructure and I was like this is going to be a lot of work for

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<v Sam Cox>something that we're not going to have to rely on every single day.

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<v Sam Cox>But I found Remote.It and I was like, this is exactly what I need.

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<v Sam Cox>It the price is, you know, I'm I'm saving money

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<v Sam Cox>by not doing this on my own. The customer support has been phenomenal.

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<v Sam Cox>Anytime I've had an issue, even if it wasn't with the product, I was having some uh

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<v Sam Cox>internal issues on the device that I was having trouble diagnosing.

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<v Sam Cox>And I was, you know, emailing back and forth with with rep and they tracked it down

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<v Sam Cox>to an MTU level problem and got it fixed on my end and all of a sudden

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<v Sam Cox>we're back up and running. So Remote.It I've had nothing but spectacular experiences with Remote.It.

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<v Ryo Koyama>Well, that's awesome. We we obviously love to hear that and we're not trying to make

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<v Ryo Koyama>a commercial here, but uh it never hurts when use.

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<v Ryo Koyama>Well, that that's awesome. Like I said, I I think the big challenge is that we're

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<v Ryo Koyama>starting to see and again what I appreciate for what you're saying is that, you

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<v Ryo Koyama>know, most of the internet was

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<v Ryo Koyama>invented when it was a much simpler problem, you know, and eventually got to

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<v Ryo Koyama>everybody just needs to get to a website. But now that you're facing not

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<v Ryo Koyama>only you know internet of things or industrial internet of things along with AI all

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<v Ryo Koyama>of a sudden now you need a real-time communications with everything

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<v Ryo Koyama>you have cellular networks you have people with Wi-Fi you have all kinds of

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<v Ryo Koyama>different network configurations and one of the things we pride ourselves on is

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<v Ryo Koyama>kind of making all that invisible so people don't have to deal with that and it

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<v Ryo Koyama>sounds like maybe that's the key benefit for you is to not have to think

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<v Ryo Koyama>about that. So taking it further then I mean talk a little bit about how you see

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<v Ryo Koyama>physical AI developing now because you know the way I look at it now is going

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<v Ryo Koyama>back to what I said no one who is in the smartphone generation they they fully

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<v Ryo Koyama>expect that they can get to anything anywhere you know they don't understand

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<v Ryo Koyama>the complexities of it because that's sort of the expectation today and so as the

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<v Ryo Koyama>world of energy and energy management starts to develop what what

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<v Ryo Koyama>do you think is going to be in a crazy amount of time like 3 years from today what

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<v Ryo Koyama>is going to be the expectation that isn't the expectation today.

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<v Sam Cox>I think I guess a more declarative world meaning that we know what we want in our heads.

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<v Sam Cox>You know, for example, like at a CEO level, I know what product I want, but I don't

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<v Sam Cox>know how to get to that implementation level. But if I can just

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<v Sam Cox>say to an AI, I want this and it can do it, then all of a sudden the world opens up

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<v Sam Cox>in ter in terms of possibilities. So

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<v Sam Cox>like you can go from having kind of loosely structured data or like very like in the

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<v Sam Cox>case of utility bills for example varying different types of data

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<v Sam Cox>with like loose relationships. I can turn an AI at it and say go retrieve this

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<v Sam Cox>information, go do this, go do that, you know, put it all in this

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<v Sam Cox>report, put it in this database, and it can just figure it out and do it.

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<v Sam Cox>And so it's it's kind of just it's going to augment our reality, I think, in terms

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<v Sam Cox>of human capability. It's just another tool really that we're all kind of learning

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<v Sam Cox>how to use and things are getting better and better as we go.

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<v Sam Cox>But yeah, I think if I just had to look

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<v Sam Cox>three years out, it's just going from that more imperative setup to that more

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<v Sam Cox>declarative. Just say what you want, you know, get what you need.

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<v Ryo Koyama>Well, I love that. Like I said, I think we're gonna

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<v Ryo Koyama>we're gonna definitely title this podcast declarative, not imperative because uh I

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<v Ryo Koyama>love that expression, but I think to your point, the big challenge

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<v Ryo Koyama>of shifting to AI is that everything isn't just plain language.

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<v Ryo Koyama>And it becomes very very declarative because you're not thinking about how do I make

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<v Ryo Koyama>this happen. You're thinking about the what do I want to have happen?

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<v Ryo Koyama>And it can be very very frustrating if it's not possible because again the expectation

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<v Ryo Koyama>in the the world of smartphones and next with AI is going to be why can't it happen

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<v Ryo Koyama>and obviously ChatGPT and all

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<v Ryo Koyama>the other LLM are very good about saying well of course you're right Sam I should be

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<v Ryo Koyama>able to do that for you and so that's the world that we're heading into. All

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<v Ryo Koyama>right as we wrap up then what's your hot take? So what's the thing that you think

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<v Ryo Koyama>that's going to happen in the world of physical AI that's maybe not

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<v Ryo Koyama>conventional wisdom that is maybe a little bit orthogonal to what everybody else is thinking?

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<v Sam Cox>I think especially around the beginning of uh generative AI becoming more and more

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<v Sam Cox>popular. There was this general

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<v Sam Cox>kind of I guess concern or thought that like AI is going to take your job.

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<v Sam Cox>AI is going to you know do this AI is going to take over all this stuff and then people

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<v Sam Cox>are going to kind of be left on the sidewalk with nothing to do.

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<v Sam Cox>And in my experience, having AI available to me, it's sped me up in a lot of ways,

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<v Sam Cox>but I am more busy than ever because now instead of doing one

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<v Sam Cox>feature a month or one feature a week, I can do six.

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<v Sam Cox>I can do 10. And so it becomes like I was always going to have

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<v Sam Cox>to solve those six or 10 other problems, but now it just the queue empties and fills

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<v Sam Cox>up more quickly. So, I think AI is

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<v Sam Cox>really going to go from I'm going to take your job to you're going to have to have

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<v Sam Cox>me to use your like to do your job. For example, like a computer or Excel.

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<v Sam Cox>Like there's certain accounting things that you would never want to do by hand, but

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<v Sam Cox>that's how they used to do it. Then you get Excel and now you can do 50

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<v Sam Cox>different accounting things, but you've now you just got 100 more customers.

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<v Sam Cox>So, it's all just a matter of volume. And I think uh we're just going to see more

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<v Sam Cox>and more volume pour into people's work queues, I guess, as a result of AI, rather

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<v Sam Cox>than seeing people's jobs be taken away.

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<v Ryo Koyama>No, I I I think that's a very good take.

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<v Ryo Koyama>I mean, one of my views is I always say every industrial revolution was marked by

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<v Ryo Koyama>indentured servitude. And if you look at the economics of AI, in a lot of

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<v Ryo Koyama>ways, this is the cheapest indentured servitude we've ever had.

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<v Ryo Koyama>And I think you explained it well. It's like, well, I would have had I could have

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<v Ryo Koyama>thought about these six things in serial, but

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<v Ryo Koyama>now I do them all in parallel. And and I love your Excel analogy because I think

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<v Ryo Koyama>that's the big thing. It's like, I could do this, but it'd be terrible, and now

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<v Ryo Koyama>it's like, oh, I want to get this done, and it's a great thing to be able to do.

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<v Ryo Koyama>So, we talked a little bit about how AI is a little bit too positive.

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<v Ryo Koyama>Do do you see that as a problematic thing where

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<v Ryo Koyama>they it is so reinforcing? I mean I I joke that it's sort of the creation of

00:12:29.026 --> 00:12:33.000
<v Ryo Koyama>religion because it is the source of truth for so many people. What what do

00:12:33.000 --> 00:12:38.310
<v Ryo Koyama>you think especially like in the energy sector what's the risk of AI being so

00:12:38.310 --> 00:12:41.000
<v Ryo Koyama>declarative about your right and how do

00:12:41.000 --> 00:12:44.000
<v Ryo Koyama>you think that will affect your industry as it goes?

00:12:44.000 --> 00:12:48.368
<v Sam Cox>It's an interesting question. I think the risk you kind of run into there is like a

00:12:48.368 --> 00:12:52.000
<v Sam Cox>very simple one I can think of is like you ask somebody to generate a

00:12:52.000 --> 00:12:56.000
<v Sam Cox>report that would historically require you to go and you know gather all this

00:12:56.000 --> 00:13:00.000
<v Sam Cox>information kind of do all this manual analysis things like that when now you

00:13:00.000 --> 00:13:04.000
<v Sam Cox>can tell the AI to go do it maybe it has to go to the internet fetch things maybe it

00:13:04.000 --> 00:13:09.000
<v Sam Cox>has to read some things from documents and maybe you've described exactly what you want maybe that's what

00:13:09.000 --> 00:13:16.000
<v Sam Cox>the AI produced but what you said and what you needed are not the same thing.

00:13:16.000 --> 00:13:19.609
<v Sam Cox>And that's kind of what I'm sometimes finding when I'm working with AI is that I'll

00:13:19.609 --> 00:13:24.000
<v Sam Cox>say that I want one thing and then it'll go to do it and I'm like, "This doesn't work in a production

00:13:24.000 --> 00:13:25.962
<v Sam Cox>environment. Why would you even attempt to do this?"

00:13:25.962 --> 00:13:28.604
<v Sam Cox>And so I think it's it's something that's got to be closely monitored.

00:13:28.604 --> 00:13:32.000
<v Sam Cox>Not sure how well that answers your question, but I guess that's kind of how I'm thinking.

00:13:32.000 --> 00:13:36.260
<v Ryo Koyama>No, I I think that's right because, you know, again, to reinforce your point about

00:13:36.260 --> 00:13:40.000
<v Ryo Koyama>it's going to take jobs in a lot of ways, it makes human competence more

00:13:40.000 --> 00:13:43.291
<v Ryo Koyama>important because you're going to have to evolve what those things are.

00:13:43.291 --> 00:13:47.000
<v Ryo Koyama>So, well Sam, it's been great to have you and anybody who's looking for physical

00:13:47.000 --> 00:13:51.486
<v Ryo Koyama>AI in the energy space, Mountain Vector is the place to go and u they're definitely

00:13:51.486 --> 00:13:55.000
<v Ryo Koyama>leading from our perspective a lot of the activities that are out

00:13:55.000 --> 00:13:58.282
<v Ryo Koyama>there. So, it was great having you on and I'm sure we'll have you on again as we

00:13:58.282 --> 00:14:01.441
<v Ryo Koyama>introduce some of our own AI tools because I definitely would look forward to

00:14:01.441 --> 00:14:03.000
<v Ryo Koyama>getting kind of your feedback on that.

00:14:03.000 --> 00:14:11.209
<v Sam Cox>Amazing. Sounds great. Thank you so much for having me.

00:14:11.209 --> 00:14:13.000
<v Ryo Koyama>Thanks, Sam.