Does Your Business Need AI?

Does your business need AI? Likely the answer is yes, and if not now, it will be. To be able to compete at speed and scale, machine learning and artificial intelligence will need to be an essential component of your tech solution.

Full Transcript Below:

Greg:

But I think what really got us into AI and me specifically was the different companies I had started just sort of demanded an AI solution.

Cris:

Machine learning, which is usually kind of paired with AI or ML and AI. Is there a difference between those two? Are they one and the same?

Greg:

Weather data for the ML to just… for the machine to kind of learn how the weather works, say in our area. And then to, hey, what’s the weather tomorrow? It’s going to give you a prediction and it’s probably not going to be always right.

Cris:

All right, everyone. So just wanted to say howdy and welcome to another episode of basically kind of a getting to know you in our Bixly series here. But more than getting to know you, I actually get to jump on and talk today with Greg who started out as a business contact but has really become an acquaintance and then now a friend and works for a company called BrightApps. So Greg, I’ll let you introduce yourself again, BrightApps and what you guys are all about, and we can go from there.

Greg:

Fantastic. I’m happy to be here. Thank you for that.

Cris:

You’re welcome.

Greg:

Let’s see, my name is Greg McGregor and I’m the CEO of BrightApps and we’re a consulting company specializing in software development specifically around integrating and using AI to help bring speed and scale to your business and larger companies — Our background has been developing everything you could imagine over the last 20 years, but we’ve really honed in on the AI side of things.

Cris:

Very cool. Now, one of the things I hear a lot floating around is machine learning, which is usually kind of paired with AI or ML and AI. Is there a difference between those two? Are they one and the same? Let’s talk about that a little bit.

Greg:

Yeah, sure. So AI, you can think of it as sort of the general catch-all or applying artificial intelligence and so forth. And you can view ML or machine learning as just a subset of AI. Basically in the process, engineers will take a lot of data and they’ll have a machine learn patterns or learn something about the data. And then when you apply the data in some AI scenario, you might ask it a question and it’ll give you the answer back. Like weather prediction. An example: it’ll take an awful lot of weather data for the ML to just… for the machine to kind of learn how the weather works, say in our area and then to, hey, what’s the weather tomorrow? It’s going to give you a prediction and it’s probably not going to be always right. But it’s close.

Cris:

Gotcha. So you do a lot of projects, you being BrightApps and obviously, personally. What kind of got you into this maybe to begin with, and then how did that lead BrightApps into starting to focus on more machine learning and kind of AI related projects?

Greg:

I’m trying to think all the way back to potentially college and stuff. There were a lot of algorithm courses and stuff. I really, really enjoy that, but I think what really got us into AI and me specifically was the different companies I had started just sort of demanded an AI solution. We had done one startup where we were trying to make a biometric credit card. So your fingerprint would release your credit card information on a really thin credit card. And so one of the things is can you get the card to recognize your fingerprint? And that’s another sort of AI taken for granted every day now, sort of thing. Another project we’re working on doing consulting was we had a company that had security cameras installed in all the grocery stores. And they came to me one day, say, “Can we do something other than to have it sit and record video all day? Like, can we do something?” I said, “Oh, that looks like a nice hardware platform for AI.”

Greg:

So we built out stuff like price checking and cab auditing, inventory checking with these cameras that were just useless before and so forth. So kind of one after another, after another, and eventually, we got really good at it and we transformed a larger Fortune 500 and made them number one in the marketplace. So then I was like, okay, I guess we’re going to stick to this.

Cris:

That seems reasonable.

Greg:

Yeah. We do well.

Cris:

What are some of those AI kind of implementations that we just take for granted that were mind blowing like 15 years ago?

Greg:

So my wife and I always talk about when we feel like we’re living in the Jetsons, that old cartoon. Like, oh my God, what’s come out today that’s so cool? But like first thing pops up my Apple watch.

Cris:

Oh yeah.

Greg:

Yeah. See you got one. If you told me 15 years ago, I’d have a watch that I can make a phone call, track my fitness, do an ECG, do blood blocks, everything else. I’d be like, oh, come on. Now, that’s definitely Star Trek right there, you know? But it’s in our everyday life. Self-driving cars. Where does that come from? You have a lot of other stuff too. There’s just a lot of things I think 15 years ago that are just kind of mind blowing. Even several years ago, when I saw Stanford take a quadcopter drone and you could watch it learn to fly.

Cris:

Oh yeah.

Greg:

Yeah. And you just watched the video of this thing, you’ve got to be kidding. It just taught himself to fly in. And now a lot of those models are used to fly quadcopters and so forth.

Cris:

Is there a limit, A to what technology should be able to do and also can do? Like, are we going to be able to find a place, do you ever think where technology just can’t do that? It’s outside of what a machine can do. It’s human, I guess, in nature to get kind of philosophical. And then also at what point should we maybe stop it because we’ve given away too much?

Greg:

No, I completely hear you. So I think you’ve got some really interesting questions there for sure. And I think around the ethics: it ranges from trying to get AI not to be biased for placing a job position and things like that. But it comes from our biased backgrounds, from us, right? All that information it’ll learn from us. But there’s multiple classes of AI and one of them is called general AI. And general AI is the AI that we’re trying to put together. AI that’s basically a human, you know that old trying test. Sit down and talk to it. You wouldn’t be able to tell if it’s a human or not, and really be able to learn and solve general problems and grow and stuff like that. And I haven’t looked into where it’s at in terms of age wise and so forth but that’s actually concerning to me. Just basically any machine, go figure shit out on its own and then come back to us and tell us what it was going to do.

Greg:

I don’t like that. I mean, I do think we need to be careful. That’s not good. There’s another aspect of, we had to be very careful there. There’s another aspect of AI called narrow AI and that’s what we specialize in. And it’s solving specific problems, like keeping the car in between the two lanes, re-detecting your heartbeat, detecting an enemy tank and a battlefield. There’s certain specific things these narrow AIs do. And to be honest, they can become biased as well because they’re coming from our viewpoints. We’re teaching these things. So, and even there you’ve got to be careful but these narrow, I think just solve a specific function. They don’t create your doomsday sky net sort of thing. Like you could put them together and they’ll be pretty powerful and controllable. Yeah.

Cris:

Very cool. What would people do if they’re considering kind of jumping into something that’s now going to involve AI, needing to jump into machine learning? Should they reach out and talk with an expert such as yourself? Is there research they should do on the side first? Kind of, what does that process look like to start engaging with a company such as BrightApps?

Greg:

So are you thinking about an individual or company?

Cris:

Or both. Maybe let’s talk about both. Yeah, if you’re an individual and you’re kind of trying to dabble: are there some good things to learn? And obviously as a company, yeah, you’re probably ready to engage with BrightApps.

Greg:

Yeah, I think as an individual, you have to ask yourself the question, are you going to become a data scientist? Is that what you want? Because there’s a whole different path, the math, and you’re off to school and everything else to become a data scientist. If you want to understand how it works and there’s a lot of great resources on YouTube, some classes at Udemy. There’s actually a course at Firepower Concepts that we partner with has got a fantastic three hour thing. That’s been the best review of AI over a three hour period I’ve ever seen. So that’s pretty cool. And if you’re a company or you really want to get moving on a project, yeah, you are going to reach out to someone like BrightApps and either get some guidance to say, no, this isn’t going to work for you. We could do it. There’s something off the shelf, something on those lines. Because there’s an awful lot to it.

Cris:

Yeah. What’s the best way for people to get a hold of you? Is it to go fill out the widget on the website? Is it give you guys a call? What’s the best way to get in touch with BrightApps, someone’s ready to start a project?

Greg:

They could fill out the widgets on the website. They might get a faster response time. You can also email me at greg@brightappsllc.com. Might get a slower response time.

Cris:

But either way, all right. So either way, check out the widget or the greg@brightappsllc.com. Perfect. All right. Well, that sounds great. Any other closing thoughts you think would be worth adding to this conversation as we’re talking about machine learning, artificial intelligence, those sorts of things.

Greg:

It’s here, it’s prevalent and it isn’t slowing down and it’s going to get faster and do a heck of a lot more in our lives a lot quicker than it has in the past. So it’s coming.

Cris:

So be ready.

Greg:

Be ready.

Cris:

I love it.

Greg:

Adopt or go by the wayside if you’re a business. You are going to need speed and scale, you need AI at some point you or you won’t be able to compete. That’s all.

Cris:

So definitely that’s good. Yeah. As a closing note, as a business out there, this is not something that you should be pushing against. There’s always a way to incorporate machines and teach them to help with some form of automation or something that’s going to help you stay ahead. Because if you don’t, you will fall behind, that eventually you’re going to become obsolete.

Greg:

A hundred percent.

Cris:

Cool. I appreciate the time, Greg. I’m really excited about this and as always, I wish BrightApps the best of luck. And I look forward to continuing this relationship and building some projects out together, it’ll be super fun.

Greg:

A hundred percent we’ll be doing that. Fantastic.

Alexandra:

Thank you for joining us for this episode of Bixly Tech Tuesday, where Cris got to sit down with our partner from BrightApps, Greg McGregor, who’s an expert in artificial intelligence and machine learning. I hope you guys got a lot out of that episode. If you have any questions, don’t hesitate to put them in the comment section down below. And don’t forget to check out our description box, there’s a ton of information down there for you. Including access to BrightApp’s own website. We’ll have that link for you, so you can check out more about Greg McGregor and the services that his company offers. You can also check out our free downloadable guide, which will walk you through the process of planning out your next app idea. And then finally check out our own website, bixly.com. We have a button there right at the top that says, validate my app idea. And if you click on that, you’ll be able to set a time to talk with Cris about your app idea, free, 60 minutes, no obligation. And we’ll really give you solid advice about what the next steps could look like for you. Until next time, this has been a Bixly Tech Tuesday.