Editor’s note: This is the latest in a series of reports about Artificial Intelligence based on a variety of deep-dive interviews conducted by Alexander Ferguson of YourLocalStudio.

Welcome to UpTech Report Series on A.I. I’m Alexander Ferguson. This video is part of our deep dive interview series where we share the wealth of knowledge given by one of our panel of experts in the field of artificial intelligence.


This is the second part of my conversation with Rett Crocker CEO and CTO of UDU in Raleigh. Rett has designed and developed over 100 games for mobile devices, personal computers, and video game consoles. He’s also invented multiple programming languages, game engines, and multi-user content. And he’s created innovative software technologies in fields ranging from speech synthesis to Avra gaming to collaborative education.

The interview

In this video, I ask Rett what examples he’s seen of businesses using A.I. to become more efficient? How A.I. differs in business use and consumer use and how business leaders should construct their team with A.I. in mind.

So, I’ve seen a few examples. Not nearly as many as I’d like to see. So. Two examples that I will give. Both relatively short. One is, one of our customers, one of our oldest customers, they track apartment rentals. Availability, pricing. The way they used to do that, well. 2/3 of the problem is solved because 2/3 of the market is these big giant apartment buildings that are owned by big companies that have tech teams that build an API, that they can just hook into.

The last 1/3 is the hard part. And the way that last 1/3 works, is they have humans in cube farms going to websites and saying, “There’s an apartment available on the first floor. “It’s $2,700 and it was $2,600 six months ago. “Square footage is the same. “It looks like they say it’s got 2 1/2 baths now, “instead of one bath. “So, what’s going on? “I don’t know.”

So, they have humans doing that problem. They now use UDU to do that work, most of the time. So, for about 1/2 of that 1/3. So, I guess, 1/6. For about 1/6 of their overall catalog UDU just goes and collects all that data for them. There’s no humans involved at all. For the other 1/6, there’s some small percentage that UDU can’t help with at all but most of the other examples, this customer has those same cube farm people but instead of going to those web pages and entering the data themselves and only getting through basically 20 apartment buildings a day, which is what their rate was, they instead go to that apartment building website and they click a button that they call the “UDU button” and it basically sucks up that website and sends it up to UDU.

UDU processes it, does all sorts of crazy stuff with the text, and then shoves that data into their CRM. So, all that that humans there for is clicking that button. And figuring out what the right page is in the first place and doing human things that are actually more difficult. I would argue their quality of life is better. Although, not much better, in my opinion. But that’s a different issue. The second example that I would give is, there’s a movement I’ve definitely seen in the private equity space just because of the fact that we’re currently serving that market of people doing what’s called deal origination or deal sourcing using more automated methods. Some are using people like us. There are some that are trying to use different A.I. techniques.

I haven’t seen many great examples of them being successful with that except for with our stuff and a couple of the other competitors that are actually mostly using humans. But the thing that they’re all trying to do, is basically make it so that their humans don’t have to do that particular grunt work again. Because the way that used to work, is that they would buy a list of all the, like they’re gonna buy, they want to buy a number of dentists. Dentist office, dental clinics.

And they’re centered around the northeast and the way they would do that is they’d go to Dun & Bradstreet or whatever, somebody and they’d say, “Give me a list of all the dentists in the northeast.” Or they’d look in the phone book, or whatever, right? And then they’d have MBA interns, people that actually make real, live money, sometimes six figures, going to each one of their websites and saying, “How many dentists did I have? “Who’s the senior guy? “The owner, how old are they, are they over 50? “Are they maybe getting ready to retire? “Maybe they’d be interested in selling.”

All those things. That’s what humans would do, everyday. Day in and day out. And have done for years and years. But, they don’t do that now. Or at least, every one of those people is trying. The smart ones, anyway, are trying to figure out how to not do that because it’s such a colossal time sink.

  • How can business leaders better utilize A.I.? And what are the potential issues those business leaders may face?

So, I would use it in cases where you need to predict the outcome of something. That’s the best case scenario use for it. That’s what it’s good for. That or automation, are the two big uses. So, an example of the automation that I gave earlier, the human sitting at the desk, clicking the UDU button and uploading the website and then UDU does all the processing on it so the human doesn’t have to do data entry, that’s a great example of automation.

The prediction side is, if you’ve got a business case where you’re trying to predict how much your customers gonna spend next year or whether or not Customer X is gonna like something or not, those are great uses for A.I. because you’re basically saying, “I’ve got a bunch of data that shows how people have reacted “in the past and I’m gonna use that to try “and predict the future.”

The biggest difficulty relating to doing anything A.I. predictive is getting good data. That is the hardest thing. And then also not believing the hype around it because the way the math works, you can end up finding false results pretty easily that seem great but aren’t real. So, it’s very important to build all your systems, all your models in such a way that you can test them and verify that they actually work.

  • How does the threshold for success change when A.I. is being used for business versus consumers?

In business, you only have to get to 80, but in consumer you gotta get closer to 99, which is why people are, diss Siri, because it’s like, “Oh yeah, it didn’t understand me that one time.”

Whereas with business you can be, it’s a little bit more pragmatic. You can be like, “Well, it didn’t work 100% of the time “but eight out of 10 times, I didn’t have to do anything.” Microsoft Office, Microsoft Word, back in the day had the paperclip. “Yeah, I see you’re writing a resume, “you want some help with that?” No, Clippy, go away.

The reality is that feeding that sort of information in and having it try and predict and help you, can be quite useful. But I think that one is sort of a consumer level bar that you have to reach where it’s like it’s gotta be right 99% of the time or you’re gonna be really annoyed with it and you’re gonna turn it off. If you can use A.I. and the principles of statistical analysis and predictive analytics and all that to get you 80% of the way to solving your problem, then you’ve got something very valuable.

Even if you have to use humans for that last 20%, that’s still dramatically better than having your humans doing it, doing 100%.

This was just a taste. Stay tuned as we share the full deep dive interviews we had with each one of our panel of experts and our upcoming episodes focused on specific topics that will transform the way you think about artificial intelligence. All this, on UpTech Reports new series on A.I.