Editor’s note: In the second of several in-depth interviews with Alexander Ferguson, CEO and founder of YourLocalStudio.com, talks with Richard Boyd, founder of Carborro-based Artificial Intelligence firm Tanjo about AI – what is it, what can it do, what it means for the world in years to come as a disruptive force.
The video is part of a series, UpTech, from YourLocalStudio which is partnering with WRAL TechWire to publish the series, including full transcripts of the interviews.
Welcome to UpTech Report’s series on AI. I’m Alexander Ferguson. This video is part of our deep dive interviews, where we share the wealth of knowledge given by one of our panel of experts. In this episode, we continue our conversation with Richard Boyd, founder of Tanjo in Carrboro. Richard is an entrepreneur, author, and speaker on a range of topics, from virtual worlds to machine learning, education and healthcare. Here, we ask, where is AI headed? What is its future? And while he says he doesn’t like to make predictions, he does have some very interesting things to say.
UpTech
I was in a car recently with someone who said, “I’m glad that I’m about to retire “because I don’t wanna use AI.” And I’m like, “We’re sitting at an intersection. “You’re using AI right now.”
“What do you mean, no I’m not! “I’m not using that Siri or any of that stuff.” And I’m like, “No no, the traffic light.”
There was a time when, when we first started having automobiles here in the country, where there was a policeman at every corner, at every intersection, who’s waving people through. Eventually we started replacing ’em with lights, and today, hopefully the lights have a little bit of intelligence. Even if it was just the basic intelligence around timing, to time when lights are on or off, but now they have sensors attached to them, so they can detect when there’s lots of traffic coming in one direction, and they can let those people through until someone else pulls up, and then it switches, right?
So when you take sensors and just combine that with basic logic gate sorts of capabilities, that is AI. We just don’t call it that anymore, right, because it’s just part of the ambient ether, now that we’ve had it for so long.
- How are machine learning and deep learning changing things?
If you talk to most technologists, like my partner David Smith or Ken Lane, who’s my CTO, who’d been working with this for a while, they’re like, “Yeah you can call it whatever you want, “but in the end it’s just code,” right? It’s all just code.
Whether it’s rigid sorts of logic that’s been programmed into a system, or it’s behavior trees for characters, to give them sort of branching behavior that begins to look like intelligence, but again, it’s still pretty bounded. Like I said, machine learning though, is, and deep learning, when you start getting into those worlds, it is, to me, a fundamentally different approach to solving problems, that we’ve never had those tools before, and it’s only, from my perspective, it’s 2009, is when I kind of got the epiphany and learned about machine learning. And again, machine learning has existed since, I don’t know, 1958 or something like that, as a concept and as a term.
But the reason it’s different today is because of a lot of people contributing, like some of the basic systems, the basic machine learning libraries. You mentioned that natural language processing, there are text parsers, there are image processors that have been trained on some of the subordinate models of understanding of elements of it, and when they sort of build up and combine, they build something that looks like intelligence. And for all we know, that’s how our brains work, right?
It’s just a whole bunch of small understandings that build up into a larger construct that looks like intelligence. But certainly deep learning, if you’ve got the processing available to you, and you can do those iterative, computational deep dives into raw sets of data, you can achieve some really interesting things. I can tell you that when we’ve experimented with a lot of that stuff, very often it gets very weird. And so you end up getting, if you’ve ever played with Google’s stuff where you actually have DeepMind to actually create art for you, and you can tell it to iterate on things you find interesting, it very often goes into really, really strange directions, that might be disturbing to a lot of human beings. But today with deep learning, you can have systems that create music, create art, beginning to write, although I haven’t seen anything really satisfying there yet, ’cause I think it’s just a, it’s a deeper problem, but I do believe it will be solved eventually, where you’ll have a system that can write like Shakespeare, or Dostoevsky or Tolstoy or anybody else.
We’ve already done that ourselves, where we resurrected Victor Hugo, for example. We had our system read, and we’re not even using deep learning. We’re using what I would call shallow learning, which is just building an interest graph and a sentiment model around reading everything a person wrote, and then everything written about them, which topics have the deepest sort of emphasis, and where are the positive and negative sort of inclinations around the different topics, and then what kind of language do they, like passive language, active language, that kind of thing. And those very simple little pieces put together, again start looking interesting, in that we’ve had Victor Hugo living on the internet, as a, what we call a Tanjo animated persona, or TAP.
I can go visit Victor Hugo every day, and see what he thinks about current events, what he thinks about Donald Trump, what he thinks about climate change, what he thinks about what’s happening in literature and art today. And he has some strong opinions, and he changes over time, which is very interesting. So we’re watching him evolve because just like humans, he’s affected by the content he consumes. So it’s, again, I don’t know, what do you do with that? It’s very interesting.
So I did the same thing, of course with my father. So in 2017 my father died. He was 85 years old, had a very successful life, he was a lieutenant colonel in the military, in the United States Air Force, he won a couple of commendation medals, but he wasn’t on LinkedIn, he wasn’t on Facebook. He did not have any kind of sort of data exhaust footprint, like we were talking about earlier. So instead, I had to take all of his personal correspondence, his military records, OCR or scan all that stuff in, have the system build kind of a weighted word cloud around his interests from that, and then of course I went in by hand and edited. So he’s really a, sort of a model of my view of who he was, right? How accurate is it? I don’t know.
But within the first week of doing that after he died, within a week, I’d created this model of him. And I can go visit him right now, any day, and go see what does he think about, what’s he attracted to, what’s his mind attracted to today? And he’s reading hundreds of thousands of articles on the net and then scoring each one of them and telling me what he’s interested in. Now that was cool, so we had to go to the next step, right, which is what if I could write to him?
So now I can write to him, and he’ll tell me what he thinks about what I’ve written. Now the final step, which we haven’t gotten to yet, is let’s go to natural language processing, where I can talk to him and he can talk back to me.
- How could these new technologies be applied to business?
I know what people wanna do with it in marketing, right? We showed that to Gartner, for example, and they made us the cool vendor, put us on the cool vendor list this year because it is disruptive to marketing. Instead of spending lots and lots of money on focus groups and surveys, create, take all of your customers, however many millions of them you have, or even if you have a small pool of them, and have this create a synthetic population of who your customers are, what are their values, what do they care about?
How do those values and interests change based on current events, or maybe just based on the seasons, or as they move through different stages of their lives? And then ask them those questions. And guess what, the data doesn’t lie. It can only represent itself. And there’s a book out there called Everybody Lies, which was, somebody pointed that to me right afterwards, right after I started talking about this idea. And that’s the problem.
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Focus groups and surveys did not predict Donald Trump. They didn’t predict Brexit, right? What did? Google search data. Google knew what was gonna happen with Brexit, and they knew about Donald Trump before any of the rest of us did. FiveThirtyEight didn’t know because people lie. And sometimes people don’t even intend to lie.
If you say like, “Alex, how many glasses of wine do you have a week?” You might go like, “Oh, no more than two a day.” It’s like, “Well here’s the data from your purchases, “from your VIP card at Harris Teeter “or Food Lion or wherever, “and here’s how many bottles of wine you bought,” right? “That you buy every single week.”
So that data suggests that there’s a different answer to that question. Even though you might think you’re answering honestly. And that’s the power of this stuff. And again, because it’s powerful, we do need to pay attention to how it’s used, who’s using it, and we’re obviously not paying enough attention right now.
- Where do you feel AI is headed? What does the future look like?
It’s likely that we’re gonna see some disruptive point. Now if you’ve heard about this idea of the singularity, Vernor Vinge, the science fiction writer, talked about this first. Ray Kurzweil kind of picked that up and he has Singularity University, and he does singularity conferences. And it’s that point at which AI has gotten so smart that it exceeds human intelligence. And most people who subscribe to that theory think that’s the last invention human beings will ever make. ‘Cause then it’s all about, “Well, “will the AI keep us around “or will they not need us anymore and go Terminator on us?” And we don’t know.
Now, most of us again who’ve been working with it and understand how it works, and we realize that it’s just a bunch of simple things, but a massive set of them that work really well fundamentally at the cellular level. When combined, they create these really complex, amazing capabilities. It’s hard to see that taking over or doing anything really disruptive or achieving anything like what we think of as real intelligence. Although it’s possible, right?
And there are people a lot smarter than me who are concerned about it. Stephen Hawking, concerned about it. Bill Gates, concerned. Elon Musk, he changes his mind all the time, but yeah, so, I think what we’re going to see, in terms of if you wanna look at a 10 year window, and I can’t look beyond 10 years. I think looking beyond five is a little perilous, right? Because things are changing so quickly now. But I would just say prepare for a world where more and more things are automated, and if I’m a young person today, I would look at the career I’m going to choose, and think, “How susceptible is that activity to being automated?”
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And again, like I said earlier, the answer to that question is changing every week, every month, so it’s hard to, really predict which of those are the right thing. But a lot of people think, “Well let’s go into “computer programming because that’s the technology field.” Guess what, there’s been a Darpa program for a while, trying to have AI systems that program and write programs. They can look at previous programs written in Fortran or Cobol or whatever, understand the conceptual process and intent of that program, and rewrite it in JavaScript or Ruby or Python or any of the new languages. That to me, that was something that took me by surprise even.
So when I see stuff like that happening, I say programming is not going to be something immune to disruption or automation. So right now I would say it’s human creativity, that’s what makes us unique. The fact that we can surprise ourselves, create our own little black swans, I think is where we should be focused. But it’s gonna be interesting, and it’s gonna happen fast.
