Time Machine Capital Ltd Founder Philip Walsh and Co-Founder and Director John Sanderson have nothing but enthusiasm for artificial intelligence and its potential as a game-changer in the tech space. The company sources AI developers from mid-tier universities, provides seed capital for AI tech start-ups, and commercializes AI products. Walsh walks viewers through an example of a project from Time Machine Capital’s portfolio: a subscription-based, music editing program designed to quickly add soundtracks to short videos with applications for YouTubers and other social media users. The company is going public in Q4 of 2018 and the pair believe that the portfolio investing Time Machine Capital offers is a softer way for many retail investors to enter the AI space.
James West: Hey, welcome back. My guests in this segment are Philip Walsh and John Sanderson; they are both directors and co-founders of Time Machine Capital. Gentlemen, welcome.
Philip Walsh: Thank you.
James West: Philip, let’s start with you: tell me, what does Time Machine Capital do?
Philip Walsh: So we are an incubator of artificial intelligence technologies. We started in the UK, and John and I have been talking about bringing a lot of what we do to North America. Canada is a great place for us to do that, so we incubate and provide seed capital to artificial intelligence technologies.
James West: Ah, so this is an AI investment bank?
Philip Walsh: It certainly is.
James West: Brilliant! I’ve been waiting for one of these to come through. Now, John, you’re a Canadian, and you’ve got some experience in the artificial intelligence space through your previous relationships?
John Sanderson: Well, my previous relationship was a business specialized in ERP resource systems – enterprise resource systems. And I exited early this year, and about beginning of 2017 I started looking at artificial intelligence, and Montreal just seemed to be this epicentre of where all this activity was happening. And our conversations with Philip just aligned and, you know, being a tech guy, and AI coming in, this was the area to reinvent some of the technologies that are out there right now.
James West: So you guys have a business model, as I understand it, where you’re sourcing artificial intelligence technologies that are evolved through universities around the world?
Philip Walsh: Yeah. So we started – in fact, both of us are very strongly connected with mid-tier universities, and we started in the UK a few years back with mid-tier universities where the opportunities are more substantial because some of the bigger universities typically have well-organized alumni and, if you like, a chain of connections that allow them to access capital in the markets quite easily; whereas in the UK, we found that the mid-tier universities were struggling to find ways in which they could get some of these technologies to market, partners to commercialize them. And then in conversations with John, I realized that actually it’s a similar setup here, albeit smaller. But in the UK we are now, given what we’ve managed to produce out of our current portfolio, we are now being approached by some large universities. So we’ve started engaging Cambridge University, for example, in the UK, which I was quite surprised about.
But at thee end of the day, I think there are so many opportunities to bring to market that people are looking for anyone that can help them, both raise the capital correctly for them, and bring them to market. So a lot of these technologies come out very early. The talent is the hard part to find, and nurturing that talent and bringing things to market in AI is what we see as the future in – well, we see this as the next wave of computing, as many people do. And so from our point of view, we’re going to be busy for the next several years.
James West: Sure. Okay, so it sounds like you’re going to start to put together a portfolio of different AI projects that are ultimately going to be incubated until the point of commercial viability? Do you have any examples you can start with?
Philip Walsh: I do, actually. In fact, if it’s possible to put one up on screen, I can show you an example.
James West: This must be a clip! What have we got here?
Philip Walsh: So let me show you what this is. This is actually a music technology that was brought to us by a university in London, and it is the first technology that allows music to be instantly edited to video by anyone. What we’ve actually done is, using artificial intelligence, we’ve effectively iconized music expressions, and we map this to a video that you just drop in, so you drop in your asset, which in this case is a video; you align your icons to the story line on the timeline; and then you are able to select from libraries that we are now engaged with across the globe, actually – Sony, Warner, BMG, Universal, and others – you’re able to drop in a soundtrack for this film instantly.
So what you’re looking at here typically would take half a day in an edit suite; we can do in about a minute.
Now, the implication of this is, there are 2 million, in excess of 2 million YouTube channels that purchase music today; you’ve got professional YouTubers that are trying to add music to videos all the time, be they DIY programs, cookery programs, etcetera. You’ll now see, as this plays the soundtrack, that effectively, in a minute, you’ve created a soundtrack to this video.
Now the really interesting part is, as that music plays to this video, and I’ll let that play in the background, the point being you’ve written the story board and now you can drop in any track. Each time you change a timeline or a track to this type of video, again it’s probably a half a day or more; it changes the entire world for creators. It allows all of us to be instant creators. We’re all taking videos all day long with our iPhones and other phones, but we can’t add music to those videos and post them on social media.
James West: Right.
Philip Walsh: This technology allows you to do that.
James West: Okay. So how is this going to be monetized?
Philip Walsh: So we are launching with a subscription model for this technology with some big labels; they are quite keen for us to use the catalogues. As a result of the AI technology, which this is the interesting part about AI, is once you start down the road in AI, you discover that the AI capabilities start to become more broad. So for example, the ability to add, again, any soundtrack to this video instantly, also means that the AI in this instance has become something that can use the DNA of a track, because it’s what we do ultimately at our core: we break these down and reassemble it, to identify the types of music you’d be looking for.
So in this instance, this application would allow any creator to, as I say, add music to video for a subscription per month. It’s very difficult to do today. If you actually created a video today, wanted to launch it on YouTube, buy music, edit it and post it, it’s a very difficult process, and typically you’d use multiple third parties in that instance. You’d go to a third party website to buy the music, you’d have to audition the music against your videos, you might use an edit suite. You’d then go to catalogues; trying to buy a track for what your usage requirements are is also complicated.
Then you need to edit the music to the video, and then you’re going to post it. In one application, you can do all of that within one ecosystem.
James West: Okay, so we produce a lot of video here; we’re actually at work on a feature-length documentary, but we also produce mini branded content pieces for companies, and we use a service which is a monthly subscription service that gives us free access to a deep catalogue. Would we be able to use this in that scenario?
Philip Walsh: You certainly would. We would pipe that catalogue into this application, which would allow – this is very good for short-form video, which is obviously the way in which the world is moving. So when we originally got involved with this technology, half the world believes that ultimately music will end up in the hands of artificial intelligence that generates music, known as generative composition, with companies like Amazon playing big roles in there. You’ve got Alexa in your house; you might ask Alexa for a playlist, or jazz, and you’re not necessarily sure whether an artist is behind that music, whether royalties are being paid to that artist, because you’ve just got the playlist coming out of the speakers in your house.
James West: Sure.
Philip Walsh: The other application of AI, which we are favourable to as we launch, is using existing music and allowing people to edit that music to any content, short-form content, typically, which could range from you’ve got a child’s birthday that you want to take a video of and you have a favourite soundtrack. You want to be able to take the track from your streaming service, drop it onto the video, have it auto-resize itself, and then post it to social media and it not be taken down.
Or, you might be somebody that takes a lot of care on your videos, GoPro users for example; you’ve done a tightrope walk in China and you want a good soundtrack to it. Typically, you’ve got the footage from the camera, and now you need to add music to that video. So in that sense, this is an application that will allow you to do that very quickly and easily.
James West: Okay. So Time Machine Capital has made the fundamental initial investment in this company, and is now in control of it?
Philip Walsh: Well, we are, as time moves forward…
James West: Time Machine…
Philip Walsh: Sort of what we do is, we provide the seed capital and we bring it to market, then we bring third party investors to our propositions. And obviously, by natural causes, we dilute our shareholding as we bring third party capital in. So we are, for example, on that investment, we’re up 500 percent on today’s valuation of the company; we can see that doing another couple of financing rounds in the next year or so.
James West: interesting.
Philip Walsh: Where we could increase our value of that investment again, 3, 5, 7, 8, 10-fold.
James West: Sure. And you have a pipeline of these types of projects?
John Sanderson: Yeah.
James West: Okay, interesting. And you’re going to go public here at some point, in Q4 2018?
Philip Walsh: We are. Very much looking forward to it, on the CSE here.
James West: Oh, fantastic.
Philip Walsh: And we’ve received a great deal of support from everyone here, actually, the entire community. It seems that at the moment in Canada, there is a real governmental push – John is closer to this than I am, but a real governmental push behind technology, but specifically AI. And we are definitely the beneficiaries of that in the sense that there is a lot of interest now being seen around the understanding of artificial intelligence. I think a few years ago, people weren’t really clear on what artificial intelligence could mean; the implications of artificial intelligence. I think that’s changing over time, and we are early to that curve, and well positioned to take advantage of it.
James West: Very cool. And so John, you’ve got a relationship base in Canada with the universities that might be a source of additional projects for the pipeline?
John Sanderson: Correct.
James West: What is the environment in Canada that makes you enthusiastic that there will be a steady supply of quality projects to this pipeline?
John Sanderson: There’s multiple levels where that is being incubated. So at the government level, you know, the Ministry of Science and Economic Development has implemented the super clusters, and there’s approximately about five of them across the country right now.
James West: Super clusters? What is that?
John Sanderson: They all have different specialization uses in applications from supply chain to FICO or Fintech.
James West: Under the AI umbrella? Okay.
John Sanderson: Exactly. So it’s a way for them to see what’s happening across the country, as well as through the incubators that they’ve set up and the government funds incubators within universities, and non for profit incubators as well. So they get a sense, and they get to see with applications of funding through government programs like NSERC and others, they’re able to see clearly, you know, get a picture of what’s happening in AI across the country, and then develop the regions, make sure that rural areas are being cultivated properly as well as having a firm handle on where their economic interests can lie, and where heavier investment or less investment is needed.
James West: Interesting. Okay, so I want to finish this off with, one of the biggest problems I have with different investors when we talk about artificial intelligence is, understanding what is artificial intelligence? So, I mean, from the standpoint that a computer is a form of artificial intelligence, one would argue, but where all of the inputs and all of the decisions are made by human operator. At what point does something like a computer technology become an artificial intelligence technology?
Philip Walsh: I’ll give John half of that. I’ll take the first piece, which is, one of the reasons we set up Time Machine Capital was actually to allow investors – we had many questions that we fielded around this area, and the reason we set up Time Machine Capital originally was precisely because so few people understand artificial intelligence, that actually allowing them to come into a portfolio of opportunities is often much easier. It’s a softer way for people to find an entry point into investing in artificial intelligence.
Most people realize there’s something going on. There’s something happening, it’s very big, it’s very important, governments are talking about it, everyone’s talking about the implication of it, and the question for a lot of people was, how do I get involved? How do I find a way in? So that’s why we set up Time Machine Capital in the first place. As to, John, I’ll hand over to you, as to what it actually is, the essence of this, because it’s a very good question; very few people –
James West: Usually I just pretend I know, but since you guys actually do know –
Philip Walsh: It’s a very, very good question, because I think many people would have different answers to that, and I’ll throw it over to John only because it’s a difficult question.
James West: Right. [laughter] Your turn.
John Sanderson: My answer will be one of a thousand answers, right?
James West: Sure.
John Sanderson: So I guess in a nutshell, is, what can a system learn? If we talk about, you know, we talk about AI as if it’s a person when we’re having discussions: Oh, well, AI will do that, and AI will do this. So, what is it that it’s learning? So it takes data, whether it’s visual data, it turns it into ones and zeros; whether it’s sound data, and turns it into ones and datas, and can do statistical predictions. So anything that we think that we have intuition around, the computer will know statistically that it’s correct.
So if it’s, whether it’s editing video to sound, it knows that through the sound footprint that there’s a peak point here, then there’s a peak point in the video, then, you know, these algorithms work to get these done. And these, you know, the real premise behind it is, what is AI? AI is being discovered in laboratories with scientists and researchers, and then those findings are actually being applied by us at Time Machine for other purposes. So we’re taking, Hey, what can we do with that sound algorithm in AI? And Time Machine has built, or Match Track has built, a suite that edits music to it.
James West: Right.
John Sanderson: So this is what we’re doing: we’re looking for unique, really highly commercial applications that we can take science and apply to in the real world.
James West: Okay, so it doesn’t imply that the machine is conscious?
John Sanderson: It could, it could, because there’s, you know, different kinds of learning. So there’s supervised learning, there’s semi-supervised, and then, you know, in cases like at Facebook or at Google, there’s unsupervised. And then that’s where –
James West: So the machines are allowed to learn whatever they want?
John Sanderson: Correct.
James West: Okay. So this is now the final question, because on the one hand, you’ve got Elon Musk warning humanity against unbridled development of AI because this is the biggest threat to humanity; and then you’ve got Mark Zuckerberg over there saying that, no, no, no, AI is fine and we’re just going to continue to develop it and freely so, because this is a free market economy. Which of those is more accurate?
John Sanderson: It’s whether guns kill people or not, right? It’s the hands that they’re in, perhaps.
Philip Walsh: Yeah. My personal view is that there are many good things that can be drawn from the application of artificial intelligence. I don’t believe there is a huge negative to this, anymore so than there’s a negative to any technology or innovation that’s created for, if it’s used for good; if it’s used for evil, it’s used for evil. At the end of the day, it’s people that will ultimately make that decision.
So you know, there’s an argument to say that it’s not really about the machines making that conscious decision, it’s where we take them from this point onwards. So they’re all very good, they’re very valid points. From our point of view, we’re not really doing the evil stuff; we’re going to focus on commercializing the fun stuff and the interesting stuff, and I’m sure there are people in different places that have to worry about this, and they think about that every day. But I think AI is potentially a huge benefit to mankind across the board.
James West: Okay. And a great economic opportunity in the meantime, I guess?
Philip Walsh: Absolutely.
James West: Okay. [laughter] All right, we’re going to leave it there, gentleman. Thanks very much for joining me today.
Philip Walsh: Thank you very much.
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