Time Machine Capital Founders on Incubating and Accelerating AI Opportunities
Time Machine Capital is an investment company focused on accelerating and commercializing early-stage AI opportunities. Time Machine Capital Founders Philip Walsh and Dr. Joe Lyske provide an update on the company and discuss the importance of AI. Time Machine Capital prioritizes products designed to enhance music editing, sports training, and a variety of financial services. Walsh and Lyske demonstrate the value of a program that allows creators to quickly add appropriate music to their videos using AI. They discuss the benefits of AI and highlight that artificial intelligence has broad applicability in industries as varied as music, media, sports, health, and finance. Time Machine Capital has 24 opportunities in its pipeline, in addition to its existing portfolio. The company cultivates relationships with mid-tier universities and sources developers by sponsoring PhD students, gaining access to valuable research. The pair note that Time Machine Capital is in the process of going public in Canada.
Narrator: Time Machine Capital is a privately held investment company focused on accelerating and capturing IP around applied artificial intelligence technologies. The company sources AI developers from mid-tier universities, provides seed capital for tech startups, and commercializes AI products.
Time Machine Capital currently builds cognitive products for music editing, sports training, social commerce, and financial services.
James West: And, as promised, half of the founders of Time Machine Capital are sitting with me right now. Philip Walsh joins me.
Philip Walsh: Hello.
James West: And Philip, quickly, what is Time Machine Capital?
Philip Walsh: Time Machine Capital is an investment company that is in the process of going public in Canada, that focuses on investing in artificial intelligence opportunities.
James West: Fantastic. And, tell me about where’s your, like, what’s, how did you come up with this company?
Philip Walsh: So I sold my last company, which was in fintech, and I wanted to – at the time, AI was starting to enter that market in a big way. I wanted to invest in artificial intelligence opportunities, and it just so happened that the first opportunity that came on was through Dr. Joe Lyske – we’ll meet in a minute – which was an artificial intelligence in music opportunity which found, for me, it found resonance in not only my love for music, but the fact that fintech is a little bit less interesting than the music industry.
James West: Right. And so you’re the brains behind the operation?
Philip Walsh: No, no, I can’t claim that. I can’t claim to be the brains behind the operation; the brains are actually Dr. Joe Lyske. Although, Dr. Joe Lyske –
James West: Dr. Joe Lyske? Where is he?
Philip Walsh: He’s found himself a keyboard somewhere, so he’s doing what he does best.
James West: Play it! Wow, that’s – so that’s the brains behind the operation?
Philip Walsh: Yes.
James West: And he’s playing live from, where is he, in London?
Philip Walsh: No, he’s actually here, he’s actually in your studio. I think he’s found a room somewhere around the corner, and he’s commandeered one of your keyboards.
James West: I can’t hear him in the feed. Should I be hearing him in the feed, or is it just going straight out? [applause] All right, brilliant!
Philip Walsh: Hold on, Joe.
James West: Let’s have Dr. Joe Lyske join us now. That was well-constructed. [laughter] Right off the top, there! Dr. Joe. So not only are you a PhD computer scientist?
Joe Lyske: Computer science, electronic engineering, yes.
James West: Computer science and electronic – double PhD?
Joe Lyske: Well, it’s just a department.
James West: Oh, I see. And also concert pianist.
Joe Lyske: Not concert, no.
James West: Well you just gave a concert.
J.L. Enjoy with you. [laughter]
Philip Walsh: Exactly.
James West: All right, so tell me about Time Machine Capital. Sounds great, like you guys are making investments. You’re a merchant bank for emerging artificial intelligence, you’re an incubator and an accelerator, and you participate in these things financially all the way and then spin them out, and on to the next one?
Philip Walsh: Yeah. So I’ll – in fact, why don’t you start with how we acquire the opportunities that we acquire, and then I’ll give an example through the music tech company, MashTrax, as to what we’ve done and how that looks, and how that’s the model for how we go forward.
Joe Lyske: So incubation accelerator suggests something slightly different from the way we operate. You want to think of us more as creating seeds. Everybody knows how to fund a company with seed capital and so on, but how do you make the seed? What are the ingredients that go into making a successful seed, something that is going to flourish and going to work?
It needs interdisciplinary knowledge in between artificial intelligence and some other element, be it music, be it sports and leisure, be it financial technology – but it also needs all of the operational components around it to support it. So that’s really where Time Machine Capital fits in: it puts everything together to create the most successful seed possible, and then it waters it.
James West: Okay. So one of the challenges investors have understanding AI, artificial intelligence, is how it is applied to either existing functions, and its dearth of computing power brought to bear on problems that couldn’t have imagined such a ton of computing power brought to it; or, it’s a new thing that is only made possible by artificial intelligence. But in both cases, artificial intelligence is an ingredient that powers some other function in a business.
Joe Lyske: It is. It’s also – the better way to think about artificial intelligence is actually as a by-product of studying cognitive psychology. So if you look at anthropology, the way that people act; if you look at linguistics, if you look at psychology and philosophy, and you look at all of these components, if you can make a breakthrough in any one of these areas, you realize that the by-product is Hey! We can program a computer to act on that behaviour, and act on that information.
Philip Walsh: Right.
Joe Lyske: So AI itself is more of a by-product to these other components. There’s this famous thing called the AI effect, which essentially is, whenever we can explain something through AI, it ceases to be AI. At that point in time we say, Oh, that’s not AI, that’s just an optical character recognition or that’s just driving a car up a road, you know.
So AI’s this kind of moving thing of the unknown, which is fuelled by all of these other components in cognitive psychology.
James West: Right.
Joe Lyske: So, you know, in this very point, if you have a company which has got a good seed of interdisciplinary knowledge in an area, AI becomes a natural way of extending that.
James West: So, using this as an example – we’re looking at one of your products, MashTrax – and this, how does this work?
Joe Lyske: Okay, so this is interesting. What we’re doing here is, we’re putting the mind, the music editor, into a computer. So this is a very difficult skill for people to have; even editors of programs and so on, it’s very rare that they’re good music editors. So what we’ve done is, we’ve taught the actual machine how to perceive music, and then we can use this tool to establish briefs. We simply describe the story independent of music, and then once we’ve described that story, we can say, Right, give me an independent track now and let me evolve a solution for that track which is unique, so that brief, which is unique. And then it finds the most accurate way to be able to fulfill that.
James West: Right, so you end up as a producer of music for film, you end up being efficient with the capital requirement for the music because you’re only licensing that small bit, thanks to your AI identification and alignment tool?
Joe Lyske: Yeah, it helps you identify music that you can source from providers much quicker than conventionally. So one of the things that this tool allow you to do is drag in what they call a Tempt Track, so, something you can’t afford, like a piece of Madonna or Coldplay and you can’t put it on your video. So you can drag it in, and it can listen to it and analyze it and say okay, what are the emotional properties behind this track, and how can I take a substitute, which is purchase-able, and then put it in its place.
James West: Oh, very interesting. So then, in terms of your business model as a merchant bank, how does a technology like this become a contribution to the investment upside of an investor in Time Machine Capital?
Joe Lyske: So yeah, do you want to –
Philip Walsh: Yeah. So there are a number of ways in which we see the future value being created within the company. Sometimes, the AI that we invest in will be patentable and license-able to companies that we don’t need to create products and services for; in other cases, it will be products and services. In some cases there might be a trade sale; there might also be an opportunity for some of these companies to be spun out as more public co’s, in which case we can offer the current investors in the company the opportunity to participate early in those spin-outs.
So it’s not, we don’t have a fixed view on the way in which value is created, so much as we’re going to look for every opportunity possible to create value. As the largest shareholders and co-founders ourselves, the number one priority we have is making money from this venture.
James West: Right, great. That makes me want to be a shareholder, which I’m probably going to be. [laughter] So, tell me about some of the other projects that you have besides this. Well, actually, before we move on to that, so, who would be interested in acquiring this project?
Philip Walsh: Okay, so given the fact that, in essence, what that technology is capable of doing is empowering anyone that creates to create the greatest music videos or the greatest videos with soundtracks attached to them, you’ve got everything from professional YouTubers all the way through to consumers that say they’re using Instagram Stories, they want to be able to create fantastic soundtracks around their videos.
So in essence, I’m pointing already to the sorts of companies that would find that technology very valuable for their customer base, their footprint of users. So we have companies in the world that already create tools that perhaps don’t reach the mass market; that might be somebody like Adobe, where they’ve come from the professional market down to the recognition that short form video now requires a different way of approaching it.
If you’ve got a 14 million following on YouTube and you do most of your videos, you’re a young kid, you do most of your videos on mobile in a skateboard park in LA, you simply don’t use edit suites. You don’t use editing tools on a desktop; you want to go straight to broadcast, effectively, on a platform like a YouTube. We’re the only answer to that. As it stands at the moment, it’s patented, so we’re recognized by the industry as something that adds a lot of value to them in the way that the entire world is moving forward toward.
So in some cases, we’ll end up with projects that we can license to companies that, as I say, they might want the tech, they might want the IP, they might want the team. So we’re seeing all kinds of opportunities here for different ways in which AI applies itself to the marketplace that we’re in.
So on that particular note, we’re in three distinct areas: we are in music and media, sport and health, and financial, fintech, which is some of our background, some of the people that invested in the company, are really fintech people.
James West: Right, okay. So how do you source your technologies? Where you find these technologies?
Joe Lyske: So, one of the great things that we can do is, we have these relationships with the universities themselves. So we can see IP which is coming through those universities. We’re also moving into the position now where we’re sponsoring PhDs in specific areas which are of interest to us, and that means that we are getting constant papers and research and breakthroughs being made over a period of time in a certain area, and it also means that of course as the sponsor of that PhD, we get to own the IP.
So moving forwards, it means that you’re actually always – one of the biggest challenges here, of course, is if you have a successful company and it spins off, how do you keep a core team to keep going on other propositions? We’ve had to solve this one. So the solution to that has been to find at earlier stages, individuals coming from the universities and bring them into the team, so you have a constant kind of flower bed of new talent coming through the AI lab and being able to spin out for the propositions of their intellectual property.
James West: Very cool. Okay, so how many of these opportunities are currently under incubation, acceleration, in the Time Machine stable?
Philip Walsh: Okay, so we have four. We have another two that are, that we are now looking at and bringing forward, and we have a pipeline of about 24 that we like. As you can imagine, there are opportunities in this space that we get presented with a lot; in fact, some of the universities we work with now present us with opportunities very early on, as somebody just recognized in the marketplace as having taken effectively soup to nuts, some of these projects to market.
So we are seeing an increasingly large pipeline, and what we’re also seeing, which is probably a feature of the landscape across the board, is that unlike in previous times where universities were very closely tied to corporate finance or corporate financing, corporate support of certain PhDs, some of today’s young tech university grads are less willing to be aligned with a large corporate that perhaps they don’t share the same values of. And therefore those universities are now looking to other partners to work with.
So we’re now seeing so many more opportunities that we can bring to market, that really is a question of how do we keep up with the opportunities that people are now bringing to us. So there’s another one of our challenges. We’ve solved some of them; one of the bigger ones is going to be, how can we make sure that we address the number of opportunities that we actually have.
James West: Okay, so that’s how you attract the projects; how do you capitalize the acquisition?
Philip Walsh: So in terms of the value recognition, or in terms of –
James West: In terms of the business model.
Philip Walsh: Right. So we have a process by which, we have an outreach program, effectively, that allows us to identify and run a series of capability qualification criteria, if you like, in our business, to say, Do we – let alone whether the opportunity itself could be the best thing since sliced bread – do we have the ability within our organization, or our network, to address that opportunity?
So we run it through a process, then we have a scorecard. That scorecard then feeds us with data points. The data points might be, what’s the market opportunity, what’s the market size for this? Who else is playing in the marketplace? Can we file for patents? What protections can we create around these things?
So if it’s really – quite often people talk about AI and everyone says they’ve got AI, as you can imagine. It becomes the new buzzword.
James West: I had AI. I got rid of it. [laughter]
Philip Walsh: There you go, exactly, yeah. Well, we’ll give it back to you. [laughter]
James West: Well, now I’m going to invest in it.
Philip Walsh: Yeah, exactly. So some of the time, you know, people talk about AI and they’re talking about algorithmic-based programs that they’ve, or code that they’ve built within their organizations. We’re talking about something else, here. We’re talking about things that learn; things that are capable of starting to do amazing things in healthcare and other areas. So from our point of view, we are in a situation now where we have a window, and we have a situation where AI is on the up. If we can gather as many of these things as we can now, and we scorecard them to recognize that we are capable, or at least we’ve enhanced, we’ve got the – we have the greatest likelihood of making a huge success of these projects because they fit the criteria that we ourselves put down, then there are infinite opportunities here.
James West: Right.
Philip Walsh: Big companies are looking at this all day long, but big companies are big companies; we’re not. We’re nimble, small, friendly…hopefully…
James West: Friendly? You seem quite friendly. [laughter]
Joe Lyske: Also say, one of the core things about the scorecard itself is, if you think about any investment, that investment itself is really a punt on trying to predict the future. You’re betting on something and saying, Well, I’m looking at all the information and I’m hoping, from my perspective, I think this is going to rise, which is why I’m going to back it.
Well that, actually, that prediction of the future is the sole and kind of only reason for intelligence. So intelligence is there to help you predict the future.
James West: Knowing what’s going to happen next.
Joe Lyske: Well, at least trying to figure it out. So if you have a company which, at its core, is creating components based on artificial intelligence, then the very question itself – that investibility and trying to predict the future – is core to the company, and I think that’s a differentiator.
James West: Yeah. No, it’s a fascinating space, and it’s why I’m so interested in what you guys are doing, and why we will continue to follow this story with interest. Thanks for joining me. The next time we have you guys, it will be in London, I believe.
Philip Walsh: Excellent, excellent!
James West: And that’ll be in May or sooner.
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