Transcript
A (0:02)
Hi, I'm Jim o' Shaughnessy and welcome to Infinite Loops. Sometimes we get caught up in what feel like infinite loops when trying to figure things out. Markets go up and down, research is presented and then refuted, and we find ourselves right back where we started. The goal of this podcast is to learn how we can reset our thinking on issues that hopefully leaves us with a better understanding as to why we think the way we think and how we might be able to change that. To avoid going in Infinite loops of thought, we hope to offer our listeners a fresh perspective on a variety of issues and look at them through a multifaceted lens, including history, philosophy, art, science, linguistics, and yes, also through quantitative analysis. And through these discussions, help you not only become a better investor, but also become a more nuanced thinker. With each episode, we hope to bring you along with us as we learn together. Thanks for joining us. Now, please enjoy this episode of Infinite Loops. Well, hello everyone. It is Jim o' Shaughnessy with yet another Infinite Loops. I am very excited to announce today's guest, Ben Reinhart, who is on the o' Shaughnessy Advisory Council and runs Speculative Technologies, a nonprofit lab working to unlock tech that hasn't quite found a home yet. And also, as I learned about it from you at our off site and reading all about it, that often is at odds with a startup mentality. But first, Ben, welcome. You've been incredibly patient with me. We. We've had to cancel this like three or four times in a row and I just keep thinking, wow, Ben is just going to stare at me during the whole thing. Welcome.
B (2:02)
Thank you. I play long games, so this is just yet another version of that.
A (2:09)
Well, let's get into that a little bit. I was really attracted to you and speculative Technologies because I believe that we really have to take as many paths towards innovation and discovery as we possibly can. And I'm very intrigued by the model that you are using based. Am I correct, on darpa? For the most part.
B (2:33)
In part, yes.
A (2:34)
And if you wouldn't mind, for our listeners and viewers, just taking us through what speculative technologies do, does and the goals.
B (2:43)
Totally. So the goal at the end of the day is to get more awesome technology into the world. Right. And all the good downstream things of that abundance and flourishing and going to space and all that good stuff. Right. So that's the goal. And the trick is that there are a lot of constraints preventing a large set of technologies from doing that. And so the way that we are attempting to address that problem, you could think of our model, very broadly, as finding awesome program leads and giving them the tools and resources to sort of do whatever needs to get done to get that technology to a point where it can get out into the world. Right. And so when I say getting out into the world, many people think of spinning off startups, but it could also look like licensing, ip, spinning off a nonprofit, open sourcing things many different ways. And sort of within these programs, we sort of divide them up into four major phases. So the first phase is road mapping. So we really believe that planning is actually really important for successfully building technology. And then during that planning, we identify the biggest risks. That would be like, okay, this fact were true, this technology would be completely worthless. And so we have a de risking phase where we do quick, fast experiments to address those questions. And then there's kind of like the actual build the technology phase. And that could look like everything from coordinating a number of other entities, you know, academic labs, startups, to work together to sort of push the technology forward, but could also look like spinning up a team in house and sort of like the whole spectrum between those. And the last phase is the actual getting the technology out into the world. And I feel like many people neglect that part where they're like, okay, we're going to get it to like, it's going to work and then like, magically it will, it will get out into the world. So we really try to like explicitly build that in. And so I'm happy to unpack any of that, but that's kind of our broad model.
