Hello, everybody, and welcome to the Financial Samurai podcast. In this special episode, I have with me Ben Miller, co-founder and CEO of Fundrise. And we're going to talk about venture capital and what's up with the innovation fund. Welcome to the show, Ben. Thanks for having me. So last time we spoke, you were all bulled up on real estate, which was a little bit different from where it was a year ago, two years ago.

So what about venture capital? What's the latest happening in AI, innovation fund, and what are you all up to? So private tech investing is so different than real estate investing. Real estate is largely macro-driven, but technology can-- it's transformative, at least great technology companies. And so you can invest into a company that could change the world, and we could be in a depression.

And so it's much more about getting into those great companies than it is like the sort of-- I mean, obviously macro matters because tech multiples in 2021 were crazy. So I'm not saying that it's only the companies that matter, but it's a very different dynamic. And so we were lucky, we had two things happen to us in 2023.

Basically the tech fund launched and we came into the market near the bottom of venture. Venture basically, I think, bottomed in '23. The second thing we did was we ended up getting into among the best private tech companies in the world. Can you name some of them? Yeah, I can name them and we can talk about it.

When I launched this tech fund, I had some naysayers. Sure. And the venture industry in particular said, "Well, you can't get into the great companies." That we did, which is really, really gratifying. And so let me break them up into categories and we can talk about the specific companies.

So basically the big thing happening in the world right now is AI. And so we pursued AI investing in sort of three ways. We invested into the AI companies directly, and those are like the big, large language models. We invested about 15% of the portfolios in the top AI companies.

We then invested in the data infrastructure companies. And data infrastructure, if you're not a tech person, one way to think about that is that in a gold rush, you can invest in the gold mine, or you can invest in selling picks and shovels to the gold miners. So data infrastructure is the picks and shovels strategy.

So everybody who is working on AI, one way or the other, needs data infrastructure, because data is the lifeblood of AI. And about half the portfolio is in data infrastructure. So the majority of it is in the picks and shovels kind of strategy, which is more consistent with my view about investing.

And then the third category are the vertical SaaS, or the applications. And we invested in a bunch of really good applications that are dominant players in each of their categories, but I think are amplified. And then we had a little bit of other things, but that's like probably 90, 95% of the portfolio.

Oh, wow. So what percentage would you say the portfolio is exposed to AI? I mean, I really have to look at it specifically, but I'm going to say over 90%. I mean, it must be close to 100%. I mean, basically, we can work backwards from the vertical SaaS companies for a second.

But like if you take a vertical SaaS company like Canva, so we invested in Canva. Canva is democratizing design. And this is actually what technology does, it takes something that was really expensive or only available to a few people, and then makes it available to everybody. And like, that's what, you know, E-Trade did with trading, right?

There's so many examples. So Canva is the dominant, absolutely dominant player in that space. I don't even, I don't even think it's close. Just to put some numbers on it for you, like Adobe has a quarter trillion dollar valuation, I think it's 250 billion last time I checked. And Canva, if you go on Google Trends, Canva has just absolutely surpassed them on Google Trends.

And they're only, I think Canva's valuation last time I checked was like 25 billion or 10 times less. And if you think about AI, if you go in or you and I go in, we're going to build do some designs for this podcast, like AI's ability to edit this podcast, produce transcript, produce notes, produce designs for it, help us distribute it.

I mean, that's all part of what AI is going to do and doing. And Canva is like going to be, I think, the dominant design solution for the sort of next generation. Yeah, I was kind of skeptical of AI a year ago, and I was like, oh, you know, it's like plagiarism and copying stuff and doing all that.

But now that I've used some of the tools to do some editing for grammar, clarity, idea generation, it's really increased my productivity. So I guess the question that I have for our children, because my kids are four and six, six and a half, is will AI be so revolutionary that it's going to take away millions of jobs and leave our children underemployed or unemployed, making college and grade school education kind of not very valuable?

Or is it not going to be that revolutionary for those who are able to use AI and therefore be able to be more productive, make more money and be more free in their lives and their careers? What's the take 10, 20 years in the future on how AI will impact our children's lives?

Oh, man, that's, I feel like I can just repeat the smartest people out there. I feel like it's a progression from the latter thing you said to the former. So I am a believer of the Raker as well, you know, the singularity or the way that the chief science officer at OpenAI talks about it, Ilya, is that the neural network, it does replicate a lot of the way the brain works and it's really like, it is a scaling challenge mostly.

Like if we can scale the compute and the, you know, algorithms and things like that, I think we will see like a surprising amount of progress. And that's what, I mean, it's sort of everybody's seeing AI go up the hockey stick rapidly. But then the nature of technology is that the last 20% ends up taking 80% of the time.

And so we're going to see rapid progress and essentially, when does it slow? When does this sort of like the linear scaling benefits run out? Like not anytime soon. And I think the actual challenge is not so much the technical capacity of, we're calling AI, whatever you want to call it, GPT.

It's actually the application, the human, changing human behavior. Like look at Zoom, the second the pandemic happened overnight, everybody changed their behavior and video became part of how we interact in work and life. And it wasn't true before. So human behavior is actually the limiting factor, changing human behavior.

My parents shopped at department stores and my kids don't know what a department store is. I don't think it's actually going to be the application and the political and human dynamics and the technology is going to keep making pretty awesome progress. And it's just going to end up being different than what we think.

It's not going to be a human being. We're going to have some complimentary, I mean, it's going to be really good at precise computation and recall, which we're not so good at, right? But exactly where we're better and where they're, I mean, the computer came along, changed how we do work, made us more productive, didn't obviate the need for jobs, just created a different kind of job.

Yeah. I just remember being in school. There was like the HP 12C calculator, the scientific calculator, and those who knew how to use it were like math geniuses. And then those who didn't know how to use it like myself were just duds. And I remember quitting math after sophomore year in high school.

So it feels like the lesson is you better get on board with AI and you better learn how to use it for your job. Otherwise you're going to be outcompeted against by those who are more productive in knowing how to use AI. Yeah. I actually think it's not really a lesson for our children because they definitely will.

It's really a lesson for people our age and, you know, if you're 20 or 30 or 40 or 50, like if you're not embracing it, yeah, you're going to have a disadvantage. And so just talking about Fundrise for a second, I think that's also true for companies. Having built a company, I find companies are like people, they age, they go through maturity, they have like cultural or personality quirks.

And so our company Fundrise, we have a team, we're building with AI and we're lucky because real estate, most real estate organizations have zero software engineers, like let alone, you know, a guy within a machine learning masters and things like that. So we're lucky to be at this intersection between tech and real estate when AI comes along and, you know, we've been messing around with it for a year.

And for the first 10 months, like we had nothing, we just didn't have any way to use it. And it just was like a kind of, as you said, you can use it for like summary and, you know, pretty silly. They're fine, but they're not like world changing, but we just were like, okay, we're hacked away at it.

And it's also how I got really, like both really confident about the kind of venture investments we made, because we were building and using the softwares. And also how I think about the trajectory of it, because, you know, we set up, you know, we have an open AI API access, we've produced things with it, things we produced were crap.

Then we had to produce again, and then we realized we needed data infrastructure, we got the data infrastructure. So like, you have to use it and like learning the piano or something like, at first you're terrible. Yeah. But you basically like too bad, you just have to keep going at it.

Yeah, you got to keep going at it. And the toughest thing is, the older you get, I'm 46 now, the less you want to learn something new, right? You want to learn new tricks. It's tough. But you got to really force yourself if you plan to be productive, have a job, be an entrepreneur, you got to learn how to use it, folks, because the productivity gains are significant and everybody else, at least the younger folks or the hungrier folks are learning how to use it.

And in terms of profitability, it's interesting, because you follow the open AI debacle with them outing Sam Altman and bringing him back and those debate, and now the New York Times is suing open AI for plagiarism and using its content illegally, I guess. It sure seems to me that open AI, for example, is highly profit driven, because they started off as a nonprofit to help all of humanity, you know, they're talking about using AI to help cure disease and sequence this DNA and all that stuff.

But now it seems like it's about max profitability. What are your thoughts there in terms of running a business and also helping humanity? I think that's good. It's like when I hear about a pharmaceutical company that invents something that saves millions of lives and they get really rich on it, I'm like, great.

So I mean, the reality is that, I mean, look, I'm not some libertarian when it comes to recognizing the need for regulations, but capitalism drove more people out of poverty in the last 30 years in China and Korea. So I think that we're much better off with an open AI that is focused on delivering for the customer and getting paid for it than a government, you know, I'm sure China has basically like a government version of it, and I just don't expect it to move as fast or be as good.

But I mean, I can see also why you basically better have good government control over the extreme outcomes that could happen. Yeah. This is more philosophical. I thought we were going to talk about like the portfolio. I feel like the stuff I'm saying, like everybody who's in the space who reads this stuff and like works with software kind of knows this stuff, but maybe I'm like too much of a nerd or something.

No, I think investing, I mean, do we really want to just invest to make money? I mean, I think we need to invest for a purpose. We need to use our gains for something. And I'd love to talk more about portfolio. So the construction of the portfolio, you know, private growth companies, different verticals, it looks like 90% exposure to some way to AI.

I mean, if you could drill down to pure play AI companies though, what percentage of that portfolio are those pure play? Just as I said, depending on when this podcast comes out, I believe that AI is the revolution, you know, exactly how you feel about valuation and how many models there'll be, we can debate.

But I thought it was important, valuable to have exposure to those companies. So we worked to get investments into what I think are the top AI companies. And that took some doing. It's 15% of the portfolio. So it's not, it mostly the data infrastructure and applications are where we invested, where I think they're much lower risk.

I mean, this company, I hear some stats, I have our average or weighted average, if you sort of dollar per, the weighted average by amount of dollars invested is a 70% annual growth and over a billion dollars in revenue. So the point of the portfolio is that these companies are like not startups, they're like rat growing mature companies.

And that's basically the best kind of venture, in my opinion, is usually you can't get into those companies because yes, you can get companies that are, you know, you wish you could get open AI at the startup or you wish you could get whatever Uber at startup. But the problem is you also get a hundred other ones that aren't.

Sure. So you're saying that later stage investing in private growth companies is more attractive because it has a proven roadmap, it's growing revenue, it could be generating cashflow. And the thing is you can't get in because everybody can see the trajectory of the company's growth and everybody wants in, but only a certain number of institutional investors or individual investors can invest.

We got in, which was the part that the venture community said was impossible. We were fortunate and lucky because in 2023 there was enough disruption in the market that we could basically provide a solution and capital and a differentiated approach that allowed us to get access. And now we have that portfolio, hopefully we can then compound that success and those relationships with those companies to do it again.

But you know, if you look at the portfolio, I can list some of the companies that we invested in, as I said, Canva, we invested in ServiceTitan, we invested in, here's one that's interesting, Anduril. Familiar with them? No. So Anduril is application of AI to defense. Defense. That's big bucks.

That's a well that keeps on giving. And I believe, they are aiming to, and I believe they'll be successful in becoming the next prime, like the next Lockheed Martin. And they are radically different than existing government contractors, I mean, everything about them is different. And so let me give you this, let me like state it as a problem statement.

So if you look at the future of defense versus the past, basically you were looking at fighting Soviet Union and that's what the defense industry was designed to do. And that basically meant massive amounts of really expensive hardware, you know, airplanes and aircraft carriers, but Anduril was launched in 2017, but Ukraine has proven it out that the war is being driven by drones.

It loses 10,000 drones a month. And so the risk of a swarm of autonomous AI controlled drones is such a radical departure from how we think about defense, a thousand low cost drones could sink a $5 billion aircraft carrier or attack a city. And so the defense of four drones and basically how all that connects to this, sort of to all military hardware and the people on the ground and the air is changing rapidly.

It's being driven by software, not by hardware. And the primes, the big primes are not software companies. And so there's just like total break in what, in the way the industry needs to work. And Anduril is, I mean, I think they're like the Tesla of defense industry or they're like the SpaceX of the defense industry.

They're taking a radically different approach and they're succeeding. And so I understand there's people going to be just as worried about the risks of it, but you basically have to recognize how critically important it is, especially in the world, you know, this is how Hamas surprised Israel also. And so it's, and this is what the Houthis are doing in the Red Sea today.

I mean, they're attacking with drones. And so anyways, this is going to become critically important. And we invested in Anduril and that was, I think, really good example of an application of AI that is like a sector that is going to be transformed. No, I mean, thanks for sharing that with me.

I didn't, I've never heard of them. And what you said makes a lot of sense in terms of defense, saving lives, protecting lives and using technology and money to defend freedoms versus lives. I mean, what's, it's pretty important stuff. Oh, that's fascinating. Yeah. And so whether, you know, I named the three big investments we made in applications, but they're each category dominant for their categories.

And same thing with data infrastructure. Last time we talked about Databricks, they're absolutely category dominant for data industry. And we also invested in DBT Labs. And I don't know if you have to be a data nerd to know probably that much about them, but basically they are the essential software for data industry.

Like anybody who's a data professional, data scientist, data engineer uses them. They've really transformed how data is transformed, how data is transformed and understood inside our organizations. It did it for us. We have a lot of data, our real estate and investors, and we adopted DBT a couple of years ago and it just absolutely changed how we built and what was possible.

And then we wanted to see them, we want to invest in you. And we ended up actually, they ended up using our, us, Fundrise and the application of DBT is like a marketing case study. So I spent a lot of time trying to build a relationship with them and then we were able to invest in them.

And they're a singular company. There's nobody that's like a number two and they are essential and transformative. So that's a company that most people have never heard of. And it's just awesome. It's awesome that we invested in them. They're awesome. It really sounds like a great plan in terms of your value add to be an investor in these companies.

Because if you're like, let's say a VC at a VC shop, right, you've got relationships. So your value add is, well, you have a good track record, you know, other portfolio companies, you can make introductions, help with hiring and marketing, whatnot. But for Fundrise, it's like, you've got connections, you've got a team, you've got a company, you've got dollars, you can also become a client and help spread the good word about the company as well.

So to me, it seems like y'all have a competitive advantage over a traditional VC who is not actually implementing that product in a, you know, a multi hundred person company. Yeah. I think we have a small advantage and a big advantage. The small advantage is that when I'm talking to somebody at those companies, I'm talking to a peer, I'm a customer, I understand the product, we use the product, we literally use almost all the products we've invested in.

And I think that makes us just a very different counterparty. And then second, you know, we have 2 million users and we are a marketing distribution platform. You know, I was talking to one of our companies, we told them we were going to send an investor update out, I don't know, a million people, and they're like, "What's it cost us?

How much do we pay you?" I'm like, "What are you talking about?" Yeah, you get the exposure if you let us invest in you. Yeah. I mean, we, you know, millions of customers, potential customers, brand awareness, potentially if they ever go public, those are millions of retail investors. I think about Databricks as an example.

Most people never heard of them and they're going to go public probably in the next couple of years. And the more people know about them, the more I think they'll be impressed. And so there's like, I mean, there's just a value to the brand awareness that we can bring that's distinct or, as you said, competitive advantage over traditional venture funds who bring a different value.

I mean, I'm not going to try to bring the kind of value venture funds bring. That's not realistic. Right. No, it's interesting. Can we transition to talk about how an investor invests in an open-ended permanent venture capital fund, such as the innovation fund? Because as you told us in a previous episode, when we're talking about real estate, time is linear, but things happen in a non-linear fashion.

And so the good thing about innovation fund is you can click on the link and you can see what y'all are holding and then you can make a determination based on your holding, whether you want to invest and how much. But the way venture or private companies get valued is pretty chunky, right?

It's like a revaluation upward or downward after another funding round. So can you talk to us about the mechanics of, if someone wants to invest, they look at the portfolio like, this is great, I'm going to invest a thousand bucks, $10,000. How do they capture the returns of the fund?

Yes. I mean, this is, to some extent, the same thing happens in real estate where you basically have private market and public market and people in the public market transact every second and expect change to happen every second. In the private markets, it's a real world, right? Like you're building companies, you're building buildings, you're under construction with a 200 unit apartment building.

What's the value of the building when the concrete's up and the roof's on and the glass is in, but you haven't put in the toilets? It's really difficult because if you would look at that building and say, once it's opened and there's a certificate of occupancy, then it's a completed building and there's like a binary change.

And the same thing happens with tech companies, like they're worth a hundred million and then they raise a round and they're worth a billion. And the day before they raised, were they worth a hundred million, the day after they raised, are they worth a billion? And that's a very challenging dynamic in the private markets because in both instances where there's a building or a company, the change didn't happen overnight.

But when the building is completed and people are living in it, there is a step change difference. Like when the company gets valued by a venture fund and they raise a billion dollars, there is a step change difference. So we need to look at both sets of data, data that's binary, like if something changes, that's an event, like a fundraising round, that's easy.

And data that's non-binary, that's incremental, like the revenue's increased or they got a new big customer enterprise sale. And take today, today we've built a pretty remarkable private portfolio or portfolio of private companies, but we can't really revalue them until there's some external input that changes the facts. I mean, you make venture investments, you know that it takes a while before you really see external changes in the valuation.

In terms of the fund mechanics though, so let's say a company was valued at a hundred million, raises capital, and now it's valued at 500 million. How does, and let's say the innovation fund holds that company, do you all revalue the company to be worth 500 million or do you have discretion to say, well, it's not 500 million, you have a discount at 250 million?

How much discretion do you have to value these companies or what is the standard practice? Yeah. Well, so our valuations get audited. Every single investment gets audited by our auditor. So it's part of the fund structure that we're in, which is a 1940 Act registered investment company. So they show up and they basically do independent valuation as well.

And you know, but ultimately like even when a venture fund invests in a company, right, they're doing independent valuation. And so typically there's like a whole book, there's this massive book that's put out about how you look at valuation and the best way to value something is a third-party independent transaction like a public market IPO or a third-party venture fund.

And that's basically likely to end up being the valuation we would take. But if it was an inside round, right, if an inside round, and so are they as independent? That's more challenging. Like were there structured terms in it? Okay, headline valuation 500, but there are all these structured terms around pref multiples and cram downs and things like that.

So yeah, you can't just look at the headline and take that valuation. You have to look at the fundamentals of the business and you have to look at the terms of it. Got it. Okay. All right. So it's a little bit of an art as well as a science.

You know, as an investor, let's say I have a view that, okay, things are getting better. Okay. Rates are coming down. Risk appetite is going up. Public equities are up, you know, 24% for the S&P 500 in 2023. M&A is probably likely going to come back. The IPO market is likely going to come back.

There's going to be a window of opportunity for private companies to go public. Therefore, would it not be strategic to look at companies that are at the cusp of going public and invest in them before they go public to then capture that upside? I mean, obviously the IPO valuation could decline, but in general, in a bull market or in a growing risk appetite market, those valuations are going to continue to increase.

So what do you think about that strategy? Yeah. Well, I mean, without naming names, because one of the things I have to be sensitive to is the companies don't want me talking about them and, right, I mean, I'm not their CEO. But if you look at our portfolio, the three most likely, sort of most exciting next companies to go public are in our portfolio.

Yeah. And we can all see that. And I think we can all make a deduction as to which ones they could be. Yeah. And I think that'll be very validating for people. I mean, again, the funny thing about tech is that unless you're in the tech industry, you really haven't heard of all these companies.

You know, we're not talking about name brands in most cases, but it's, yeah, I believe that some of these companies will go public the next year or two. I think that they're really good companies. There's no question about that in my mind. And exactly how the market values it, again, I'm not a short-term investor.

Even when some of these great companies went public, it didn't mean that they were no longer a good investment. You know, we have to have some of the fund in liquid assets because investors redeem every quarter. And so the way we did that in 2023, and even now we have the portfolio in bonds of tech companies, we basically felt like when we started deploying the innovation fund that our investors were not looking for us to take like a kind of public market risk that they could take themselves.

So we focused on private tech companies and then we had the rest of the portfolio in public tech bonds, which actually are not that easy to buy. They usually hold lots or a million dollars and most people aren't buying public tech bonds. And so we got pretty good yields.

I mean, it was a good time to buy tech bonds. And so we have to have some of the portfolio in liquid assets in order basically to have this sort of hybrid fund, this crossover fund, democratize investing in private markets because otherwise there'd be no liquidity and investors expect some limited amount of liquidity when they invest.

So let's say one of your portfolio companies goes public next year, there's a six month lockup period after IPO. What is the decision process then in terms of selling in the public market to capture that gain and liquidity, riding it out? Is there some type of standard which you all will operate or is it dependent?

No, it's going to be a kind of a micro decision, ground up. You look at the company, look at what basically is where it's pricing, it's growth, etc. And then you look at the portfolio. And one of the great things about private markets, it's a funny thing about private markets is actually in some instances you get more information than public markets.

Like a venture investor who invests in a company gets way more information than a public market, you know, S1. And so today, at least if you look at the construction of the portfolio, the macros we've invested in are really early in their growth cycle. AI is like a year old.

I mean, I don't think we would be a seller, I think we'd be like, one of the reasons a company like, well, I'm not going to say a name, but a company takes your money because they want you to be a long-term holder. They don't want somebody to just trade you, right?

That's actually not a value-add partner. And so to get the best companies, you need to be like Warren Buffett. You need to be low touch, you know, helpful if they want your help and a long-term investor. That's how you basically, I think, attract the type of companies that we want to invest in.

Right. No, no, that makes a lot of sense. You don't want to be, you know, I don't know, the hedge fund investor who buys on a Monday and sells on a Friday after a 15% pop, right? You want to be long-term value-added, you're right, low touch, not a PITA.

Every time we sell, we trigger capital gains, right? The investor gets these capital gains flow down to them so that the investor doesn't want, capital gains are a huge waste of, you lose, what is it, 37% between state and federal, maybe 40. Right. Yeah. I'm just thinking down the line, let's say five years from now, you know, more companies may go public, probably will go public in the portfolio.

And so eventually the mix might be a greater percentage of public company exposure versus private company exposure. Because right now it's... That's not our mandate though. I mean, our mandate is to be vast majority private. Right. Currently, it absolutely is, and I think we can maintain that. If I look at my lessons from 2021, if we were basically, we wouldn't be making a decision that private markets are overpriced and we would be like not investing in predominantly maybe back to bonds or something because you, part of what the structure of our funds can do, which most people can't, most funds can't either, is that you can be in, you can be allocating to private or public.

And that arbitrage between where the multiples or prices are more attractive, it's really uncommon, not just for individual investors, but even institutions like venture funds can't really invest in public stock and public funds can't invest in private. And that's like an arbitrage opportunity. Right. Right. Well, sounds pretty promising.

In conclusion, what are your thoughts for, I guess, the rest of 2024 and maybe a little bit 2025 in the venture capital land? I mean, the venture industry is basically today operating basically in two different environments. Anything that's AI is basically priced like it's 2021. Anything that's not AI is almost unpriced, almost unpriced.

You have amount of venture capital dollars declined by 50, 60% in the last two years. So there's a good sign for investors, but at the same time, there's still markdowns from the peak that haven't happened yet. And so there's a lot of work. I mean, the same thing with real estate, right?

There's still a lot of change or reality to bring to bear on both industries. And that's going to take time. The good thing about our fund structure is we don't have to be in a hurry. So we got a lot of good investments in 2023, and then we may slow down unless we see something good, right?

There's no reason to deploy. All right. Well, it seems like we're also passing the bottom for the venture capital industry, just like we're passing the bottom for the real estate industry. So in other words, it sounds like you are very optimistic and bullish, just like I am. Optimistic. Are you optimistic too?

If we're aligned again, there's something. I'm very optimistic. I mean, I live in San Francisco. We're a startup city of the world. All the AI companies are here. Everywhere I go, everybody's talking about AI, whether I'm on the pickleball court, whether I'm playing tennis, I'm in the library, whatever, AI, AI, nonstop, or even at the Starbucks with some guy's laptop out.

So it's everywhere. I'm maybe a little bit worried about valuations. How are those going to shake out? But it sounds to me that investing in AI long term is worth it. And if you want to hedge against an interesting future, you want to have some exposure to AI. And so that's what I'm going to be doing.

And I want to thank you for having this open-ended fun where the investment minimum is only $10 and there's liquidity. Well, thanks so much for coming on the Financial Samurai podcast, Ben. And maybe what we can do is a mid-year checkup to see how things are going and whether that optimism remains in both real estate and venture.

Yeah, that would be great. I love our conversations. All right. And when you come out to San Francisco, we're going to grab a beer, hopefully, what in March, and we'll reconvene then. All right, everyone. Thanks so much for listening. And if you enjoyed this podcast, don't forget to subscribe, share and review.

We will talk to you all later. Thanks everyone for listening to the conversation I had with Ben Miller, CEO and co-founder of Fundrise about his outlook for venture capital in 2024 and beyond. If you would like to explore the open-ended Fundrise Innovation Fund, you can go to financialsamurai.com/innovation. Unlike traditional closed-end venture capital funds, where you commit capital and then hope the fund makes wise investment decisions, you can first see what type of investments the Innovation Fund has made first before deciding on if and how much to invest.

Fundrise is a longtime sponsor of Financial Samurai and Financial Samurai is an investor in Fundrise Funds. Lastly, if you enjoyed this episode, I'd appreciate a rate, review and a share. Every single episode takes hours to record, edit and produce. Thanks so much.