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Conductive Ventures recently raised $100 million to invest in enterprise hardware and software. One reason is that hardware giants have been acquiring innovative startups when those larger companies aren’t able to invent something in-house, which makes hardware startups a good investment.
I moderated a panel on hardware’s resurgence at HardwareCon. My panel included Jennifer Gill Roberts, cofounder of Grit Labs; Mike Edelhart, managing partner at Social Starts; Ashish Aggarwal, principal at Grishin Robotics; and Ephraim Lindenbaum, managing director of Advance Ventures.
Our focus was on hardware’s resurgence, how to do pitches, and how to elevate a startup beyond the Maker stage to get real funding and traction.
Here’s an edited transcript of our panel.
VentureBeat: I moved to Silicon Valley in 1994, and I remember when I arrived that people said that hardware startups were done. That was obviously wrong. We’ll get into that, but first please introduce yourselves.
Jennifer Gill Roberts: I’ve been in Silicon Valley my entire life. I grew up here. I went to Stanford and worked at Sun and HP as a hardware engineer. After business school I went into venture. In the ‘90s I was funding optical and wireless equipment, up and down the stack. That was very capital-intensive. Some of those companies raised hundreds of millions of dollars and had only a handful of customers. Today actually seems a lot easier.
When I look at businesses now, to me they have some of the same elements: finding customer and market fit, trying to get launched on a reasonable amount of capital. I’m excited to talk about that.
Mike Edelhart: I’m a managing partner of two sets of very early stage venture funds. One is Social Starts, which tracks the impact of social mobile technology. That’s been active since 2012. The other is Joyance Partners, focused on the technological vectors of happiness. I look at both hardware and software. I was the founding editor of pretty much all the Ziff-Davis computer magazines, like PC Magazine and PC Link, the labs and benchmarks and things like that behind them. We tested every product, hardware and software, on the PC.
Ashish Aggarwal: I’m part of Grishin Robotics. We’re a $100 million VC fund, primarily investing in early stage companies, in hardware robotics and consumer.
Ephraim Lindenbaum: I’m managing director of Advance Ventures. I’m a recovering entrepreneur. I’ve actually sat in your chair before. I started in Silicon Valley as well, growing companies all through the ‘90s, not to date myself. Exited in the first dot-com boom. I came back to Silicon Valley after some time as a chief strategic officer. It’s pretty binary when you get back to Silicon Valley. You’re either starting a company or becoming an investor. I didn’t have any great ideas, so I became an investor.
We spun up Advance Ventures in 1999 and we’ve now invested through three successive funds. We invest in information technology, mobility, IOT, and what we call sustainability, which is pretty much agriculture and food technology. We’ve been involved in the connected device and hardware space since the ‘90s. With our entrepreneurs we built the first connected gas pump for Chevron, the first connected terminals in airports. Like Jennifer we were in telco and moved into hardware. Today about 20 percent of our portfolio is hardware-component. We just closed a deal this morning, a hardware-connected diagnostic device company. We’re quite happy in the hardware space.
VentureBeat: We have all the big companies – Intel, Cisco, Seagate. Why should there be hardware startups at all now? At the same time, we also have so many makers out there, people working in their garages and going to the Maker Faires. What seems to be going on, from your perspective, as far as why the hardware startups still exist?
Roberts: With every technology wave, you create new market leaders. It’s not in the DNA of the prior market leaders. I’m not saying these companies won’t be dominant for some time to come, but certainly we saw companies emerge in the PC wave, in the telecom wave, in the mobile social wave. I’m excited about the power of robotics. I think we’ll see completely different DNA.
The companies we’re funding through Grit Labs are coming to us with deep domain knowledge, with deep tech backgrounds. They’re recent PhDs. We’re not seeing as many companies iterate out of the dominant companies you mentioned. To me it’s that new DNA and new technology that drives new market leaders.
Edelhart: It’s always the best time to start new technology and it’s always the worst time to start new technology. There are always enormous entrenched players who look like they have infinite advantage and can’t be displaced. And they’re always displaced. Human behavior changes. Technology changes. When you put those two together, there are requirements for new capabilities that the existing companies aren’t set up to understand, respond to, or provide. There’s always a need for the new, and the old order will always change.
Aggarwal: The fundamental theory—when you think about it, what is robotics made of? Math, physics, all of these fundamental technologies. A lot of research has been going on for the past few decades, and in the past decade, a lot of technologies have started to come together, things that weren’t available 10 or 15 years ago. What AWS makes possible today—I used to manage hardware data centers for Yahoo. It used to take almost a year of planning to spin up a hardware data center. Today it’s so easy.
Similarly, the amount of data people can capture from devices—15 years ago, none of us used to have—how many connected devices did you carry around with yourself? Today everyone has at least one or two, all the time. Fundamentally, a lot of things have changed that allow new types of problems to be solved and new data sets to be captured. That has led to new types of advances and allowed new realms of technology to come together for people to build and create new types of robotics. New AI and machine learning are being applied to these larger problems in ways that weren’t possible before.
Lindenbaum: If this was Jeopardy, this would be the daily double. The most valuable company in the world is a hardware company. It’s Apple. It all starts there in terms of that conversation. To Jennifer’s point, hardware has been out of favor in the venture space for a while. That creates a drought. It creates the opportunity to innovate in particular categories.
The back office ecosystem of technology has come around to the point where these pieces work. Robotics without great machine vision isn’t great robotics. Robotics without great AI isn’t great robotics. The biggest challenge we see in this space is solutions looking for problems. Being able to drive into that, we’ve seen some wins in hardware in the venture world, companies like Tesla that have been successful, which spurs us to look back into that space.
A question in the green room was, with the Intels of the world out there, why are you all doing this? Innovation is value. It started to happen at the big companies, in the late ‘80s and through the ‘90s. It became an M&A process very quickly. These big companies couldn’t innovate purely on their own. M&A became a huge part of the R&D strategy at all of these companies, and it still is today. Look at Salesforce. Look at Apple. Look at everybody. They’re buyers. That gives you, as an entrepreneur, a clear trajectory to grow these businesses.
The next piece of the story is, there are great sectors where hardware is super meaningful. We’re a big player in food and agriculture. These are huge areas. There was a very meaningful robotics exit earlier this year in the space. In the food space there’s a ton of traction. If you look at some of what we call frontier markets, like cannabis, there’s tremendous movement in cannabis in hardware.
VentureBeat: How many cannabis investors do we have in the audience? We have one!
Lindenbaum: The reason why you want to look at that is adoption curves. When you have industries that have huge margins and incremental improvements translating into huge movement, you get high-speed of adoption. When you’re moving into the retail market where you have perhaps a three percent margin, getting any kind of technology adoption in rapid fashion is very challenging.
We’re investors, for example, in financial technology, where there’s a lot of retail movement. We’re investors in health tech, which is a huge IOT and connected device category. Food and agriculture are very meaningful at this point.
VentureBeat: You’ve already partially answered my second question, then, which is: What are the interesting categories you’re looking at? Do you want to talk more about what you like and what you might not do anymore?
Edelhart: We’re investors at the very beginning. We tend to see these trends when they emerge. Some of the things we’re seeing related to hardware—things like throwaway hardware, where the hardware is a smaller component of the overall solution. It used to be the hardware was the biggest, heaviest, most expensive part. Now a sensor is very inexpensive. It can be part of accumulating data sets that can then be exploited in other places. IOT sensors are one example.
We have one in agriculture where the whole system is taking advantage of the sensors that are already present on farm equipment. The sensors are there, the equipment is there, and the system is taking new advantage of what’s already there. Or taking advantage of capabilities in the phone and things like that, where the new hardware is an incremental element.
The other thing we’re seeing in hardware is hardware as a service. If the data sets are changing, or the usages are changing–the traditional hardware just does what it does. It does it the same way forever. It’s becoming a bit outmoded to the use. Hardware needs to become more flexible. The interaction between hardware and software needs to be more flexible. The whole system has to interact with the person more flexibly. We’re starting to see hardware less as the big piece of steak in the middle of the plate and more as a part of a mixed stew.
Roberts: We like verticals that are getting disrupted. Someone already mentioned agriculture. If you look at logistics, transportation, and construction, you can see that many Fortune 500 businesses are at risk. What’s going to happen to UPS? What has already happened to U.S. automakers? You’ve probably all seen them arrive in Silicon Valley and set up their venture arms and innovation centers. They’re starting to be very acquisitive. I like that these verticals are not only ripe for innovation, but also for acquisition.
I love robotics as a service because you can lower the barrier to entry, to getting it deployed. You can constantly upgrade it. You can delight the customer. You have a better lock. Our companies are very capital-efficient because it doesn’t need to be perfect and pretty like a consumer product. We’re looking for this intersection of things that lead us to believe that these companies are a prospect for a nice multiple or have the opportunity to be independent in these verticals.
Aggarwal: Among the things we look at, food tech is one of the big things, where you start seeing innovation happening in how food is prepared, how food is delivered, how producers are meeting demand. There’s a lot happening, mostly on the back side rather than front side. You see a lot of places where people are thinking about automation, like Eatsa is doing in downtown San Francisco. We see a lot of innovations where you’re trying to take the human factor out of how food is prepared.
A lot of stuff is happening on the agricultural tech side. Because of labor shortages and what’s happening with climate, people are looking at different ways of getting access to labor to pick different types of stuff – apples, other kinds of produce. People are trying to figure out ways to solve that problem.
There’s a whole bunch of things we see around self-driving. Everyone knows about Uber and Waymo and all these other companies building different stacks of software, both for getting people and getting goods from point A to point B. There are competing applications in almost any space: security, smart homes, transportation, logistics. All of these have big applications for computer vision.
We’re seeing companies try to build Amazon Go-style stores for almost every other retailer. Every retailer is feeling pressure from Amazon in terms of trying to improve their margins. They have to think about reducing costs as well as increasing revenue. Everybody’s trying to figure out things like inventory management at scale that can help reduce the cost of labor. That’s becoming a lot more prevalent.
On the consumer side, we’re focused on how people spend time. You cook, clean, drive, sleep. Companies are looking at how to automate some aspect of life. One of the first companies in the space was iRobot, because cleaning needs to happen in a constrained environment and it’s easy to build a robot to do that. Today we’re seeing robots for more complex applications in the home, like taking care of the elderly.
On the enterprise side, we’ve started seeing companies that are focused on either increasing revenue or decreasing cost. On the industrial side, the focus is primarily on understanding how to take humans out of hazardous environments, like using drones for the surveying of critical structures. That’s very difficult for humans to do.
VentureBeat: What sort of guidance do you give in some of these areas? It seems like we have enough self-driving car startups. Nvidia’s working with 400 different companies doing something with its self-driving car chips. Nvidia’s also said their working with 2,900 AI companies, engaging with them in some way. You start to think, these guys are all ahead already. Should I do what they’re doing?
Lindenbaum: Let me throw this out there. One of the hottest bubbles right now is connected scooters. This didn’t take machine vision or robotics or anything else. This took a problem with a good hardware solution. This is less of a solution looking for a problem. We see a lot of that in these categories, where it’s not clear where the exit trajectory is in the near term.
This is one of the greatest times in the history of entrepreneurship to start a company. This is also the greatest place on the planet to start a company. There are incubators. There are accelerators. There are micro-funds. There’s AngelList. There’s crowdfunding. On this panel, everything from smaller funds and angels all the way up to big boys. I saw an entrepreneur recently who was basically gaming the accelerator and incubator system. Who had the best food? Who had the best package? These programs were competing for a startup.
As an entrepreneur looking for funding, you have all the standard stuff we talk about. How do you point the ship? How do you look out into the future and figure something out? But it really comes down to the product. Great companies solve problems. A great VC, a firm president once said to me once, “The shorter the deck, the better the product.” I asked him what was the shortest deck he ever funded. He said, “Three slides. If I could get one that was down to one I would fund it in a heartbeat.”
This is all about solving big problems. With what we look at, we break it into two categories. There’s the brave new world, and there’s better, faster, cheaper. It’s a question of picking one and going after it. With all of the infrastructure that’s now available to you, as well as the ability to manufacture quickly—as I was talking about earlier, M&A has become a big part of R&D. The ability to get out there and get enough traction under your startup to get our interest is incredibly high.
It’s all about solving a real problem. It can be as complex as robots or as simple as scooters. Don’t get wrapped around the axle trying to make something too complex. Just solve a big problem.
VentureBeat: Are you getting to the distinction between a maker or an inventor and an entrepreneur, who’s actually got a shot at getting funding?
Edelhart: One thing to keep in mind, as we bring this back to how you get funding: are you actually a company? Or are you a product attribute? We’ve got something really wizard that’s nobody’s ever done before that solves part of the problem. It contributes. But is it doing something big? Is it part of something else? Is it just a product?
If there’s a deficiency in the companies we see, it’s the lack of recognition that business model innovation produces much more value than technological innovation. Technological innovation on its own is great, but how does it make a company? Microsoft became Microsoft because it was on every computer. It had a distribution advantage. As that went away, the company had to work much harder to succeed.
You have to think about solving a big problem in a way that actually produces a company. You have to build value not just in an interesting product or an interesting set of capabilities. That involves distribution, understanding who the customers are and how you get to them, and how you can use all of that to create real value with a real organization and real people.
Roberts: I wanted to comment a bit on fundraising, because I’ve been in those shoes as well. I had a startup, and I probably pitched 200 investors, micro-VCs, and venture firms. With our own portfolio, we go out with them and help them raise and try to make sure they go through that pre-seed through seed through A. It’s really hard, and there’s a few things to think about.
First of all, incubators sound great, but when they take a lot of your common equity and your cap table gets screwed up, that’s something you need to think through. A lot of investors are passive in that seed to A phase that we see. They literally have a thousand in their spreadsheet. You’re not going to get a lot of help during that time frame. You’ll need to be smart about who you surround yourself with, advisors who can help you think through business models and launch. They’re probably barely going to respond to your calls.
Knowing what their fund size is and how they think about outcomes is important. A $30 million fund versus a billion-dollar fund is a very different profile of success. That whole process deserves an immense amount of hard work, as well as strategy, so you’re not wasting your time beating on doors that just aren’t going to fund you or that aren’t interested in the space you’re in. It’s a repeat exercise I do with every portfolio company.
Lindenbaum: I want to go back to something that Mike said. If you walk away with nothing but that critical data point, we’re going to save you lots of pain and suffering and time. Are you building a startup? You can come see all of us in the Valley, but if the venture economics don’t work—I don’t want to go into a deep dive on venture economics, but there are specific benchmarks you need to see in companies in order for them to work. The differential between a venture-scale company and a great company is often very different.
It’s really important to look out into the future of what you’re working with today. Is this a venture company? We’ll have to go through a number of baseline checkoffs in order to even bring you into consideration within our firm. That’s an important aspect of this. Don’t break your back seeing 200 of us if the fundamentals aren’t there. Is this company going to reach a multi-hundred-million-dollar exit in a reasonable time frame? Is the adoption curve of the technology within our life cycle? Venture funds are 10 years. If you’re going to exit in 10 years and a day, you just scored a touchdown five minutes after the game’s over. It doesn’t matter to us.
You have to look inward and understand things beyond the personal. Is this a venture product? Does this have a real exit trajectory with a meaningful return that’s going to click with our level of interest? That’s important. There are lots of great companies out there that have been able to get funded and everything else, but don’t go into this often difficult ecosystem and spend a lot of cycles if it doesn’t match up early on.
We saw this in mobile. Was it an app or was it a company? We’re seeing a lot of this in hardware today. Is it a solution or, as Mike said, a part of a solution? Or is it a company? Those are the most important factors to look at. If you take that away, that’s going to save you time and effort. It’s not always right to build a venture company. There are lots of good companies that do get venture funding, but understanding that differential is really a time-saver for an entrepreneur.
VentureBeat: I wanted to get to a lesson a company has taught you, that could be valuable for the audience. I’m thinking of the movie Founder, about McDonald’s. Ray Kroc was grinding away, trying to get his franchises going, trying to make a royalty from the hamburgers they sold. Another guy came in and says to him, “You haven’t figured out what business you’re in. You think you’re in the hamburger business, but you really should be in the real estate business. You can make more money buying land and leasing it to your franchises.” I wonder if you have some lessons like that apply to hardware.
Edelhart: At the topmost level, it’s too much belief and too little belief. The one thing I’ll say, after doing this for a long time, I don’t think I’ve ever seen a startup that ever succeeded doing exactly what they said they were going to when they walked in with a deck. Life just doesn’t work that way. Companies have to adjust with what the market teaches them, what technology turns out to make possible in a practical way or not.
Companies that come in where the CEO says, “I’m right. I’ve always been right. I’ve never been wrong. Everything I say is true,” that company’s going to get in trouble, because that hardly ever happens. Companies who come in and—this is absolutely what not to say in a meeting, at least with a venture capitalist like me. “What do you think we ought to do?” I don’t know! I’m spending 45 minutes on your company. You’re supposed to be spending 22 hours a day.
So we find that companies with too much belief and too little belief, in their different ways, they get into the weeds. Success comes from the capacity, from the top down, to always believe – the company always knows what it’s about – and always change. What it’s about is different from what it was six months ago.
You have a big dream. You have a big problem. But you’re acting small right now. You have to get a customer, then 10 customers. You have to get 10,000 units and then 100,000 units. If you’re focused on taking over Europe, but you can’t manufacture at your current scale, you’re not taking over anything. It’s that juxtaposition. I had someone in a meeting, an entrepreneur, say to me recently, “You have to have a plan, and if it’s more than a one-year plan, you’re fooling yourself.” It’s a 12-week plan, an eight-week plan, maybe a three-week plan. The event horizon you can actually control in your business is not far off.
Aggarwal: People forget how easy hardware is to copy. You’ll be surprised. Other companies can do it better, faster, cheaper, at a point where you can’t imagine. People get hung up on thinking, “No, the hardware I built cannot be copied.” Understand that you have to really build the prestige factors around the software layer, or some other way that cannot be copied. That’s extremely important.
If you’re building hardware for consumers, the market is already so big. You’re competing against some of the biggest players – Google, Apple, Amazon. It’s a very covered market. Also, from what we’ve seen, looking at companies that have been successful, only a handful have been successful in the hardware space, at least on the consumer side. By studying those, you can try not to make the same mistakes.
Going after a market that already exists and trying to sell in that market—for example, in the case of Ring, everybody has a doorbell. The high line is, can you make a product that makes life a little bit better for you as the owner of that product? How frequently do people actually buy this product? What is the pain point it’s going to solve? Understanding all these fundamental questions and being able to be very scrappy, early on, trying to do these things—this matters a lot, even for hardware startups.
When we see a hardware startup that’s raised a lot of capital and they haven’t launched a product, that’s a very big red flag. Where have you put all that money? They’re saying, “Well, we were trying to perfect the technology.” The other side of the spectrum, like on the China side—Chinese entrepreneurs are very good at executing. Even the low-tech solutions. A good example of that is Amazon Go-style stores. In China there are already companies that have deployed hundreds of these stores at scale. If you search for companies like BingoBox, they already exist. Over here people are still trying to perfect the technology to make sure it works.
Understanding the market you’re going after, there’s a lot you can achieve. That’s something I tell people. Try to build a product in a market that already exists, so you’re not the first that’s spending millions of dollars educating people about why they should buy your product.
Lindenbaum: I don’t necessarily buy into the idea that every company pivots, because if you look at the big ones — Facebook, Google, Apple — they didn’t. They are all what they started as, for the most part. That true sense of being able to get there makes sense. Although the pivot is clearly a big part of the model. But really, finding a big problem and solving it is still the crux of our whole business.
That problem may be one step beyond the surface level. Our belief in Ring, for example, is if you didn’t have packages, then people wouldn’t have been as interested in doing that. It’s not only the first step. It’s really the second step. If you look at why they were acquired, it’s because there’s a pretty long tail associated with that concept.
Look at the problems that are solvable. People are jammed up in San Francisco. Somebody connected a scooter. Now they’re duking it out for control of the city. Taxicabs are inefficient. Now we have ride-sharing. Look at problems. Don’t look at technology and then go try and solve something that may or may not be a true problem. The bigger the problem, the easier it is to break it down. The smaller the problem, the bigger the problem you have.
Edelhart: You can have your Jerry Springer moment. I’ll point out, for the record, that the first version of Facebook was about pretty girls on the Harvard campus—
Lindenbaum: What do you think people are using Facebook for now? I don’t know what you’re using it for.
Edelhart: You couldn’t even get in if you weren’t a college student.
Lindenbaum: That’s called denial marketing.
Roberts: I’d also like to inject a little controversy. I am not excited about businesses where the hardware is the centerpiece. I’d encourage you all to think about—your team is probably going to need to be 80 percent AI. Hardware is off the shelf.
We’ve talked about this, but it’s about identifying those big customer problems. Rigorously go after understanding them, the human-centered design approach. Have those really differentiated teams, because they bring the deep domain knowledge. They bring the different disciplines. They understand that they’re building a service. They have to be customer-centric, not PhDs meeting with customers. I can’t even imagine funding a hardware business today like I used to where it was all about developing hardware. It’s just not going to be the case anymore.
Audience: Fortunately I work at a startup that’s building a service, trying to solve problems, but as an engineer I’m pretty excited by hardware. I love buying it and playing with it. Why do you feel so strongly that a hardware product will need something more than that today?
Roberts: There has to be hardware for Grit Labs to fund it. I just don’t think that the hardware is generally the most challenging piece of the solution. It’s going to be about the intelligence, about how this solution operates in the customer constraints. I’m not saying I’m not interested in hardware. I’m an electrical engineer by background. It’s just not where we’re seeing the innovation come from.
Edelhart: Another way to put that is that the value isn’t in the silicon. The value isn’t in the steel. The value isn’t in the plastic. The value is in the human behavior. If the thing ends up just sitting there like a rock, where’s the value? If it’s getting there, the value comes from interaction with the outside world. That’s where the AI and the software and the whole system come in. There has to be that interaction for there to be value. If this configuration of stuff, augmented by some system, produces insight, value, response that wasn’t there before, that’s the value. The thing itself is just a pile of stuff.
Audience: When it comes to a cannabis startup, what would you recommend as the best avenue for trying to get funding?
Lindenbaum: We see cannabis as a high-value crop. If you compare it to something like soybeans or corn, corn is about $55 a bushel and cannabis is $1,000 a pound. There’s a fairly large margin difference. When you see an incremental improvement with something that’s a commodity at that cost, it goes a long way. When you have margins approaching 80 percent, there’s a lot of additional capital to collapse into the adoption cycle.
In all cases, in all of our businesses, whether it’s hardware, software, anything, this is all about customers and adoption curves. If you can collapse an adoption curve in any environment, it makes sense. In particular, agriculture and food have been areas where gray technology has been very hard to bring into the native strains, because the timelines and the margins have not allowed for rapid advancement. Only now are we seeing food and agriculture move more quickly in that category.
We don’t invest directly in cannabis as a thing. We invest in picks and shovels. We just funded a connected diagnostic company for the lab business, because all the cannabis that anybody wants to go out and buy needs to be tested now. That’s a huge backlog. That’s an area where these guys are essentially going from a few thousand dollars a month to hundreds of thousands of dollars a month in sales in only a few months. I don’t care what your business is. When we see an arc that’s going to move that way, we want to know more about it.
It’s all about finding the pieces of the story that make sense. Robotics and cannabis, the ag story—Blue Robotics is doing some interesting things. These are some big problems that need to be solved. Then you move on to stronger areas when the economics are easier to manage over time.
Audience: Hardware can’t succeed without good software, and the reverse is true as well. Software needs compact, efficient hardware. What makes the decision to fund or not to fund when you’re presented with something that has to work forward in both areas?
Edelhart: Margin, and predictable margins. One of the challenges—I’m a relatively small fund compared to some of the others up here. In hardware it’s more difficult to know in the beginning what the unit economics will be, what the margin will be. You don’t know the yields. You don’t know a lot of things.
The more the entrepreneur can help bring that forward – we’ve done some test runs, we’ve done this, we’ve done that, we have a sense of how this will naturally scale as a business – it makes it much easier for us to understand. If we don’t understand that, maybe the company will take $1 million to get to a product, or maybe it’ll take $10 million, or $100 million. That can be a big challenge for us, because we don’t have the resources to support an unbounded requirement for capital.
With software, it’s easier, in many cases, to understand what the fundamental unit economics are. It’s easier for a fund sitting in front of a software company to say, “Okay, we see what the hard costs are. We see how it amortizes. We get a sense of what the margins are going to be, how much cash we’re going to need, and we’re comfortable with that.” That’s one reason for the sort of prejudice toward software. In the beginning, it’s easier for us to analyze and get comfortable with.
Roberts: I like having a customer lock, because it’s so competitive in every single category. As an example, we funded a robotic harvester that does strawberries. It’s called Tortuga. Initially, it’s going down the aisles in a greenhouse and picking strawberries, and that’s very hard to do. But you can imagine, once you’re in there and you have a service business model, where you’re doing the harvest business for them–again, you’re not doing 100 percent of it initially. You’re doing five percent of it. But now you can start to bring in the intelligence and the analytics and all the things AI has to offer. Now you have more of a customer lock, so that when someone else comes and says, “I have a better strawberry picker,” you have a path forward with that customer. You may substitute a piece of the hardware. Maybe there’s a better arm that picks. What I like is just that ability to upgrade constantly and delight the customer over many years.
Audience: We have a hardware startup. We do an ECG, fully autonomously, from one wrist, and we’re using that to read heart rate variability. While we have one hardware with our sensors, there’s a lot of potential for different applications to be built around that.
Lindenbaum: If you want to dig in — if you come to us you might say, “Well, what should I do?” We don’t know. You tell us.
Edelhart: Also, the ability to capture heart rate variability is a description of a product attribute. A company that starts with the understanding of the behavior of heartbeat in certain situations has huge impact on certain kinds of organizations. Those organizations have certain kinds of problems that can be approached in this way. That’s a company.
Lindenbaum: The first thing you have to think about is, pick one. Who pays for it? Is it a private pay? Is it an insurance pay? Then you have to think about, do you have a regulatory permit? Once you solve all those pieces you can come back to us and say, this is what I’m going to do. This is who pays for it. This is my regulatory permit. The minute you talk about something involving a human body, flags go up all over the place. Get those solved, because in 10 seconds, three sentences, you can answer the first questions anybody was going to ask.
Audience: I wanted to ask about partnerships with other people interested in building around our technology. I’ve heard about mixed results from VCs based on who it is that we’re looking to partner with and what they do. What would you recommend for an investment pitch to present that, if we haven’t secured a partnership yet?
Lindenbaum: Don’t. If you don’t have it inked, don’t tell us.
Edelhart: I would say that startups partnering with startups is multiplying fractures. It’s getting smaller, not getting bigger. Neither side is big enough to help the other and it’s a pure distraction from both sides. If you want to partner up, fine, but to me, that’s a customer. Find customers who are bigger than you and have their large amounts of money flow to you so you can start getting bigger. Don’t distract yourself with partnerships in that sense. I don’t know the particulars, but it tends not to work. Neither side has enough resources. Both sides are changing. It’s like when teenagers date. It’s not going to last.
VentureBeat: I caught the season opener of Westworld, and my last request is, please don’t fund any of that stuff. We don’t need robots who are just like us. We don’t want to go there.
Edelhart: I heard that thing about the plastic-eating microbe, and it sounded so much like the beginning of a 1950s horror movie to me. “Then it started eating things that weren’t plastic!”
Roberts: It’s actually a really exciting field for our children and the next generation. The ethics around AI are quite complex. That’s going to open up all kinds of new fields as we get into human interaction. What I’ve been talking about, at least, is very contained. It’s transactional. It’s replacing an unpleasant job with a robot, but it’s not social robotics, interacting with people. That’s going to be fascinating.
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