Leading robotics VCs talk about where they’re investing - 8 minutes read
Leading robotics VCs talk about where they’re investing – TechCrunch
The Valley’s affinity for robotics shows no signs of cooling. Technical enhancements through innovations like AI/ML, compute power and big data utilization continue to drive new performance milestones, efficiencies and use cases.
Despite the old saying, “hardware is hard,” investment in the robotics space continues to expand. Money is pouring in across robotics’ billion-dollar sub verticals, including industrial and labor automation, drone delivery, machine vision and a wide range of others.
According to data from Pitchbook and Crunchbase, 2018 saw new highs for the number of venture deals and total invested capital in the space, with roughly $5 billion in investment coming from nearly 400 deals. With robotics well on its way to again set new investment peaks in 2019, we asked 13 leading VCs who work at firms spanning early to growth stages to share what’s exciting them most and where they see opportunity in the sector:
Participants discuss the compelling business models for robotics startups (such as “Robots as a Service”), current valuations, growth tactics and key robotics KPIs, while also diving into key trends in industrial automation, human replacement, transportation, climate change, and the evolving regulatory environment.
Which trends are you most excited in robotics from an investing perspective?
How much time are you spending on robotics right now? Is the market under-heated, overheated, or just right?
Are there startups that you wish you would see in the industry but don’t? Plus any other thoughts you want to share with TechCrunch readers.
Three years ago, the most compelling companies to us in the industrial space were in software. We now spend significantly more time in verticalized AI and hardware. Robotic companies we find most exciting today are addressing key driver areas of (1) high labor turnover and shortage and (2) new research around generalization on the software side. For many years, we have seen some pretty impressive science projects out of labs, but once you take these into the real world, they fail. In these changing environmental conditions, it’s crucial that robots work effectively in-the-wild at speeds and economics that make sense. This is an extremely difficult combination of problems, and we’re now finally seeing it happen. A few verticals we believe will experience a significant overhaul in the next 5 years include logistics, waste, micro-fulfillment, and construction. With this shift in robotic capability, we’re also seeing a shift in customer sentiment. Companies who are used to buying outright machines are now more willing to explore RaaS (Robot as a Service) models for compelling robotic solutions – and that repeat revenue model has opened the door for some formerly enterprise software-only investors. On the other hand, companies exploring robotics in place of tasks with high labor shortages, such as trucking or agriculture, are more willing to explore per hour or per unit pick models. Adoption won’t be overnight, but in the medium term, we are very enthusiastic about the ways robotics will transform industries. We do believe investing in this space requires the right technical know-how and network to evaluate and support companies, so momentum investors looking to dip their hand into a hot space may be disappointed.
We’re entering the early stages of the golden age of robotics. Robotics is already a huge, multibillion-dollar market – but today that market is dominated by industrial robotics, such as welding and assembly robots found on automotive assembly lines around the world. These robots repeat basic tasks, over and over, and are usually separated by caged walls from humans for safety. However, this is rapidly changing. Advances in perception, driven by deep learning, machine vision and inexpensive, high-performance cameras allow robots to safely navigate the real world, escape the manufacturing cages, and closely interact with humans. I think the biggest opportunities in robotics are those which attack enormous markets where it’s difficult to hire and retain labor. One great example is long-haul trucking. Highway driving represents one of the easiest problems for autonomous vehicles, since the lanes tend to be well-marked, the roads have gentle curves, and all traffic runs in the same direction. In the United States alone, long haul trucking is a multi-hundred billion dollar market every year. The customer set is remarkably scalable with standard trailer sizes and requirements for shipping freight. Yet at the same time, trucking companies have trouble hiring and retaining drivers. It’s the perfect recipe for robotic opportunity. I’m intrigued by agricultural robots. I’ve seen dozens of companies attacking every part of the farming equation – from field clearing and preparation, to seeding, to weeding, applying fertilizer, and eventually harvesting. I think there’s a lot of value to be “harvested” here by robots, especially since seasonal field labor is becoming harder to find and increasingly expensive. One enormous challenge in this market, however, is that growing seasons mean that the robotic machinery has a lot of downtime and the cost of equipment isn’t as easily amortized in other markets with higher utilization. The other big challenge is that fields are very, very tough on hardware and electronics due to environmental conditions like rain, dust and mud. There are a ton of important problems to be solved in robotics. The biggest open challenges in my mind are locomotion and grasping. Specifically, I think that for in-building applications, robots need to be able to do all the thing which humans can do – specifically opening and closing doors, climbing stairs, and picking items off of shelves and putting them down gently. Plenty of startups have tackled subsets of these problems, but to date no one has built a generalized solution. To be fair, to get to parity with humans on generalized locomotion and grasping, it’s probably going to take another several decades. Overall, I feel like the funding environment for robotics is about right, with a handful of overfunded areas (like autonomous passenger vehicles). I think that the most overlooked near-term opportunity in robotics is teleoperation. Specifically, pairing fully automated robotic operations with occasional human remote operation of individual robots. Starship Technologies is a perfect example of this. Starship is actively deploying local delivery robots around the world today. Their first major deployment is at George Mason University in Virginia. They have nearly 50 active robots delivering food around the campus. They’re autonomous most of the time, but when they encounter a problem or obstacle they can’t solve, a human operator in a teleoperation center manually controls the robot remotely. At the same time. Starship tracks and prioritizes these problems for engineers to solve, and slowly incrementally reduces the number of problems the robots can’t solve on their own. I think people view robotics as a “zero or one” solution when in fact there’s a world where humans and robots work together for a long time.
Source: TechCrunch
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Keywords:
Robotics • Venture capital • TechCrunch • Robotics • Technology • Innovation • Artificial intelligence • Computing • Big data • Computer hardware • Investment • Robotics • Robotics • Industry • Labour economics • Automation • Delivery drone • Machine vision • Data • Pitch book • TechCrunch • 1,000,000,000 • Investment • Robotics • Investment • Venture capital • Legal personality • Economic growth • Share (finance) • Opportunity cost • Business model • Robotics • Startup company • Robotics • Service (economics) • Economic growth • Robotics • Performance indicator • Scuba diving • Automation • Human • Transport • Climate change • Evolution • Regulation • Natural environment • Robotics • Time • Robotics • Market (economics) • Startup company • Industry • TechCrunch • Industry • Software • Time • Artificial intelligence • Computer hardware • Robotics • Company • Turnover (employment) • Research • Science • Reality • Environmental science • Robotics • Employment • Economics • Maintenance, repair, and operations • Logistics • Microeconomics • Construction • Robotics • Capability management • Renin–angiotensin system • Robot as a service • Robotics • Enterprise software • Robotics • Labour economics • Agriculture • Robotics • Industry • Investment • Technology • Momentum • Hot Space • Islamic Golden Age • Industrial robot • Welding • Robot • Automotive industry • Assembly line • Robot • Deep learning • Machine vision • Robotics • Robotics • Labour economics • Road transport • Highway • Autonomous car • Lane • Road • Traffic • United States • Robotics • Agriculture • Robotics • Agriculture • Deforestation • Tea • Sowing • Weed control • Fertilizer • Harvest • Value (economics) • Season • Labour economics • Market (economics) • Mean • Robotics • Military technology • Market (economics) • Computer hardware • Electronics • Rain dust • Robotics • Motion (physics) • Robot • Weak solution • Purchasing power parity • Motion (physics) • Natural environment • Robotics • Autonomy • Robotics • Teleoperation • List of automated urban metro subway systems • Robotics • Human • Teleoperation • Robot • Starship Technologies • George Mason University • Virginia • Active Robots • Autonomy • Human • Teleoperation • Robot • Time • Starship • Robot • Problem solving • Robotics • Fact • Earth • Human • Robot • Time •
The Valley’s affinity for robotics shows no signs of cooling. Technical enhancements through innovations like AI/ML, compute power and big data utilization continue to drive new performance milestones, efficiencies and use cases.
Despite the old saying, “hardware is hard,” investment in the robotics space continues to expand. Money is pouring in across robotics’ billion-dollar sub verticals, including industrial and labor automation, drone delivery, machine vision and a wide range of others.
According to data from Pitchbook and Crunchbase, 2018 saw new highs for the number of venture deals and total invested capital in the space, with roughly $5 billion in investment coming from nearly 400 deals. With robotics well on its way to again set new investment peaks in 2019, we asked 13 leading VCs who work at firms spanning early to growth stages to share what’s exciting them most and where they see opportunity in the sector:
Participants discuss the compelling business models for robotics startups (such as “Robots as a Service”), current valuations, growth tactics and key robotics KPIs, while also diving into key trends in industrial automation, human replacement, transportation, climate change, and the evolving regulatory environment.
Which trends are you most excited in robotics from an investing perspective?
How much time are you spending on robotics right now? Is the market under-heated, overheated, or just right?
Are there startups that you wish you would see in the industry but don’t? Plus any other thoughts you want to share with TechCrunch readers.
Three years ago, the most compelling companies to us in the industrial space were in software. We now spend significantly more time in verticalized AI and hardware. Robotic companies we find most exciting today are addressing key driver areas of (1) high labor turnover and shortage and (2) new research around generalization on the software side. For many years, we have seen some pretty impressive science projects out of labs, but once you take these into the real world, they fail. In these changing environmental conditions, it’s crucial that robots work effectively in-the-wild at speeds and economics that make sense. This is an extremely difficult combination of problems, and we’re now finally seeing it happen. A few verticals we believe will experience a significant overhaul in the next 5 years include logistics, waste, micro-fulfillment, and construction. With this shift in robotic capability, we’re also seeing a shift in customer sentiment. Companies who are used to buying outright machines are now more willing to explore RaaS (Robot as a Service) models for compelling robotic solutions – and that repeat revenue model has opened the door for some formerly enterprise software-only investors. On the other hand, companies exploring robotics in place of tasks with high labor shortages, such as trucking or agriculture, are more willing to explore per hour or per unit pick models. Adoption won’t be overnight, but in the medium term, we are very enthusiastic about the ways robotics will transform industries. We do believe investing in this space requires the right technical know-how and network to evaluate and support companies, so momentum investors looking to dip their hand into a hot space may be disappointed.
We’re entering the early stages of the golden age of robotics. Robotics is already a huge, multibillion-dollar market – but today that market is dominated by industrial robotics, such as welding and assembly robots found on automotive assembly lines around the world. These robots repeat basic tasks, over and over, and are usually separated by caged walls from humans for safety. However, this is rapidly changing. Advances in perception, driven by deep learning, machine vision and inexpensive, high-performance cameras allow robots to safely navigate the real world, escape the manufacturing cages, and closely interact with humans. I think the biggest opportunities in robotics are those which attack enormous markets where it’s difficult to hire and retain labor. One great example is long-haul trucking. Highway driving represents one of the easiest problems for autonomous vehicles, since the lanes tend to be well-marked, the roads have gentle curves, and all traffic runs in the same direction. In the United States alone, long haul trucking is a multi-hundred billion dollar market every year. The customer set is remarkably scalable with standard trailer sizes and requirements for shipping freight. Yet at the same time, trucking companies have trouble hiring and retaining drivers. It’s the perfect recipe for robotic opportunity. I’m intrigued by agricultural robots. I’ve seen dozens of companies attacking every part of the farming equation – from field clearing and preparation, to seeding, to weeding, applying fertilizer, and eventually harvesting. I think there’s a lot of value to be “harvested” here by robots, especially since seasonal field labor is becoming harder to find and increasingly expensive. One enormous challenge in this market, however, is that growing seasons mean that the robotic machinery has a lot of downtime and the cost of equipment isn’t as easily amortized in other markets with higher utilization. The other big challenge is that fields are very, very tough on hardware and electronics due to environmental conditions like rain, dust and mud. There are a ton of important problems to be solved in robotics. The biggest open challenges in my mind are locomotion and grasping. Specifically, I think that for in-building applications, robots need to be able to do all the thing which humans can do – specifically opening and closing doors, climbing stairs, and picking items off of shelves and putting them down gently. Plenty of startups have tackled subsets of these problems, but to date no one has built a generalized solution. To be fair, to get to parity with humans on generalized locomotion and grasping, it’s probably going to take another several decades. Overall, I feel like the funding environment for robotics is about right, with a handful of overfunded areas (like autonomous passenger vehicles). I think that the most overlooked near-term opportunity in robotics is teleoperation. Specifically, pairing fully automated robotic operations with occasional human remote operation of individual robots. Starship Technologies is a perfect example of this. Starship is actively deploying local delivery robots around the world today. Their first major deployment is at George Mason University in Virginia. They have nearly 50 active robots delivering food around the campus. They’re autonomous most of the time, but when they encounter a problem or obstacle they can’t solve, a human operator in a teleoperation center manually controls the robot remotely. At the same time. Starship tracks and prioritizes these problems for engineers to solve, and slowly incrementally reduces the number of problems the robots can’t solve on their own. I think people view robotics as a “zero or one” solution when in fact there’s a world where humans and robots work together for a long time.
Source: TechCrunch
Powered by NewsAPI.org
Keywords:
Robotics • Venture capital • TechCrunch • Robotics • Technology • Innovation • Artificial intelligence • Computing • Big data • Computer hardware • Investment • Robotics • Robotics • Industry • Labour economics • Automation • Delivery drone • Machine vision • Data • Pitch book • TechCrunch • 1,000,000,000 • Investment • Robotics • Investment • Venture capital • Legal personality • Economic growth • Share (finance) • Opportunity cost • Business model • Robotics • Startup company • Robotics • Service (economics) • Economic growth • Robotics • Performance indicator • Scuba diving • Automation • Human • Transport • Climate change • Evolution • Regulation • Natural environment • Robotics • Time • Robotics • Market (economics) • Startup company • Industry • TechCrunch • Industry • Software • Time • Artificial intelligence • Computer hardware • Robotics • Company • Turnover (employment) • Research • Science • Reality • Environmental science • Robotics • Employment • Economics • Maintenance, repair, and operations • Logistics • Microeconomics • Construction • Robotics • Capability management • Renin–angiotensin system • Robot as a service • Robotics • Enterprise software • Robotics • Labour economics • Agriculture • Robotics • Industry • Investment • Technology • Momentum • Hot Space • Islamic Golden Age • Industrial robot • Welding • Robot • Automotive industry • Assembly line • Robot • Deep learning • Machine vision • Robotics • Robotics • Labour economics • Road transport • Highway • Autonomous car • Lane • Road • Traffic • United States • Robotics • Agriculture • Robotics • Agriculture • Deforestation • Tea • Sowing • Weed control • Fertilizer • Harvest • Value (economics) • Season • Labour economics • Market (economics) • Mean • Robotics • Military technology • Market (economics) • Computer hardware • Electronics • Rain dust • Robotics • Motion (physics) • Robot • Weak solution • Purchasing power parity • Motion (physics) • Natural environment • Robotics • Autonomy • Robotics • Teleoperation • List of automated urban metro subway systems • Robotics • Human • Teleoperation • Robot • Starship Technologies • George Mason University • Virginia • Active Robots • Autonomy • Human • Teleoperation • Robot • Time • Starship • Robot • Problem solving • Robotics • Fact • Earth • Human • Robot • Time •