Start-up Society #104: Cal vs Stanford | ππ»π vs β€οΈπ²π€ (Part 1)
Keeping the American Dream Alive
Welcome to the 104th edition of Start-up Society! This blog highlights some of the most exciting start-ups in the country striving to keep the American Dream alive.
Make sure you check out the previous issue, if you have not already, here!
In honor of the upcoming Big Game on November 19, 2022, we are launching the first part of our Cal vs Stanford rivalry series! In this series, each article will highlight one start-up founded by a UC Berkeley alum and one start-up founded by a Stanford alum. The Big Game is an American college football rivalry game played by the California Golden Bears football team of the University of California, Berkeley and the Stanford Cardinal football team of Stanford University. Both institutions are located in the San Francisco Bay Area. First played in 1892, it is one of the oldest college rivalries in the United States. In even-numbered years, the game is played at Berkeley, while in odd-numbered years it is played at Stanford. Who are you rooting for?
Home Team: California Golden Bears (The University of California, Berkeley)
Covariant
HQ: Berkeley, California
Founded: 2017
Employees: 138 (on LinkedIn)
ABOUT THE COMPANY
Covariant is an AI Robotics company offering intelligent warehouse automation solutions engineered for fulfillment centers to run more efficiently at lower cost. The company has offices in North America, Europe, and Asia.
The companyβs flagship solution is the Covariant Brain: a universal AI robotic platform that allows robots to see, reason, and act on the world around them. It powers physical robots to interact with and learn from dynamic environments and achieve true autonomy.
Covariant has fully automated a variety of pick-and-place applications including order sortation, item induction, good-to-person order picking, and depalletization for a wide range of customers across the globe in industries spanning Fashion/Apparel, Health and Beauty, Pharmaceutical, Industrial Supply, Parcel, Logistics, and General eCommerce Merchandise.
On July 27, 2021, the company announced it raised $80 million in Series C funding, bringing its total capitalization to $147 million. The round was led by returning investor, Index Ventures, with additional participation of Amplify Partners and Radical Ventures. Covariant also added new global investors, Temasek and Canada Pension Plan Investment Board (CPP Investments).
MEET THE TEAM
The founders of Covariant met at UC Berkeley and at OpenAI, an AI research and deployment company headquartered in San Francisco.
Peter Chen, Co-Founder & CEO
Before co-founding Covariant, Peter was a research scientist at OpenAI working on reinforcement learning and generative models.
Peter earned his Ph.D. degree in Electrical Engineering and Computer Sciences (EECS) from UC Berkeley in 2016. His professor was Pieter Abbeel.
Peter obtained his B.A. in Computer Science and Statistics from UC Berkeley in 2014.
Pieter Abbeel, Co-Founder, President & Chief Scientist
Pieter goes both ways. While he is currently a top UC Berekely professor (also Director of the Berkeley Robot Learning Lab and Co-Director of the Berkeley Artificial Intelligence Lab), he is actually a Stanford alum!
Like his co-founders, Pieter was previously a research scientist at OpenAI.
Pieter is also an Investment Partner at AIX Ventures, an AI-focused venture firm investing in early-stage start-ups.
Pieter earned his Ph.D. in Computer Science from Stanford University in 2008. He also received his M.S. in Computer Science from Stanford University in 2002.
Prior, Pieter attended KU Leuven where he obtained a B.S. in Electrical Engineering.
Rocky Duan, Co-Founder & CTO
Previously, Rocky worked at OpenAI as a research scientist.
Rocky obtained his Ph.D. degree from UC Berkeley, where he was advised by Pieter Abbeel. His thesis is Meta Learning for Control.
Tianhao Zhang, Co-Founder
Tianhao earned his Ph.D. degree in Electrical Engineering and Computer Sciences (EECS) from UC Berkeley in 2021. His advisor was Pieter Abbeel.
Prior, he obtained his B.A. in Computer Science and Statistics from UC Berkeley in 2016.
THE START-UP SOCIETY ASSESSMENT
Unimate, the very first industrial robot was introduced in 1961. Since then, millions of industrial robots have been deployed globally in factories, warehouses, and the like. These robots have automated countless dangerous, repetitive tasks and undoubtedly transformed manufacturing.
However, until recently industrial robots have been incapable of thinking independently, they can only do pre-programmed tasks in tightly-controlled environments. They can't understand, learn, or adapt.
βThe Covariant Brain has unlimited learning potential to act on multiple applications across the warehouse. Our current deployments are just the tip of the iceberg on everything that AI Robotics can do for the supply chain and beyond.β - Pieter Abbeel
With the Covariant Brain - that is no longer the case. Sounds like this could replace jobs - maybe Andrew Yang was onto something?
The reality is, consumer demand for physical goods continues to be explosive. And customers want orders fulfilled fast. On the supply side, labor markets are tight and inflation has industry leaders thinking deeply about reducing costs. Given these dynamics, Start-up Society believes the adoption of industrial AI robotics is going to accelerate.
GO DEEPER
Confidence in intelligent robots for warehouse automation at all-time high
Robotic AI firm Covariant raises another $80 million
Industrial AI startup Covariant raises a $40M Series B
Away Team: The Stanford Cardinal (Stanford University)
Rapid Robotics
HQ: San Francisco, California
Founded: 2019
Employees: 96 (on LinkedIn)
ABOUT THE COMPANY
Rapid Robotics is the creator of the first affordable robotic machine operator (RMO) designed for simple machine tasks. The Rapid Machine Operator enables manufacturers to easily deploy a pre-trained robot in hours, moving it between tasks as needed and seeing ROI in months.
The system is available under the RaaS (robotics as a service) model for $25,000 a year and requires absolutely no programming, systems integration, specialized hardware, or robotics skills.
On August 18, 2021, the company announced it raised $36.7 million in Series B funding led by Kleiner Perkins and Tiger Global, with existing investors NEA, Greycroft, Bee Partners, and 468 Capital also participating. The round brings its total funding to $54.2 million and valued the start-up at $192.5 million.
MEET THE TEAM
Jordan Kretchmer, Co-Founder & CEO
Jordan is also an Investor and Advisor at Intuition Capital.
Prior to co-founding Rapid, Jordan founded Livefyre in 2009, the largest cloud-based content and community platform on the web for marketers and publishers. He sold Livefyre to Adobe in 2016 and, through various subsequent advisory and board roles, found himself immersed in the world of manufacturing.
Working with some of the worldβs leading robotics and AI experts, Jordan quickly saw the potential of bringing the service model to manufacturing automation.
Ruddick Lawrence, Co-Founder & CTO
Previously, Ruddick was the VP of Engineering at Carbon Robotics, where he led the entire engineering team. He spent a little over three years at the company as he initially joined as Head of Platform in 2018.
Prior to Carbon, Ruddick was in charge of the manufacturing software group for all new robotic end effectors for the da Vinci robot at Intuitive Surgical. The da Vinci robot is the most-used surgical robot in the world, capable of performing extremely precise medical procedures.
Ruddick earned his M.S. from Stanford University in Mechanical Engineering in 2010, with a focus on mechatronics. He also obtained his B.S. in Mechanical Engineering from Stanford in 2008.
THE START-UP SOCIETY ASSESSMENT
Previously, robotics solutions were too often overly expensive for machine-tending tasks. Between hardware, software, integration, and maintenance, they wound up costing factories more than they saved.
"Until now, only the largest facilities could benefit from robotic automation, but most manufacturing in America is done in smaller factories, which have been deeply challenged by the machine operator shortage. For them, the Rapid Machine Operator provides the additional support they need to thrive.β - Griffin Schroeder, Partner, Tiger Global
The RMO, by contrast, arrives trained and ready to perform the most common machine-tending tasks. It comes with all necessary components, including grippers and computer vision, can be put to work in hours (typical robotics solutions take weeks or even months), and can be easily transferred between tasks as needed, with no retraining necessary.
With Rapidβs OpEx-friendly subscription model, factories can βhireβ an RMO for less than $2,100 per month, a small fraction of the cost of conventional robotics, bringing automation within reach of manufacturers of all sizes.
GO DEEPER
Rapid Robotics Named to Fast Companyβs First-Ever List of the Next Big Things in Tech
Rent-a-robot: Silicon Valleyβs new answer to the labor shortage in smaller U.S. factories
Rapid Robotics raises another $36.7M
Automation-as-a-service startup Rapid Robotics raises $36.7M
Thank you for reading this article! Please leave a comment, like, and subscribe.
Authored byΒ Arteen Zahiri,Β Rumeer Keshwani,Β Elham Chowdhury, &Β Julian Ramcharan