Jay Li acknowledges that a lawsuit from Tesla is an unwelcome challenge for any nascent startup. However, he believes the experience has ultimately strengthened his company, Proception.
In an exclusive interview with TechCrunch, Li described the ordeal as "a resilience test, or pressure test." He added, "People say that what doesn’t kill you makes you stronger, right?"
Last year, Li, a former technical lead on Tesla’s Optimus humanoid robot program, faced accusations from his ex-employer of misappropriating trade secrets to establish Proception. Following several months of legal contention, a settlement was reached, leading to the dismissal of the lawsuit by Tesla earlier this month. (Tesla declined to comment on the matter.)
With the legal dispute behind him, Li is now focused on what he considers an even more formidable challenge: developing robotic hands with human-like functionality.
To advance this goal, Proception announced on Monday the successful closure of an $11 million seed funding round. The round was spearheaded by First Round Capital, with additional investments from Y Combinator and the early-stage fund BoxGroup.
Simultaneously, Proception disclosed on Monday that it has begun shipping the initial consignment of its "high-dexterity robotic hand" to "researchers and robotics companies," and is now accepting broader orders. Li articulated the company's ambition to become the foremost supplier of robotic hands for organizations seeking to avoid the significant investment in time and resources required to develop "dextrous manipulation" capabilities internally.
Despite a substantial influx of capital and focus into the robotics sector, Li contends that insufficient attention has been directed towards enabling robotic hands to genuinely emulate human dexterity.
Ironically, one of the most prominent figures highlighting this engineering hurdle is Li's former employer, Tesla CEO Elon Musk, who has publicly stated that developing effective robot hands remains among the most significant unsolved engineering challenges.
Although Musk has suggested that Optimus robots could be deployed in factories within a few years, the prevailing expert opinion indicates that achieving human-level dexterity in robotic hands is still a distant prospect. Kevin Lynch, director of Northwestern University’s Center for Robotics and Biosystems, informed The Wall Street Journal last year that his team estimates it will take a decade before such hands are "functional and useful and able to do some of the things that humans do."
Li, however, is confident that Proception can accelerate this timeline significantly, primarily due to their innovative approach to data collection.
Currently, the majority of companies developing humanoid robots rely on teleoperation for system training. This method involves a human operator wearing a virtual reality headset to perceive the robot's environment and remotely manipulate objects, allowing the robot to learn from these human-generated commands.
Li points out a significant limitation of this method: the teleoperator lacks haptic feedback from the objects the robot interacts with. Furthermore, he noted that this approach is constrained by the finite number of robots a company possesses at any given time.
Proception's innovative solution utilizes a sensor-equipped glove. As detailed in their press release, human testers wearing these gloves (alongside a headset) enable Proception and its clients to gather "human hand interaction data without requiring a robot in the loop."
This identical glove also serves as the sensor-rich "skin" for the robotic hand Proception is developing. According to the company, the hand features 22 degrees of freedom and multiple joints per finger, facilitating a "wide range of dexterous motions."
Li explained that this methodology allows Proception and its customers to collect more granular, task-specific data, which in turn enables their robotic hands to achieve a higher degree of human resemblance. He also believes this approach offers superior scalability.
"You need both hardware and data, and those need to come hand-in-hand to get [dextrous manipulation] to work," Li stated. He observed that "a lot of companies solely focus on hardware, or like hardware plus non-scalable data [collection]." In contrast, Proception is "working on this highly dexterous hardware plus highly scalable data. We believe that’s a key combination to solve this problem."
Bill Trenchard, a partner at First Round who spearheaded the investment in Proception, cited this integrated approach as a primary motivation for backing Li.
"We think they will have the best hand in the market, maybe the most sophisticated hand today, and the underlying data and models to support that," Trenchard conveyed to TechCrunch. He emphasized, "Dexterous manipulation is a very, very, very important part of the whole humanoid story going forward, and as many people have said, it’s sort of the last mile of getting these robots to be truly performant."
Trenchard also commended Li for maintaining composure throughout the lawsuit initiated by his former employer.
"He was very upfront with us when this came out, and I think the team did an amazing job of keeping their heads down," Trenchard remarked, concluding, "Jay’s a very strong leader."
Li himself exudes confidence. Having successfully navigated Tesla’s "hardcore litigation department," he shared with TechCrunch that he anticipates Tesla may seek Proception's assistance as his company expands.
"I think it will happen," he affirmed.
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