Key Takeaways
- Skild AI has secured $300 million in a Series A funding round, bringing its valuation to $1.5 billion.
- This investment round was led by Lightspeed Venture Partners, Coatue, SoftBank Group, and Jeff Bezos through Bezos Expeditions.
- Skild AI is developing a scalable, general-purpose AI model for robotics that is trained on significantly more data points than its competitors.
- The company aims to tackle critical labor shortages in industries like healthcare, construction, warehousing, and manufacturing.
Skild AI has raised $300 million in a Series A funding round Led by Lightspeed Venture Partners, Coatue, SoftBank Group, and Jeff Bezos through Bezos Expeditions. The Series A round also saw participation from Felicis Ventures, Sequoia, Menlo Ventures, General Catalyst, CRV, Amazon, SV Angel, and Carnegie Mellon University. This influx of capital brings Skild AI to a valuation of $1.5 billion.
Skild AI is at the forefront of developing scalable foundational models for robotics, distinguishing itself by training its models on exponentially more data points than its competitors.
The company aims to create a shared, general-purpose brain capable of powering a wide range of robots for diverse tasks, including manipulation, locomotion, and navigation. This approach contrasts sharply with the industry norm of designing robots for specific, vertical applications.
“The large-scale model we are building demonstrates unparalleled generalization and emergent capabilities across robots and tasks, providing significant potential for automation within real-world environments,” said Deepak Pathak, CEO and Co-Founder of Skild AI. “We believe Skild AI represents a step change in how robotics will be scaled, and has the potential to change the entire physical economy.”
Skild AI’s technology aims to address critical labor shortages across various industries. The U.S. Chamber of Commerce reports a gap of 1.7 million more job openings than available workers, with projections indicating 2.1 million unfulfilled manufacturing jobs by 2030 according to the National Association of Manufacturers. Skild AI envisions its general-purpose robots performing tasks alongside humans in sectors like healthcare, construction, warehousing, and manufacturing, as well as taking on dangerous jobs such as those on oil rigs and in machine rooms.
“With general-purpose robots that can safely perform any automated task, in any environment, and with any type of embodiment, we can expand the capabilities of robots, democratize their cost, and support the severely understaffed labor market,” added Abhinav Gupta, President and Co-Founder of Skild AI.
The excitement around Skild AI’s potential is palpable among its investors. Raviraj Jain, Partner at Lightspeed Venture Partners, praised the company’s rapid advancements and its potential to redefine machine capabilities. “Deepak and Abhinav have been catalysts of advancements in robotics, and their innovation around leveraging the core principles of foundation models into the real world puts the industry on the path of general-purpose robotics,” Jain said.
Stephanie Zhan, Partner at Sequoia Capital, compared Skild AI’s breakthrough to the transformative impact of GPT-3 in digital intelligence. “A GPT-3 moment is coming to the world of robotics,” she stated, emphasizing her conviction in the company’s vision since its seed round.
The founders, both Carnegie Mellon University professors with a combined 25 years of experience in robotics and AI, have been pivotal in numerous industry breakthroughs. Their expertise and the robust Skild AI team, which includes talent from Meta, Tesla, Nvidia, Amazon, Google, and top universities, underscore the company’s capacity to revolutionize the robotics landscape.
“Their scalable approach to building foundational models for robot manipulation and locomotion could revolutionize robotics, shifting from pre-programmed to dynamic, adaptable robots,” noted Sri Viswanath, General Partner at Coatue and former CTO of Atlassian.
With this significant funding, Skild AI plans to scale its models and training datasets for future commercial deployment, and expand its team across various domains. The company’s long-term ambition is to develop artificial general intelligence (AGI) rooted in the physical world, challenging the prevailing notion that AGI can only emerge from digital knowledge.
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