If you didn’t get a chance to listen to our most recent episode of the Collective Intelligence Community Podcast, go listen to our very own Thomas Joshi’s interview with Rajiv Ayyangar, CEO of Product Hunt. In this episode, they discuss what product development looks like in the age of LLMs, and the product categories that have been resurrected by AI! 

The vision of building humanoid robots is not a new concept. This idea has captivated our imagination for the last 30 years through countless references in hit shows and blockbuster films  like R2-D2 (Star Wars), Hal 9000 (2001: A Space Odyssey), and Dolores Abernathy (Westworld). These characters often explore themes of autonomy, morality, and the blurring lines between humans and machines, reflecting the immense potential and societal fears about the future of artificial general intelligence (AGI) and robotics. That being said, the timeline for building a truly autonomous humanoid robot that could respond to natural language inputs and seamlessly integrate into everyday life always felt far from reality… until now.    

Key advancements in robotics and AI coupled with rising economic challenges have accelerated R&D dollars into the technology. Humanoid robots promise a generalizable form factor that understands its physical environment, can collaborate seamlessly with humans across multi-modal inputs/outputs, and most importantly leverages reinforcement learning with their general-purpose models to solve a wide range of human applications without significant task-specific training data. Today, many of the robotic platforms deployed in industrial environments focus on a particular use case (pick and place, inventory counting, pallet movement) and struggle to adapt to a changing set of labor bottlenecks. Nevertheless, the need for increases in automation is nascent, and the rise of generative AI is a key enabler for building generalizable intelligence into robotic platforms. On the market side, global labor shortages, inflationary cost pressures, productivity challenges, and rising workplace safety concerns are driving exploratory investment. The US Census Bureau projects the US manufacturing sector alone will face a labor shortage of more than two million workers by 2030. On the tech side, breakthroughs in core technologies like robotic foundation models and language models as well as enabling hardware such as robotic skeletons, batteries, edge compute devices, and sensors are decreasing the cost and complexity of building these autonomous systems. 

Humanoid robots require multi-model AI and computer vision to emulate human cognitive skills and dexterity, and off-the-shelf LLMs are already proving they can surpass human benchmarks across general reasoning tasks. Additionally, the emergence of large action models–AI models that can translate human intentions into action–both open and closed source are further democratizing the ecosystem. In March, Nvidia announced Project GR00T, a general-purpose foundation model specifically trained for humanoid robots. As part of the initiative, they also unveiled a new compute architecture for running these foundation models on the edge and major upgrades to their robotics development platform Isaac. 

Venture excitement is growing precipitously for this application of physical-digital convergence, and 2024 has already seen record funding in the segment–most notably, Figure’s $675M Series B and open partnership with Nvidia, OpenAI, and Microsoft to accelerate development.

The rise in funding is a hint that the segment is reaching a key inflection point. The technology and enabling ecosystem is maturing to meet customer requirements, production is ramping, and enterprise adoption is accelerating past the pilot phase. BMW has signed a commercial agreement to begin deploying Figure robots at a US facility this year, and as part of the announcement Brett Adcock, the CEO of Figure, proclaimed “single-purpose robotics have saturated commercial markets for decades, but the potential of general purpose robotics is completely untapped.” Figure is just one example of a humanoid robot that has gained virality as of late. Other competitors that are beginning to scale up production to meet customer demand include: 

Although customers are beginning to deploy humanoid robots in production environments, the industry is still early and many challenges remain. Most of the early leaders have been forced to deploy vertically integrated solutions, but the future will benefit from greater standardization across form factor and hardware-software interoperability to further drive down costs, increase performance, and lower the barrier to entry for new innovators. Additionally, an increase in robotic engineers and the maturity of developer platforms are poised to overcome continuous challenges around on-device inference, training costs, battery life, and edge compute limitations. 

The evolution from a fictional sci-fi concept to reality is closer than ever, and the potential for humanoid robots to transform human life from industrial automation to everyday tasks should not be taken lightly. In February, Goldman Sachs released a report that projects the market size for humanoid robots to increase from less than $500M in 2023 to $38B by 2035 (a sixfold increase from their original projections). As these robots become increasingly human-like and their ability to not just augment but completely replace human labor, ethical considerations will grow. In a not so far out reality that mirrors a Westworld-like future, how will we interact with these robots? How do we stay ahead? What kind of new jobs and specialties will be created for humans? I guess we’ll have to wait to find out!

With that, I hope you enjoyed the newsletter and would love to hear how the community sees the future of humanoid robotics transforming human life and industrial productivity! If you would like to share your thoughts, hit up Eric on the community Slack, or reach out via email at [email protected] for a feature in our next newsletter! 

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About Eric Fett

Eric leads the development of the newsletter and online presence. He is currently an investor at NGP Capital where he focuses on Series A/B investments across enterprise AI, cybersecurity, and industrial technology. He’s passionate about working with early-stage visionaries on their quest to create a better future. When not working, you can find him on a soccer field or at a sushi bar! 🍣