Brett Adcock - Shawn Ryan’s First Interview with a Robot | SRS #292
Quick Read
Summary
Takeaways
- ❖Figure AI's humanoid robots, like Figure 3, are 5'6" and 135 lbs, capable of tasks like folding laundry and operating in manufacturing, powered entirely by neural networks.
- ❖Archer Aviation's electric vertical takeoff and landing (EVTOL) aircraft aim to enable 10-minute urban flights for the cost of an Uber, with FAA certification in progress.
- ❖Cover uses terahertz radar technology, originally developed by NASA JPL for military standoff detection, to passively scan for concealed weapons in schools and public spaces.
- ❖The AI industry is not in a bubble; Adcock believes the next 36 months will see the most transformative technological events ever, leading to an 'age of abundance' through synthetic human productivity.
- ❖Humanoid robots are expected to be deployed in businesses first due to lower environmental variability and higher commercial value, before widespread consumer adoption.
- ❖The biggest challenge for home robotics is achieving 'general purposeness' – a robot capable of performing diverse tasks in an unpredictable home environment without prior training for that specific space.
- ❖Adcock self-funded Figure AI's initial year and Cover's development, highlighting the difficulty in attracting traditional VC funding for deep tech hardware ventures.
- ❖Figure AI successfully ran robots for six months, 10-hour shifts daily at a BMW manufacturing plant, demonstrating hardware durability and the shift to neural network-based control.
- ❖Hark, Adcock's new AI lab, is developing post-iPhone AI hardware and multimodal models for highly personalized, always-on AI assistants with near-perfect memory.
- ❖The safety standard for Archer's EVTOL aircraft is 1 in a billion hours of reliability before a catastrophic event, a benchmark set by the FAA for passenger air travel.
Insights
1Figure AI's Rapid Humanoid Development and Neural Network Dominance
Figure AI developed its first walking humanoid robot (Figure 1) within 12 months of incorporation and has since advanced to Figure 3, a 5'6", 135 lb robot capable of complex tasks. The company transitioned from hybrid code-and-neural-net control to an almost entirely neural network-based system (Helix 2) after observing that coded parts struggled with variability in real-world environments. This neural-net approach allows robots to learn and generalize tasks like package logistics and laundry folding, even with compliant, moving objects, which was previously intractable with traditional coding.
Figure 1 walked in under 12 months (). Figure 2s worked 10-hour shifts daily for six months at BMW (). Helix 2 removed over 100,000 lines of code, making the system almost entirely neural net-driven (). Robots now run 24/7 shifts, autonomously swapping for charging (). Neural nets excel in high-variability environments like folding laundry or handling moving packages ().
2Archer Aviation's Vision for Urban Air Mobility
Archer Aviation is developing electric vertical takeoff and landing (EVTOL) aircraft to address urban gridlock. These 'flying cars' combine vertical lift (like helicopters) with winged flight (like airplanes) and are fully electric for cost and safety. The goal is to provide 10-minute city commutes for the price of an Uber, leveraging the three-dimensional nature of airspace to create exponentially more routes than ground transport. The FAA's stringent 1x10^-9 reliability standard (one catastrophic event per billion hours) is the primary hurdle for passenger certification.
EVTOLs can fly in 10 minutes for the cost of an Uber (02:). Airspace is three-dimensional, allowing infinite 'roads' (). FAA certification requires 1x10^-9 reliability (). Archer aircraft are already flying weekly in California ().
3Cover's Terahertz Weapon Detection for School Safety
Cover is deploying NASA Jet Propulsion Lab's terahertz (millimeter wave) radar technology to passively detect concealed weapons in K-12 schools. This system can scan individuals from 10-30 meters away as they walk through entrances, identifying guns, knives, and other objects hidden in pockets, waistbands, or backpacks. The technology was originally developed for military standoff detection. Cover's innovation includes reducing the cost of critical components from $50,000 to $7 per chip, making the system affordable for schools. The primary goal is to prevent the 90%+ of school shootings that are unplanned, by detecting weapons before they are brandished.
Technology from NASA JPL for standoff detection (). Detects concealed weapons in pockets, waistbands, backpacks (). Reduced chip cost from $50,000 to $7 (). Aims to prevent 90%+ of unplanned school shootings ().
4The 'Age of Abundance' Driven by AI and Synthetic Humans
Adcock refutes the notion of an 'AI bubble,' asserting that the technology is in its earliest stages and will lead to unprecedented productivity gains. He envisions a future where AI, embodied in humanoid robots and digital assistants, performs 'busy work' in both physical and digital realms. This proliferation of 'synthetic humans' will drastically increase GDP per capita and reduce goods and service prices, ushering in an 'age of abundance' by delegating mundane tasks and freeing human cognitive load.
AI is not in a bubble, 'scratching the surface' (). AI will lead to the 'greatest increase in productivity' and 'reduce goods and service prices to unprecedented levels' (). Envisions AI running a 'Brett Adcock operating system' to manage his life ().
5Hark: The Post-iPhone Era of Personalized AI
Hark is Adcock's new AI lab, self-funded with $100 million, focused on developing the next generation of AI hardware and multimodal models beyond current chatbots. The goal is to create 'human-centric AI' that is always on, always thinking, and deeply personal, with near-perfect memory of a user's life and preferences. This family of devices is intended to replace current phones and computers, acting as intelligent, proactive assistants and even accountability coaches.
Hark is a new AI lab, self-funded with $100 million (). Aims to build 'human-centric AI' and 'what comes after the iPhone for AI' (). AI systems will be always on, always thinking, with near-perfect memory ().
Bottom Line
The future of urban travel is three-dimensional, with air mobility (EVTOLs) and subterranean tunnels (Boring Company) providing exponential capacity beyond current 2D roads.
This implies a fundamental re-architecture of city planning and infrastructure, moving away from surface-level congestion towards multi-layered transport networks.
Investment in urban air infrastructure (vertiports), advanced tunnel boring technology, and the regulatory frameworks to manage these complex, multi-modal systems.
The 'holy grail' of robotics is a general-purpose humanoid machine that can perform any human task in any environment, achieved through neural networks rather than traditional coding.
This shift from task-specific programming to generalized AI learning unlocks the potential for robots to operate in highly variable, unstructured environments like homes, which were previously too complex.
Developing robust data collection and training methodologies for diverse physical tasks, and creating hardware platforms that are highly adaptable and durable for unpredictable use cases.
The current perception of AI as 'scary' or job-replacing leads to corporate hesitation, requiring CEO-level approval for humanoid robot deployments, even in industrial settings.
This highlights a significant public relations and ethical communication challenge for AI and robotics companies, beyond just technical and economic benefits.
Strategic communication and education initiatives are needed to frame AI and robotics as tools for human augmentation and societal abundance, rather than threats, to accelerate adoption and mitigate regulatory friction.
Opportunities
AI-Powered Personalized Digital Assistants (Hark)
Develop a family of AI-native hardware devices and multimodal AI models that offer deeply personalized, always-on assistance with near-perfect memory, replacing current phones and computers. This AI would manage digital and physical tasks, act as a coach, and understand user preferences over time.
Affordable Terahertz Weapon Detection Systems (Cover)
Commercialize advanced terahertz radar technology, miniaturized into cost-effective chips, for passive, non-invasive weapon detection in high-traffic public areas like schools, airports, and venues. Focus on high accuracy and low false positives to build trust and prevent unplanned violence.
General-Purpose Humanoid Robot as a Service (Figure AI)
Offer humanoid robots on a subscription basis to commercial and eventually consumer markets. These robots, powered by adaptable neural networks, would perform a wide range of physical tasks (manufacturing, logistics, domestic chores) with high reliability and efficiency, autonomously managing charging and task handoffs.
Key Concepts
Harder Things Are Easier
Starting a company with a significantly harder problem and a larger potential outcome (100x) is often only 3-5x harder in execution. This approach attracts top talent, secures more capital, and targets disproportionately larger markets, leading to greater success despite perceived difficulty. It filters out less committed individuals and creates a compounding advantage.
Lessons
- Entrepreneurs should prioritize 'harder things' with disproportionately larger outcomes, as these attract top talent and capital more effectively, creating a virtuous cycle of innovation and success.
- Founders must cultivate extreme resilience and a 'no-failure' mindset, as the entrepreneurial path is often lonely, lacks a rulebook, and involves significant personal sacrifice and a high probability of failure.
- Focus on building robust hardware that can remain constant while software (neural networks) provides new capabilities, akin to a smartphone, to enable rapid iteration and deployment of new functionalities in robotics.
- When developing AI systems, prioritize deep memory and personalization to create truly 'human-centric' and useful intelligence, moving beyond generic chatbot interactions.
- For deep tech hardware, be prepared to self-fund initial stages, as traditional VCs often shy away from complex, capital-intensive ventures, even those with massive potential.
Notable Moments
Brett Adcock's kids interacting with a humanoid robot, treating it as normal and even getting attached to it.
This highlights the rapid normalization of advanced robotics, particularly among younger generations, and hints at the emotional integration of AI into daily life, raising questions about long-term human-robot relationships.
The Figure AI robot successfully performing a complex task like making coffee using only neural networks, without traditional code.
This demonstration marked a critical turning point for Figure AI, proving the viability of neural networks for complex physical manipulation in unstructured environments, a key step towards general-purpose robotics.
Brett Adcock's decision to 'fire' OpenAI from a partnership because Figure AI's internal team was outperforming them in robot learning and to avoid intellectual property leakage.
This illustrates the intense competition and rapid pace of innovation in the AI and robotics space, where even leading AI labs may not have the specialized expertise for embodied AI, and highlights the importance of proprietary development.
The Cover team miniaturizing a $50,000 terahertz radar component into a $7 chip.
This cost reduction is a critical enabler for widespread adoption of weapon detection technology in budget-constrained environments like K-12 schools, transforming a high-end military technology into an accessible public safety tool.
Quotes
"I'm watching AI in a human body do human work like early. It's early. We don't have, you know, we we don't we at some point here this year, we'll have thousands of robots. We have like, you know, we have hundreds now. Like, but like we need like millions of robots to make an impact. That's just going to take some time and it's going to be crazy cool."
"I mean, that's going to lead to such a productivity um like we measure like GDP per capita like per human but if you're able to make like as many synthetic humans like you know millions billions tens of billions of synthetic humans in the case of the digital world maybe trillions. Um that'll lead to the I mean I think the greatest uh increase in productivity we've ever seen in our lifetime and ultimately like reduce goods and service prices to unprecedented levels like like a true age of abundance."
"There are more states in the robot than atoms in the universe. There's more positions the body can be in. By far. It's much greater number. Um done the math a few times. Very confident in this even though it sounds ridiculous."
"I think it's probably one of the first examples in the world to ever have shown that. And in, you know, this was like game on. This is like we have let's go build a really good human on hardware. Let's make it cheap and really reliable. Let's make sure it can do what humans can from a hardware perspective."
"I have kids and you have kids like you you have a fiduciary duty to go build this."
"Harder things are easier... starting something that could be like a hundred times higher outcome is generally not a 100 times harder. It's probably like three times harder, maybe five times harder, but the total addressable market opportunity is probably millions of times bigger."
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