“iPhone Moment” Nears For Humanoid Robots

Brett Adcock, founder of Archer Aviation, who left the flying taxi company to pursue humanoid robotics and the deployment of Artificial General Intelligence, recently shared how his team at Figure AI developed a humanoid robot in just 31 months, achieving the robot’s first successful walk within a year. 

Adcock recently spoke at the 2025 Abundance360 summit in Los Angeles and described how humanoid robots are the ultimate “deployment vector” for AGI, comparing what’s happening in robotics to an “iPhone moment”- a game-changing breakthrough when a new product suddenly transforms an industry. 

Adcock said that Figure AI designs a new hardware platform every 12 to 18 months. He noted that his startup has secured commercial customers like BMW… 

BMW x Figure Update

This isn’t a test environment—it’s real production operations

Real-world robots are advancing our Helix AI and strengthening our end-to-end autonomy to deploy millions of robots pic.twitter.com/p8a7OD7r3U

— Figure (@Figure_robot) March 31, 2025

He forecasts that Figure AI’s humanoid robots will be affordable, around $20,000 to $30,000, allowing for widespread adoption in both the workplace and the home. 

Meet Helix, our in-house AI that reasons like a human

Robotics won’t get to the home without a step change in capabilities

Our robots can now handle virtually any household item: pic.twitter.com/Wsx5s8Qelc

— Figure (@Figure_robot) February 20, 2025

Here’s a summary of Adock’s conversation about humanoid robotics and how the industry is in the midst of an “iPhone moment”: 

• (00:00–01:42): Brett Adcock, founder of Figure, rapidly launched humanoid robots from scratch in 31 months. He sees humanoid robots as the ultimate “deployment vector” for AGI (Artificial General Intelligence), comparable to an “iPhone moment” happening now.

• (02:21–03:30): Adcock stresses that giving AGI a physical body is critical to avoid dystopian outcomes where powerful AI remains trapped in servers. Humanoids allow AGI to learn and act through transfer learning and multitasking.

• (06:24–07:54): Commercial robots are already operating at BMW’s largest US plant (Spartanburg, SC), autonomously performing repetitive manufacturing tasks. Demand is growing, with a second logistics customer signed.

• (08:28–09:58): Long-term goal: humanoid robots for home use, priced around $20,000–$30,000, leasing for about $300/month. At that rate, Adcock envisions multiple robots per home doing chores like dishwashing, laundry, dog-walking.

• (10:40–12:28): Figure’s success is attributed to assembling a world-class, hardworking team with a laser-focused, high-intensity culture (working 5–7 days a week in person) and a shared “ship-product” mindset.

• (14:30–15:43): To succeed, Figure had to solve three hard problems: build ultra-reliable humanoid hardware, teach humanoids through neural nets (not hand-coded controls), and generalize actions to unfamiliar tasks via language instructions.

• (16:51–19:17): Figure abandoned external AI vendors like OpenAI and built its own large vision-language-action AI model called Helix. Robots using Helix can generalize and complete new tasks, like putting groceries away without prior training.

• 22:04–25:45): Workforce applications (manufacturing, logistics, healthcare) are booming, with massive demand. Home deployment is harder but accelerating rapidly. Internal alpha tests in engineers’ homes are planned this year, with full rollout projected within this decade.

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As we’ve previously described, AI, semiconductors, eVTOL, and photonics—are poised to define the great power nations in the 2030s and why the US needs to urgently re-shore or at least friend-shore those critical supply chains.

Entirely relying on China for critical minerals and magnet exports to power drones and humanoid robots has left Tesla delaying its series production of Optimus robot. 

America’s robotics industry can’t have an “iPhone moment” if it lacks control over the critical supply chains needed to build these technologies.