The integration of AI into human-led services will mirror Tesla's approach to self-driving. Humans will remain the primary interface (the "steering wheel"), while AI progressively automates backend tasks, enhancing capability rather than eliminating the human role entirely in the near term.

Insiders in top robotics labs are witnessing fundamental breakthroughs. These “signs of life,” while rudimentary now, are clear precursors to a rapid transition from research to widely adopted products, much like AI before ChatGPT’s public release.

The current excitement for consumer humanoid robots mirrors the premature hype cycle of VR in the early 2010s. Robotics experts argue that practical, revenue-generating applications are not in the home but in specific industrial settings like warehouses and factories, where the technology is already commercially viable.

The robotics field has a scalable recipe for AI-driven manipulation (like GPT), but hasn't yet scaled it into a polished, mass-market consumer product (like ChatGPT). The current phase focuses on scaling data and refining systems, not just fundamental algorithm discovery, to bridge this gap.

Current home security systems are passive. The next major opportunity lies in active deterrence, moving beyond cameras to physical, patrolling robots. The market wants a "better big dog"—a device that can actively patrol property and deter threats, a more practical application of robotics than consumer humanoids.

While the US prioritizes large language models, China is heavily invested in embodied AI. Experts predict a "ChatGPT moment" for humanoid robots—when they can perform complex, unprogrammed tasks in new environments—will occur in China within three years, showcasing a divergent national AI development path.

Contrary to public perception that advanced home robotics are decades away, insiders see tasks like cooking a steak as achievable in under five years. This timeline is based on behind-the-scenes progress at top robotics companies that isn't yet widely visible.

AR and robotics are bottlenecked by software's inability to truly understand the 3D world. Spatial intelligence is positioned as the fundamental operating system that connects a device's digital "brain" to physical reality. This layer is crucial for enabling meaningful interaction and maturing the hardware platforms.

The most profound near-term shift from AI won't be a single killer app, but rather constant, low-level cognitive support running in the background. Having an AI provide a 'second opinion for everything,' from reviewing contracts to planning social events, will allow people to move faster and with more confidence.