Applied Intuition uses the same fundamental software platform across cars, trucks, boats, and construction equipment. This is possible because all are machines interacting with the physical world governed by consistent laws of physics, enabling a scalable "Teslification" of multiple industrial sectors with a single core technology.

Google's robotics strategy isn't to build its own hardware, but to provide the dominant AI "brain." CEO Demis Hassabis envisions the Gemini Robotics model being used by many different robot makers, mirroring the Android OS strategy for smartphones.

Gecko Robotics' strategy extends beyond its own hardware. The company is creating a "nervous system" – a data and application layer – to manage fleets of industrial robots from various manufacturers, aiming to orchestrate them to solve high-ROI problems like refinery maintenance.

Hardware vendors like NVIDIA (CUDA) and AMD create fragmented, proprietary software stacks that lock developers in. Modular builds a replacement layer that enables AI models to run consistently across different hardware, giving enterprises choice and flexibility without rewriting code.

While first-wave defense tech leaders like Anduril pursue a vertically integrated "Apple" model (hardware and software), a new approach is emerging. Companies like Auterion are building a common, open operating system for drones from various manufacturers. This "Android for drones" strategy focuses on creating a wide, interoperable ecosystem rather than a closed, proprietary one.

NVIDIA is releasing an open-source, end-to-end AI software and hardware stack for autonomous driving. This strategy mimics Google's Android playbook: by enabling any automaker to build self-driving cars, NVIDIA aims to sell more of its onboard computers and dominate the chip market.

Xiaomi's AI strategy diverges from building general-purpose chatbots. Instead, they focus on 'physical AI' by embedding intelligence into their ecosystem of over a billion connected devices, including phones, appliances, and cars. The goal is to interconnect these devices to enhance user productivity and efficiency in the real world.

By solving the core "intelligence" problem with a foundation model, the barrier to entry for creating novel robotic applications and form factors will dramatically decrease. This will enable a "Cambrian explosion" of hardware creativity, as builders will no longer need to solve AI from scratch for each new idea.

Traditional vehicles have complex, disparate wiring and compute systems. Applied Intuition first simplifies this into a centralized "one box" architecture, which is a necessary step before they can effectively deploy advanced autonomy and AI capabilities, much like developing apps for a modern smartphone.