Physical Intelligence

Robotics and related technology are ready for deployment, but the industry hasn’t crossed the threshold into full-scale production. Computational breakthroughs in stunning demonstrations are attention-grabbing, but the realities of industry quickly take over. There is a gap between robotics and artificial intelligence (“physical intelligence”) as it transitions from potential to hardware delivery in a demanding industrial setting. Physical AI and its integration into robotics may become one of the largest markets in history. But it is an industrial problem whose solution is not on a software timeline. In other words, its commercial deployment requires much more systems integration and real-world constraints than a software slide deck contemplates.

Time for Hard Things

With better models, more effective benchmarks, and a framework for constant improvement, now is the time to focus AI on complex, innovative, and transformational tasks. Essentially, AI and models should focus on hard tech. Hard tech refers to businesses rooted in advanced engineering and scientific innovation, often involving the development of physical products or systems that address complex challenges. Beyond drones, robots, and AI-driven hardware, the following are prominent examples of hard tech opportunities across industries. AI-driven hard tech is creating new business models and industries, such as personalized medicine, autonomous logistics, smart infrastructure, and agentic AI platforms that autonomously manage complex operations, reshaping the competitive landscape and unlocking new avenues for value creation. As a result, businesses and professionals who embrace interdisciplinary skills and continuous learning will thrive in the hard tech ecosystem.