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Physical AI: The Next Platform Shift Beyond Software and Into the Physical World
- Christopher H. Loo, MD-PhD
- 5 days ago
- 7 min read
Introduction
The next great technology revolution is already here—and it isn’t confined to our screens.
Physical AI—the application of artificial intelligence in the physical world—is moving us from an era dominated by software to one where AI drives cars, delivers food, manages logistics, and reshapes real estate.
If the last two decades were defined by digital breakthroughs—search engines transforming how we find information, social media connecting billions, smartphones putting the internet in our pockets, and the sharing economy redefining asset use—this decade belongs to AI in the physical world.
This is not speculation. The shift is visible on the streets of San Francisco, in autonomous vehicles cruising quietly past human drivers. It’s in delivery robots navigating sidewalks and AI-powered warehouses orchestrating global supply chains. And like past platform shifts, the change is following a familiar pattern: first gradually, then suddenly.
The Gradual Build-Up (Launch Phase)
In 2023, San Francisco became a living laboratory for examples of physical AI in everyday life.When Waymo launched its autonomous ride-hailing service in the city, the vision was bold: fleets of self-driving cars navigating complex urban streets without human drivers.
But in those early months, the reality was far from seamless. Cars would stall mid-intersection, hesitate at crosswalks when a dog wandered by, or pause awkwardly in dense pedestrian zones. They were impressive, but clunky—still learning the choreography of city life.
By early 2024, improvements were noticeable. Waymo vehicles began handling nuanced situations better: merging smoothly in heavy traffic, navigating crowded events without freezing, and responding appropriately to unpredictable hazards. Yet they were still a rare sight—an occasional curiosity rather than a daily mode of transport.
This phase felt like the early internet before broadband—full of potential, but limited by performance and availability. Still, the foundations were being laid for what would become a major shift in transportation and delivery.
The Inflection Point (Acceleration Phase)
By July 2025, San Francisco’s streets told a different story. Physical AI had moved from novelty to normalcy. Waymos were no longer rare; they were everywhere—sliding quietly past ride-hail drivers, picking up passengers in multiple neighborhoods, and doing so with unmatched consistency.
The competitive gap had shifted. A trip from Nob Hill to Downtown that cost $30 with Uber was now $12 with Waymo. And it wasn’t just cheaper—it was faster to get a ride. Wait times that could stretch 10–15 minutes on Uber or Lyft were now often just 3–5 minutes with Waymo.
Safety perceptions changed too. What was once hesitation gave way to trust. Parents began sending their children to school or activities in Waymos without concern—a telling sign of cultural adoption. I once saw a 10-year-old hop into a Waymo alone, as naturally as if it were the family car.
Still, the system has its current limits. Waymo does not yet operate on highways. The company is testing this capability, with cars gathering data on runs to SFO, but always with a safety driver and without carrying paying passengers.
This was the inflection point—the moment when AI in the physical world shifted from promising technology to a better, more affordable, and more trusted alternative to the status quo. And as with past platform shifts—search, social, smartphones, and the sharing economy—once the curve bends upward, adoption accelerates rapidly.
Expansion & Industry Moves
The rise of Physical AI isn’t confined to San Francisco. As of this writing, Waymo has officially deployed in Austin, Texas, marking its first major expansion outside the West Coast since reaching full driverless operations. In Houston, Waymo is actively testing—collecting data and fine-tuning for the city’s unique driving environment before offering rides to the public.
Competitors are moving fast. Uber, once the quintessential symbol of the sharing economy, is now positioning itself for a driverless future. In mid-2025, Uber announced a strategic partnership with Nuro and Lucid Motors to launch a fleet of 20,000 autonomous EVs powered by Nuro’s Level-4 self-driving technology. These vehicles are slated to hit U.S. streets by 2026, scaling nationwide in the years that follow.
Meanwhile, Tesla continues pushing toward its own robotaxi network, leveraging its vast fleet and real-world driving data. The battle lines are forming—not between “AI vs. human drivers,” but among tech giants vying to dominate the AI-powered mobility market.
The competitive energy feels eerily similar to the early days of search engines, social media networks, and smartphone operating systems—when the platforms that would eventually dominate the market were still battling for users, mindshare, and infrastructure. Only this time, the stakes are physical: roads, vehicles, cities, and livelihoods.
Beyond Mobility — Physical AI Across Industries
While autonomous vehicles and robotaxis are the most visible face of Physical AI, they represent only the first wave. The same core technologies—computer vision, advanced robotics, real-time decision-making—are beginning to transform industries far beyond transportation.
In real estate, AI-powered building systems are optimizing energy usage, adjusting lighting and climate based on occupancy patterns, and even predicting maintenance needs before they become urgent repairs. Smart building platforms are already marketed as a differentiator for high-end properties, and over time, these efficiencies will become standard across the industry.
In logistics, AI in supply chain management is driving unprecedented gains in speed and reliability. Fully autonomous delivery robots are handling last-mile fulfillment for food and grocery orders, weaving through pedestrian areas with growing ease. Autonomous trucks—capable of long-haul freight transport—are reducing driver fatigue risks and enabling 24/7 operations.
In urban planning, the early seeds of smart cities are visible. Traffic flows are being coordinated by AI to reduce congestion, while autonomous public transit systems are beginning pilot programs in select metros.
These real-world applications of artificial intelligence are pushing us into a new era—where AI doesn’t just live in the cloud or on a screen, but in the streets, the buildings, and the infrastructure we interact with every day. The transition from software-based innovation to physical AI integration is reshaping both consumer experience and industrial capability, much like smartphones reshaped not just communication, but commerce, media, and culture.
Historical Parallels — Lessons From Previous Platform Shifts
Every major technology wave follows a familiar arc: skepticism, slow adoption, sudden mainstreaming, and eventual ubiquity. We’ve seen it before.
When search engines emerged in the late 1990s, they were clumsy, slow, and limited. But once Google refined the model, they became the gateway to the internet, fundamentally changing how we access knowledge.
Social media began as niche platforms for college students and hobbyists. A decade later, it was the public square, the marketing engine, and the news feed for billions of people worldwide.
Smartphones started as expensive, limited tools for the tech-savvy. Then came the iPhone in 2007—ushering in an era where our most important device fits in our pocket, enabling entire industries like mobile commerce, app development, and real-time communication.
The sharing economy was once a fringe experiment—renting out spare bedrooms or catching rides from strangers seemed unusual, even risky. Today, Airbnb and Uber are embedded in the fabric of urban life.
Physical AI sits at the same kind of inflection point these platforms once faced. The parallels are striking:
A period of awkward early trials, where the technology worked but felt unfamiliar.
Rapid improvement cycles that push the product toward reliability and trust.
A sudden surge in adoption when value (cost, speed, safety) clearly surpasses the incumbent systems.
Just as these earlier platform shifts reshaped the digital economy, Physical AI will redefine the physical economy—how we move, build, deliver, and live.
Opportunities & Risks
The arrival of Physical AI opens the door to transformative opportunities—and equally significant risks.
On the opportunity side, the real-world applications of artificial intelligence promise to make our cities safer, cleaner, and more efficient. Autonomous vehicles could dramatically reduce traffic fatalities caused by human error. AI-powered logistics could shorten delivery times from days to hours while lowering emissions. Smart infrastructure could optimize energy use at scale, cutting costs for businesses and households alike.
But these gains will not come without disruption. The impact of physical AI on jobs and the economy will be profound. Professional drivers—whether in ride-hailing, trucking, delivery, or public transit—face displacement as autonomous systems mature. Service industries that depend on large fleets of human-operated vehicles could be fundamentally restructured, forcing workers into reskilling or entirely new sectors.
Public trust is another hurdle. While early adopters in cities like San Francisco and Austin are embracing AI-powered mobility, others remain skeptical about safety, reliability, and ethical governance. High-profile incidents could slow adoption if the technology is perceived as untested or poorly regulated.
Finally, infrastructure readiness varies widely between cities. Urban areas designed around human-driven vehicles will need significant updates—dedicated lanes, smarter intersections, and robust connectivity—to fully unlock the potential of Physical AI.
We stand at a crossroads: the same forces that could make our physical environment more intelligent and sustainable could also concentrate economic power, widen inequality, and create new vulnerabilities if left unchecked.
Conclusion & Call to Action
The next platform shift is no longer unfolding on our screens—it’s happening in our streets, buildings, and supply chains. Physical AI marks the transition from a software-dominated era to one where artificial intelligence operates in the physical world, transforming transportation, delivery, real estate, logistics, and beyond.
Like search engines, social media, smartphones, and the sharing economy before it, this shift is following a familiar trajectory: first gradually, then suddenly. We’ve already crossed the threshold from experimental novelty to scalable, trusted infrastructure in select markets. The curve is bending upward.
In the years ahead, AI in the physical world will no longer be a differentiator—it will be the baseline. Companies, cities, and individuals who prepare now will thrive in the new ecosystem. Those who ignore it will find themselves displaced as quickly as industries once disrupted by the internet, mobile, and platform economies.
The question isn’t if this transformation will reshape your world, but how quickly you’re ready to adapt to it.
💡 Thoughts? Where do you see the biggest opportunities—or the greatest risks—in the rise of Physical AI?
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