
I worked on the first iPhone under Steve Jobs before selling Nest for $3.2 billion. AI can change everything when it steps into the physical world
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My old boss Steve Jobs cared about hardware, and it still matters.
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August 26, 2025
12:00 PM
Fortune
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ary·Artificial IntelligenceI worked on the first iPhone under Steve Jobs before selling Nest for $3.2 billion
AI can change everything when it steps into the physical worldBy Matt RogersBy Matt Rogers Matt Rogers is the Cofounder & CEO of Mill, a wasted food prevention company based in San Bruno, CA
Matt is a founder of Incite.org, in early-stage companies built to scale and bring change to the world
Matt co-founded Nest, acquired by Google in 2014 for $3.2B
Prior to Nest, Matt worked with Steve Jobs to build the very first iPhone, as well as device hardware in the 2000s.Steve Jobs holding an iPhone in 2007.SHAUN CURRY/AFP via Getty ImagesSociety loses when builders ship for ’s sake
To paraphrase something my former boss Steve Jobs repeated as we engineered the very first iPhone: The number of megahertz doesn’t matter
Innovation must be dering practical applications into the physical world that imve s
Combining AI with smart hardware and physical infrastructure will ensure the transformation of trillion-dollar industries from manufacturing to life sciences to agriculture
AI will power the future
But in order to do so, it must be paired with physical hardware that makes everyday life better for people
To put this in context, let me something that’s not widely known
The very first iPhone—I’m talking pre-launch, kept deep within the Apple engineering lab—had a click wheel exactly the iPod
We tested the user experience into the ground before confirming that invoking a rotary phone vibe when users scrolled through s and navigated the phone’s was not good
The lesson from Steve Jobs? Making the user’s life more difficult isn’t going to fly
We up scrapping that clunky model for the sleeker one launched in 2007
This same tension—whether new nology is burdensome or helpful—is playing out with AI today
The ’s current chatbot era puts the onus on the user to der the right mpts and commands
What if AI actually made life easier without the overhead? This is what can happen when AI enters the physical world
The physical world matters During a recent trip to China, Nvidia CEO Jensen Huang told students he’d study the physical sciences if he was enrolled today, not software
During a speech in DC, Huang said that AI’s next revolution will take place in the physical world, requiring an understanding of “things the laws of physics, friction, inertia, cause and effect.” Huang nailed it on both sides of the world
While only one or two startups launched today will rise to Nvidia tomorrow, there’s rising interest in supporting the race with capital and engineering expertise—a trend similar to what we experienced with Nest, leading to our acquisition by Google
Back then, building apps with AI took months and years—especially for advanced features computer vision and facial recognition
In fact, it took us a full year to develop a package detection app for the Nest Cam
Now, companies can ship sophisticated AI features in a matter of weeks
Ease and speed enabled by next gen AI infrastructure accelerates real world gress and engineering possibility
What the physical world offers AI innovators: One shot, endless potential Industries with major physical operations, health, robotics, manufacturing, transportation, and agriculture, are trillion-dollar sectors
Reinvention requires time, resources, and a focus on pairing the most advanced software with the most practical hardware
Software can be shipped, iterated, and upgraded constantly
Builders can make adjustments after a duct goes into the market
They can tinker forever
Hardware, on the other hand, requires a mountain of pre-launch work defined by longer development cycles, advanced tooling, and regulatory hurdle jumping
There’s added pressure on hardware founders from the beginning because they truly have one shot at getting the core architecture right prior to shipping a duct that ders what customers need
The go-to-market journey can be long and costly
Shipping physical innovation at scale requires higher upfront costs, supply chain complexity, and safety standards with industry-specific nuance
It’s worth it for founders because success yields competitive advantage across intellectual perty, manufacturing expertise, and brand differentiation. gress reinforces network effects that strengthen data, nology, and infrastructure around hardware
When successful, there’s significant spillover benefits for society: safer infrastructure, more resilient supply chains, and space for human interaction
Hardware companies that enlist next gen AI to put customers first, capture enormous value, introduce infrastructure efficiency, and attract sustainable investment will be leaders in the market
Founders looking for a jumpstart, I recommend taking a page from Apple (smartphone hardware and software) and Tesla (electric vehicles and charging infrastructure) and own the full stack
Apple just announced “a pipeline of hardware” company leaders expect to be important to its “resurgence” as an AI powerhouse
AI operating in the physical world will experience a similar shift from a crowded field to a dominant few that we saw in the browser wars
I believe the world is better off if American companies are in the mix
They can be because we have the investor community, engineering and startup talent, and can build the physical world infrastructure scale needed to fuel the next wave of AI innovation
And once physical AI becomes viable, literally every industry operating on last gen , work, and logistics becomes ready for reinvention
I believe the next AI revolution will reshape everything we do from saving s to building houses to preserving food
It’s why we’re taking a full-stack apach to both AI software and the physical platform it embodies at Mill
It’s why we can’t afford to apply the world’s best minds and nology to pumping out models destined for commoditization
We need to invest in talent and engineering that scales where meets the real world
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