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Amazon recently announced that it had deployed its one-millionth robot across its workforce since rolling out its first bot in 2012. The figure is astounding from a sheer numbers perspective, especially considering that were talking about just one company. The one million bot number is all the more striking, though, since it took Amazon merely about a dozen years to achieve. It took the company nearly 30 years to build its current workforce of 1.5 million humans. At this rate, Amazon could soon employ more bots than people. Other companies are likely to follow suit, and not just in factories. Robots will be increasingly deployed in a wide range of traditional blue-collar roles, including delivery, construction, and agriculture, as well as in white-collar spaces like retail and food services. This occupational versatility will not only stem from their physical designsjoints, gyroscopes, and motorsbut also from the two burgeoning fields of artificial intelligence that power their brains: Physical AI and Embodied AI. Heres what you need to understand about each and how they differ from the generative AI that powers chatbots like ChatGPT. [Photo: Amazon] What is Physical AI? Physical AI refers to artificial intelligence that understands the physical properties of the real world and how these properties interact. As artificial intelligence leader Nvidia explains it, Physical AI is also known as generative physical AI because it can analyze data about physical processes and generate insights or recommendations for actions that a person, government, or machine should take. In other words, Physical AI can reason about the physical world. This real-world reasoning ability has numerous applications. A Physical AI system receiving data from a rain sensor may be able to predict if a certain location will flood. It can make these predictions by reasoning about real-time weather data using its understanding of the physical properties of fluid dynamics, such as how water is absorbed or repelled by specific landscape features. Physical AI can also be used to build digital twins of environments and spaces, from an individual factory to an entire city. It can help determine the optimal floor placement for heavy manufacturing equipment, for example, by understanding the building’s physical characteristics, such as the weight capacity of each floor based on its material composition. Or it can improve urban planning by analyzing things like traffic flows, how trees impact heat retention on streets, and how building heights affect sunlight distribution in neighborhoods. [Photo: Amazon] What is Embodied AI? Embodied AI refers to artificial intelligence that lives inside (embodies) a physical vessel that can move around and physically interact with the real world. Embodied AI can inhabit various objects, including smart vacuum cleaners, humanoid robots, and self-driving cars. Like Physical AI, Embodied AI can reason about physics, as well as how one object affects another. However, since Embodied AI literally embodies a physical entity, such as a robot, it can also alter the real world around it, whether that be a robotic arm performing surgery, a humanoid bot working construction, or a self-driving truck transporting supplies from one location to another. Embodied AI has advanced capabilities due to the mobility of its physical body and, as Nvidia explains, additional sensors, which can include cameras or LiDAR, that enable it to perceive its surroundings. A real-time distinction It is worth noting that the terms “Physical AI” and “Embodied AI” are increasingly being used interchangeably to describe any AI that understands the physics and spatial relationships of the real world and uses that understanding to power the brains behind bots. However, most experts agree that Physical AI and Embodied AI are interrelated but distinct varieties of artificial intelligence. Henrik I. Christensen, an expert on robotics and AI and a professor of computer science at the University of California, San Diego, says that one distinguishing factor between the two is their real-time operational capabilities. “Physical AI denotes systems that [infer things] related to the physical world, such as friction, elasticity,” Christensen told me via email. This kind of system “may not operate in real time but has a detailed model of interaction in the physical world.” Embodied AI, on the other hand, “denotes systems that operate in the physical world [and also] interact with objects in the real world, [so] they must operate in real-time,” Christensen says. This real-time requirement is essential for robots working in the real world. If a robot doesn’t grab something as fast as it should, disaster can strike on the factory floor. He notes that Embodied AI systems often need to use simplified models to ensure they can “provide an answer fast enough.” Will robots take all the jobs? LLM artificial intelligence systems that power ChatGPT, Claude, Llama, Grok, and others have long been seen as a threat to white-collar jobs, since they can reason about information and generate answers based on that information, much like a human can. However, because LLMs lack both a physical presence and an understanding of how physics affects objects in the real world, they have generally been seen as less of a threat to blue-collar jobs, which typically involve physical labor and an understanding of how objecs interact in the real world. But Physical AI and Embodied AI systems change the blue-collar risk assessment. Physical AI systems now possess reasoning capabilities regarding physical interactions, and Embodied AI enables robots to apply that understanding in the real world. Yet, for now, at least, LLMs still pose a greater threat to white-collar jobs than Physical AI and Embodied AI do to blue-collar ones. This is because LLM technology is readily available and easily deployable across organizations at scale. While Physical AI systems could see nearly as speedy a rollout in the years ahead, Embodied AI systems face more hurdles due to the need to manufacture legions of robots capable of operating in real-world environments. However, as Amazons one millionth robot rollout demonstrates, companies are increasingly interested in integrating more bots into the workforce, whether thats in the factory or in the kitchen flipping burgers. As for why? Well, to take a line from my own novel, Beautiful Shining People, bots never accidentally drop or damage thingsnot to mention they never get sick, or need days off, or give away free burgers to their friends. In other words, Physical AI and Embodied AI-powered robots have the potential to save companies a significant amount on their biggest expense: labor. And they are sure to take advantage of it. The only question for me, then, is: When AI takes all our jobs, who will be left to buy the things these companies sell?
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E-Commerce
You dream of quitting a toxic job, pivoting to a new career, or starting your own business. But theres a financial reality to such a move: can you afford to earn less? In 2021, I quit a job as an executive at a tech company. I pivoted into content marketing and journalism, and, initially, I was earning about one-third of my previous salary. But I had spent months looking at our household budget, and was prepared to earn even less. When youre determined to make a change, youll look at your finances differently. You should calculate your freedom number and understand the changes you need to make in your budget. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/04\/workbetter-logo.png","headline":"Work Better","description":"Thoughts on the future of work, career pivots, and why work shouldn't suck, by Anna Burgess Yang. To learn more visit workbetter.media.","substackDomain":"https:\/\/www.workbetter.media","colorTheme":"blue","redirectUrl":""}} Keep in mind that your freedom number is not your final destination. Its a transitional change in your income to pursue the career you want. Why your freedom number matters Your freedom number is the bare minimum you need to cover your essentials: rent/mortgage, groceries, insurance, utilities, etc. Its not the same as what youre spending to support your current lifestyle. Calculating your freedom number forces you to think about what youre willing to give upeven temporarily. Lets say youre earning $100,000 today and think you need to earn $80,000. But once you go through the numbers and cut everything nonessential, you might find that the number is far below $80,000. Knowing that makes it easier to navigate a career change, because you know what you need to get by. The bare minimum is your freedom number. Closing the gap in your freedom number If you dont think youll earn enough to cover your monthly expenses, there are ways to close the gap between your income and your freedom number. You might build up some savings and draw from that account when you make your move. Or you could supplement your income with a side hustle. When I first changed careers, I took a new full-time job and freelanced on the side. The combination of my new salary and my freelance earnings helped me reach my freedom number. It meant working in the evenings and on weekends, but it was worth it to make the change. Keep in mind that a lower income might be temporary. Within eight months of starting a new career, I took a new job at a much higher salary. I just needed to get a bit of experience on my resume, and then many more doors opened for me. As you settle into your career change and earn more, you can add back the things you enjoyed about your lifestyle. The temporary squeeze is worth it to find a freedom number that makes a lot of career options possible. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/04\/workbetter-logo.png","headline":"Work Better","description":"Thoughts on the future of work, career pivots, and why work shouldn't suck, by Anna Burgess Yang. To learn more visit workbetter.media.","substackDomain":"https:\/\/www.workbetter.media","colorTheme":"blue","redirectUrl":""}}
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E-Commerce
On this week’s Most Innovative Companies podcast, Cloudflare COO Michelle Zatlyn talks with Fast Company staff writer David Salazar about hitting $1B in revenue and going global, as well as why defending businesses of all sizes online is more necessary than ever.
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E-Commerce
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