Imagine you’re a developer, and you want to try out the latest AI model on your laptop. Not so long ago, you could just download it and get to work. But now, these models have grown so huge and complex that your trusty computer just can’t keep up. The world of AI has outgrown the machines most of us have on our desks, and suddenly, everyone has to rethink how they build and run these systems.
The numbers are staggering. Some of today’s AI models need hundreds of billions of parameters just to run, and they gobble up more memory than most computers could ever dream of. If you want to work with them, you can’t just fire up your PC or laptop anymore. Instead, you’re faced with a choice: move your work to the cloud, or start thinking about building your own mini data center.
For business leaders, this isn’t just a technical headache—it’s a budgeting problem. Do you keep paying for cloud computing every month, or do you bite the bullet and invest in expensive new hardware? The old days of running everything on a standard office computer are over.
For developers, this means your whole way of working is changing. You have to decide what you can still do on your own machine, what needs to be sent off to the cloud, and how to juggle the costs and delays that come with moving data back and forth. The old, smooth workflow is suddenly full of bumps.
If you’re working on sensitive projects—maybe something private or security-related—the cloud might not even be an option. Companies like Nvidia are racing to fill the gap with new, powerful machines, but nobody’s saying how much they’ll cost yet. So the big question is: when does it make sense to stop renting power from the cloud and start building your own?
