Many businesses think of IT as nothing but an expense, often represented by losses on your budgeting reports. You might dump countless dollars into your IT only for it to eat it all up without providing any discernible return on investment. Here’s the truth about IT: when it’s managed properly, it can represent opportunity and investment rather than expense.
Many modern businesses rely on in-house server hardware, enjoying the perceived sense of security it provides. After all, you can see it, you can touch it, your data is literally at arm’s reach… what could happen?
Well, a brownout… and that’s just for starters.
While there are many benefits to an in-house infrastructure, there are also many shortcomings. For one, your business is among the most dangerous places to store your data.
You can’t wake up anymore without hearing something about AI, and in the business world, there’s almost a sense of peer pressure around it. Nowadays, you have to be using AI, or your business will be left behind… or at least, that’s the narrative.
While we are in no way discouraging you from adopting AI, we are saying that moving forward without a plan is likely to waste your money. For AI to work the way you want and need it to, you need to have done the homework and laid a foundation for success.
Artificial intelligence has reshaped the relationship that many people have with technology, and especially how we work and communicate. Despite this, there are plenty of challenges that the technology faces—especially if it wants to remain sustainable. Today, we want to look at the fuel that keeps these platforms running—the data center—and why it’s important to consider them in the context of the AI conversation.
Artificial intelligence, or AI, is practically now a household name, and it’s changing the way we think about work, communication, and even innovation. It takes a lot of power and infrastructure to fuel these systems, however, and they wouldn’t be possible without the data center. These structures are the powerhouses that enable AI, but what does a data center for AI look like?
