MongoDB Inc.

07/01/2024 | News release | Distributed by Public on 07/01/2024 08:07

AI Apps: What the World Sees vs. What Developers See

Imagine you're in the market for a new home in, say, Atlanta. And you're on vacation in a different city. You see an amazing-looking house, whose design you love. You open up your favorite real estate app, snap a picture of this house, and type: "Find me a home that looks like this in Atlanta, in my price range, and within my budget, that's also next to a park." Seconds later, you're served a list of homes that not only resemble this one, but match all your other specifications.

This is what the world-specifically, consumers-expects when it comes to AI-powered applications.

But when developers see the possibilities for these hyper-personalized, interactive, and conversational apps, they also see what goes into building them.

A video showing the behind-the-scenes of an AI-powered real estate app.

To make these advanced apps a reality, developers need to be able to unify operational and vector data. They also want to be able to use their preferred tools and popular LLMs.

Most of all, developers are looking for a platform that makes their jobs easier-while, at the same time, providing a development experience that's both seamless and secure.

And it's critical that developers have all of this.

Because as in previous tech revolutions (the software revolution, the birth of the World Wide Web, the dawn of the smartphone, etc.), it's developers who are leading the new AI revolution.

And it's developers who will use different kinds of data to push the boundaries of what's possible.

Take for instance audio data. Imagine a diagnostic application that records real-time sounds and turns those sounds into vectors. Then an AI model checks those sounds against a database of known issues: all of which pinpoints the specific sound that signals a potential problem that can now be fixed. Until recently, this kind of innovation wasn't possible.

A video showing an AI-powered advanced diagnostics use case.

This is also just the tip of the iceberg when it comes to the types of new applications that developers will build in this new era of AI. Especially when given a platform that not only makes working with operational and vector data easier, but provides an experience that developers actually love.

To learn more about how developers are shaping the AI revolution, and how we at MongoDB not only celebrate them, but support them, visit www.mongodb.com/LoveYourDevelopers.

There you can explore other AI use cases, see data requirements for building these more intelligent applications, discover developers who are innovating in this space, and get started with MongoDB Atlas for free.