Deep learning has the power to improve all of our lives through applications in fields from medicine to transportation to entertainment to commerce. It lets software connect with the analog world around us and creates opportunities that are hard to imagine and even harder to realize. Text or images, sensors or robots—deploying intelligence is one of the biggest and most promising challenges of our time. We’re here to help you meet that challenge.
Our technology lets you put intelligence where you need it. Whether you run on cloud, desktop, mobile, or embedded—whether your priority is bandwidth, reliability, responsiveness, or security—our technology will help you meet your goals. Hand-coding deep learning algorithms for all of the CPUs, GPUs, and accelerators that your application demands requires expert skills in deep learning and parallel algorithms. Our toolkit eliminates these challenges, getting you up and running in minutes with a future-proof solution.
Promising new research emerges almost every day—but it takes real products to bring it to the rest of the world. Vertex.AI was founded by a team of developers with decades of experience building challenging applications across diverse platforms. With systems including computer vision, mobile apps, cloud infrastructure, and mesh networking under our belts we understand what it takes to build great software. Now we’re taking the power of the latest deep learning research and making it work with your codebase, toolchain, target platforms, and timeline.
We're working to bring the power of neural nets to every application, using new technology invented and built in-house, to make applications that weren't possible, possible. There's a large gap between the capabilities neural networks show in research and the practical challenges in actually getting them to run on the platforms where most applications run. Making these algorithms work in your app requires fast enough hardware paired with precisely tuned software compatible with your platform and language. Efficient plus compatible plus portable is a huge challenge...