Advances In Imaging Technologies Provide Exciting Possibilities, But Can Computation Keep Up?

One of the most exciting frontiers in technology in recent years has been advanced imaging in diverse fields from medicine to media and automotive to astronomy. This comes from the marriage of new imaging hardware and rapidly advancing computing technologies that allow for the processing of more and more complex and intensive data, which in turn allows for new and exciting applications.

In the medical field, VentriPoint Diagnostics VPT uses artificial intelligence (AI)-powered imaging technologies to create hyper-detailed 3D models of the human heart. 

With the recent launch of the James Webb Space Telescope, striking images of the universe including what may be the earliest galaxies ever observed have been collected. The telescope is not a point-and-shoot camera, and mountains of data must be processed to stitch together the images that are released. These images are only possible because of advances in computation technology.

One of the most popular technologies that have driven the growth of advanced imaging is light detection and ranging (LIDAR). The technology allows for extremely detailed mapping of things be it the ocean floor or a factory floor. Combining LIDAR with images to create 3D models of complex environments is fast becoming the new normal for CGI in Entertainment and for so-called digital twinning. 

LIDAR’s popularity has exploded. The market was valued at $1.8 billion in 2021 and is expected to grow to $4.71 billion by the end of the decade.

Automakers are adopting LIDAR into their systems to help keep drivers safe. Microvision Inc. MVIS has developed LIDAR systems that may help manufacturers finally bring autonomous driving to market. The automotive LIDAR market is expected to grow at an impressive 23% compound annual growth rate from 2022 to 2030.

Much of this technology requires the use of what’s known as high-performance computing (HPC). The incredible amounts of data required by these imaging systems often require access to specialized GPU computing resources. Resources that can be difficult to source cost-effectively when your resource pool is constrained to in-house resources or those of a single centralized cloud provider.

Distributed Computing may provide the solution. For example, Cudo Compute’s distributed cloud-computing platform provides its users with the freedom to choose from the available resources across multiple data center providers around the globe. By adding Cudo Compute cloud to their existing centralized options, customers are expanding their resource pool for high-performance systems and overcoming the limitations in choice inherent in a purely centralized cloud operating model. 

Critically, the service is completely scalable, allowing users to reserve the exact amount of power required for the task. By tapping into the available capacity for those who have the most need of it, Cudo Compute is creating a more equitable and therefore more competitively priced cloud, helping companies cost-effectively access more high-powered computing.

The company’s product has the potential to revolutionize the space because high-performance computing from traditional sources is often cost-prohibitive, or significantly eats into bottom lines. The ability to tailor the exact resources needed, in the perfect location and on-demand at any time, will greatly increase the accessibility of advanced imaging in all markets.

If you are interested in learning more, check out https://www.cudocompute.com/.

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Featured photo by Scott Blake on Unsplash