Forrester selected Deci as one of the most important computer vision platforms within the edge accelerators segment that can optimize CV models in production
Computer Vision Going Mainstream
Computer vision (CV), a field of artificial intelligence, is rapidly changing the way businesses operate. By automatically processing, analyzing, and extracting information from digital images, video files, or any visual input, CV can enable organizations to improve efficiency, reduce costs, and meet new business trends and customer demands.
From hype to reality, the rapid advancements in technologies that enable CV have moved it into mainstream commercialization. With computing power, big data, and open-source deep learning frameworks becoming more accessible to businesses of all sizes, the use of CV is no longer limited to tech giants, startups, and innovation teams.
The Growing Market of CV Platforms
The computer vision market size is predicted to reach $19.1 billion by 2027, with a growing number of applications that include cashless checkout, sports analytics, automated visual inspection, and video surveillance. But for businesses to take advantage of the benefits that CV can provide, many factors come into play and functionalities to consider. One of which is acceleration at the edge.
According to Forrester, the segment of edge accelerators “specializes on the last mile of vision model deployment, optimizing the vision model—usually to minimize its processing, energy, and heat profile—for the target hardware that it will be deployed on.” This is crucial because CV models in production need to be fast and accurate. Otherwise, businesses suffer from large compute costs, inefficient use of resources, and poor performance.
Unlocking New Efficiencies for CV Models at the Edge, Cloud, or Mobile
Weighing four criteria, namely, revenue from CV, number of enterprise customers, year-over-year growth rate, and number of employees focused on CV, Forrester selected Deci as one of the most important CV vendors within the edge accelerators segment. To see a landscape overview of 43 CV providers, download the Forrester Report on New Tech: Computer Vision Platforms, Q3 2021.
Deci’s deep learning acceleration platform automatically gears up neural networks to become top-performing production-grade solutions on any hardware, at scale. Recognized as a Tech Innovator for Edge AI by Gartner last year, the platform is powered by AutoNAC technology (Automated Neural Architecture Construction), enabling CV practitioners to:
- Accelerate inference throughput/latency by 3X-15X while maintaining accuracy on any hardware—edge or cloud
- Shorten development cycle from months to weeks with automated tools
- Maximize hardware use and cut compute costs by up to 80%
The same AutoNAC technology recently discovered DeciNets, a family of image classification models with notable accuracy-latency tradeoff that outperforms popular open-source neural nets including EfficientNets and MobileNets. Learn more about DeciNets here.
With Deci, enterprises can produce the best architecture that achieves the optimization goal of CV models for their specific inference hardware of choice.
Way Forward
Computer vision opens a host of valuable use cases and advantages for businesses. Providing new ways to unlock intelligence about people, products, assets, and documents, it can drive outcomes in productivity, automation, and innovation at scale.
At Deci, we aim to make deep learning optimization accessible and scalable so that more organizations can successfully deploy CV at the edge with outstanding performance. We are proud to be serving Hewlett Packard Enterprise, Intel, and more in pushing the boundaries of deep learning and computer vision. Get started.
