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SKY ENGINE AI’s Software Solutions Fuel Developments in Computer Vision - Gartner Report

By SKY ENGINE AI   21 August 2024

3D Generative AI

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Synthetic Data Cloud

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Gartner

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AI

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Vision AI


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SKY ENGINE AI’s Software Solutions Fuel Developments in Computer Vision with 3D Generative AI - Gartner Report

SKY ENGINE AI’s Software Solutions Fuel Developments in Computer Vision - Gartner Report – Press Note

The increasing importance of computer vision solutions drives demand for high-quality training data for ML models. Gartner analyzes that topic in their latest Market Guide and mentions the SKY ENGINE AI Software-as-a-Service Synthetic Data Cloud as one of the sample providers of synthetic data for Vision AI.

SKY ENGINE AI is a fully managed platform as a 3D Generative AI Synthetic Data Cloud. It allows for the generation of completely annotated synthetic data for Vision AI development and provides advanced algorithms for domain adaptation.

Designed for professionals such as Data Scientists, ML Developers, and AI Engineers, SKY ENGINE AI is ideal for developing computer vision solutions across diverse sectors, from automotive to face analysis to medical diagnostics to defense. The Platform features a generative scene design, ground truth data generator, and sensor simulator, which contribute to closing the domain gap by providing synthetic data of unparalleled technical quality and reproducibility. Moreover, its latest feature – a catalog of 3D generative AI blueprints – increases the dataset diversity and improves mapping of abstract features required for training of accurate vision AI models.

In the recent Gartner report “Emerging Tech: Maximize the Impact of Generative AI In Computer Vision,” Alizeh Khare, 17 July 2024, SKY ENGINE AI was mentioned as one of the sample providers of synthetic data in the following insight: Synthetic Data Provides Data Diversity by Creating Scenarios and Edge Cases.

Bartek Włodarczyk, PhD, the CEO and founder of SKY ENGINE AI says about the inclusion in the Gartner report “We are humbled to be mentioned as one of the sample providers and products in the report on 3D Gen AI by Gartner. Our goal is to provide data scientists with tools to generate synthetic data tailored to the needs of their use cases. We are fully aware of the importance of physics-based sensor simulation and pixel-perfect ground truth as computer vision technology becomes increasingly prominent in areas such as diagnostic medical imaging or drone surveying in defense. There is no space for error in such cases and the most crucial warrant of computer vision reliability lies in the quality of training data. Only synthetic data guarantees appropriate and customizable parameters of a dataset, and at SKY ENGINE AI we are endeavoring to provide an easy-to-use and best-in-class tool for the generation of such data. We are constantly developing our software and we keep adding new features, such as Omnihuman – a functionality that enables generative production of fully customizable human-related datasets and much more.”

Full Gartner's Report can be found here: https://www.gartner.com/document/5593759

If you are interested in SKY ENGINE AI’s offer and features, leave us a note in our contact form and we will get back to you.

Disclaimer
Gartner, Emerging Tech: Maximize the Impact of Generative AI In Computer Vision, By Alizeh Khare, 17 July 2024.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Gartner® does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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