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Editshare - Enhancing EditShare’s flow media asset management with Automated AI
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Editshare - Enhancing EditShare’s flow media asset management with Automated AI

Features

Leverage secure, on-premise AI solutions

February 16, 2023
February 17, 2022
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2
min
Introduction
Don’t depend on Big Data to get big results

Carefully curated and sorted visual archives offer unassailable competitive advantages to businesses. But if archives are processed on the cloud or third-party servers, they run the risk of being exploited, lost, or violating privacy regulations.

Choose a solution that lets you keep your data where it belongs: with you. Our computer vision technology is delivered as an SDK (Software Development Kit) that works on-premise, in your own systems.

This means
- zero compromise in data ownership and security
- total control over your content
- lightweight models that can be deployed on ‘edge’ devices like laptops and satellites
- the ability to customize solutions in-house based on your business needs without sharing sensitive data


We don’t need access to your data in order to give you the best results. To know more about how Superhuman Vision ensures complete control and privacy for your business, check out our detailed article here.


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Solution
Benefits
Written by
Trisha Mandal
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Edited by
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Illustrated by
Xana Ramos

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Mobius Labs GmbH is receiving additional funding by the ProFIT program of the Investment Bank of Berlin. The goal of the ProFIT project “Superhuman Vision 2.0 for every application- no code, customizable, on- premise  AI solutions ” is to revolutionize the work with technical images. (f.e.) This project is co-financed by the European Fund for Regional Development (EFRE).

In the ProFIT project, we are exploring models that can recognize various objects and keywords in images and can also detect and segment these objects into specific pixel locations. Furthermore, we are investigating the application of ML algorithms on edge devices, including satellites, mobile phones, and tablets. Additionally, we will explore the combination of multiple modalities, such as audio embedded in videos and the language extracted from that audio.