GUTERSLOH, Germany—Arvato Systems’ Vidispine has ported a wide range of its products to the Google Cloud Platform, the company said today.

Among the ported Vidispine products are VidiCore, a media management backend, and VidiEditor, a browser-based production solution. Both now run natively on the Google Cloud Platform. 

The products can now be used directly via the Google Cloud Platform’s web-based console and can be used to build the entire digital media supply chain natively in the cloud.

Existing users of Vidispine products now have seamless access to a   wider range of Google Cloud services as an increasing number of broadcast organizations look to build out their cloud workflows. For example, Vidispine users can now build out their media archive with Google Storage.

“Arvato Systems is already a long-standing Google Cloud Partner with deep experience in cloud projects, and we are delighted to be supporting the industry-wide move towards native cloud-based workflows with our Media Supply Chain products and expertise,” said Stefan Eckardt, head of platform success within the Vidispine team at Arvato Systems.

More information is available on the company’s website. 

AI: WHAT'S WHAT?

No other topic has dominated industry conversation in recent years like AI. But what exactly does it mean when we speak of AI? 

Artificial intelligence is the generic term for a machine simulation of human cognitive abilities. Machine Learning, in turn, describes a series of mathematical methods that can identify certain patterns in data from learned examples. Deep Learning is a subset of machine learning and uses artificial neural networks that enable the system to learn autonomously. 

DEEP LEARNING IN MEDIA

Deep Learning enables the processing of amounts of data that is not practical to process manually. The strength of deep learning lies in capturing patterns and structures of different data types, as well as in tagging and enriching data. With its daily flow of current facts, figures and data, the media sector is ideal for the application of deep learning. 

Although many media professionals are skeptical about AI, recent studies find they would be comfortable with AI-generated news like traffic or weather reports. But without the right strategy, more automation can quickly become a nightmare.

AI IN THE MEDIA SUPPLY CHAIN

How do we integrate our existing systems with the rapidly growing field of AI providers with pre-trained models, frameworks and environments ready to be used as services?

First, we need to look at where we might apply them. There are opportunities throughout the media supply chain. A few examples include: 

• Ingest—Automatic QC, compliance, deep fake recognition, copyright monitoring  
• Production—Tagging, entity recognition, topic clustering and (soon) rough cuts, automatic highlight cuts, robot journalism 
• Planning—Automatic program planning, based on licensing or marketing patterns 
• Marketing—Rating prediction, imitation of buying patterns 
• Distribution—Automated playout or packaging

A GOOD STRATEGY

Deep Learning helps us to gain insights into media objects at a level that wasn’t practical without automation and helping us toward our vision of wanting to know "everything about every frame."

To support to the multitude of services available and bridge the data and organizational silos that segregate both content and business intelligence, we implement an “AI-specific” intelligence layer that manages all communication, but also adds value through:

• Normalization—Bringing results into a unified format 
• Cross-media analysis—Video, stills, audio, text 
• Multicloud—Connect many different providers 
• Training—Especially in the field of computer vision 
• Knowledge graph—Build contextual data models from different data silos and query them in real time with dynamic requests  

Supporting a "best-of-breed" approach, users can choose the combination of services that best fit their requirements. This is realized through the normalization of different result schemes and making them available in a uniform metadata model. In this way, a uniform experience is achieved without neglecting the special knowledge or features of the individual services.

Applying a uniform metadata also has further advantages. Recognition concepts analyzed by different services can be merged, compared and interchanged. We can also combine services, for example, a speech-to-text transcript from one operation can be sent through Natural Language Processing in a “Cascade” operation.

A standardized metadata set and version tracking enable us to reproduce individual results ourselves and also determine where the data actually comes from and what predicted confidence was recognized. This enables users to rapidly optimize—for example changing threshold values—with results displayed immediately without having to re-analyze all media.

Organizations using deep learning need to train the algorithms with the data that is appropriate to their needs, and continuously train as those needs evolve—especially important in dynamic environments such as news where topics/people/objects of interest constantly change. Creating labeled training data is the “tagging” of tomorrow but being not the primary task in a creative process, the effort for this should be minimized. Since the training data is media objects, why not do this directly in the MAM with easy tools for media managers or journalists, integrated into daily tasks.

HOW DOES AI ENTER INTO PRODUCTION?

"AI" is an interdisciplinary team sport—from idea to validation by means of a prototype, up to the transfer into production, many different roles are required, including:  

• Business analyst—The domain expert  
• Data engineer—Provides data sources in sufficient quantity and quality 
• Data scientist—Implements and verifies the algorithms

The 80/20 rule applies here with practical experience showing that data engineering often takes up the majority of the work, whereas implementation accounts for a smaller part.

With roles defined, it is recommended to take a standardized “go live” process as follows:

• AI Roadmap—Identify & prioritize relevant use cases  
• AI Lab—From idea to a verified prototype within a few days 
• AI Factory—Develop operational AI service fully integrated to the production environment 
• AI Operation—A stable and permanent operation and ongoing improvement 

As a global leader in the world of IT, AI has been an important topic within Vidispine and the Arvato Systems group as a whole. We have fostered professional and creative exchange in the Arvato Systems AI Competence Cluster—a network of interdisciplinary colleagues aiming at transferring knowledge and driving innovation. To this end, many interesting examples from other businesses are coming to the forefront, such as interactive fashion recognition, extraction of manuscript insights, anomaly detection of infrastructure, data journalism (e.g. through a “crime map”), to name a few. It is clear that in the future, AI will simply be a part of every IT toolbox.

Ralf Jansen is software architect and product manager, Vidispine, an Arvato Systems brand

GÜTERSLOH, Germany—Arvato Systems has announced its plan to combine its media & entertainment product portfolio with the Vidispine businesses under a relaunched Vidispine brand.

Arvato acquired Vidispine, a media supply chain company, in 2017 as part of a strategy to strengthen the link between the two companies’ complimentary solutions and expand into new markets.

This new Vidispine brand is meant to be a “content ecosystem” for Arvato’s product portfolio and professional services with a community of partner vendors, consultants and service providers and developers, according to the announcement.

The restructured portfolio includes media asset management, content planning & rights management, ad tech and the cross-industry content platform, VidiNet.

“In order to better support our customers, we feel the time is now right to combine these two leading portfolios under the Vidispine brand,” said Ralf Schürmann, CEO or Arvato systems. “Streamlining our portfolio and creating the framework for the content ecosystem enables us to better help companies working with media to focus on their core business, by providing easy access to technology that supports their business needs. The Vidispine platform enables customers to get the maximum value from their assets, rights, media inventory and market.”

For more information, visit www.vidispine.com. 

GÜTERSLOH, Germany—Arvato Systems and Vidispine have announced that they will not be attending IBC 2020 in Amsterdam, which is currently scheduled for Sept. 11-15.

In the announcement, there is no specific mention of coronavirus as the reason for withdrawal, although the pandemic was likely a key factor in the decision. COVID-19 has already caused the cancellation of the physical 2020 NAB Show and the postponement of other conferences.

“As a major milestone in our event calendar, this has been a difficult decision to make,” said Ralf Schürmann, CEO of Arvato Systems S4M GmbH. “Our focus is now on ensuring that our customers can maintain business continuity during these challenging times. And of course, we are considering how we can keep them fully informed and supported with the latest solutions and innovations from Arvato Systems and Vidispine.”

As a substitute for not attending IBC, Arvato Systems has announced that it is hosting online events and is continuously looking to expand its program of virtual user group meetings, as well as other ways of staying connected with customers and partners, the company says.

One such event will be an online technology summit, “vortechConnect.by/Vidispine,” set to take place on May 27. For more information on the summit, visit www.vortech.by/connect.  

GÜTERSLOH, GERMANY—Arvato Systems Group earlier this month announced the acquisition of 100 percent of the shares of Vidispine AB to strengthen its product portfolio and collaborate on ways to take advantage of explosive growth in video content and cloud-based solutions to manage media.

Vidispine, founded in 2009 in Stockholm, has concentrated its efforts on developing and selling digital content management solutions, especially those for video. Customers include companies from the media sector as well as other industries. Vidispine CEO Erik Åhlin and CTO Isak Jonsson will continue in their roles.

The company’s product portfolio consists of various components built upon the Vidispine Server content management platform. They include:

· VidiXplore, a software-as-a-service solution for content management across a variety of locations;

· Vidinet, a platform-as-a-service cloud solution for enterprise media workflows.

“We are delighted that the existing partnership with Arvato Systems will enable an even more intensive integration of our solutions and a joint market launch," said Åhlin.

Matthias Moeller, CEO of Arvato Systems Group, said the company’s customers will “benefit significantly” from the integration of products, technology and expertise of both companies.

More information is available on the Arvato website.