14 YOUR TAKE Machine Learning
e are all aware of the pace of change within our industry. Faced with rising content volumes and the need to
1. Start by talking to people in the organisation for whom metadata (or the lack of it) is their biggest challenge. This could be the VFX supervisor at a post house or a director of operations at a broadcaster or an archivist. It is rarely the technologists. Ensure the people with the greatest need for metadata get hands-on experience using the technology. We sit with these users to understand their current processes to help them get the best out of the machine learning toolset. We find diehard sceptics often become our biggest champions when they see a practical use for machine learning. 2. Think broadly about how machine learning can be adopted and involve different functional groups.
MATT EATON Managing director, EMEA for GrayMeta, on how machine learning can help streamline your business
reduce costs, organisations cannot afford to be complacent about the way their content is managed and distributed. The attraction of AI (more accurately, machine learning) has been a major focus for the industry over the past few years and it will be no different at the 2020 NAB Show. The term, AI, seems to be tagged to almost every stand at NAB these days, however, the hype is distracting us away from an important fact: progressive content owners are already saving money and managing more content using machine learning and the data it generates. We should know. GrayMeta is a machine learning-driven metadata company that enables operational efficiency and monetisation of assets. The faster organisations adopt machine learning to increase operational efficiency and to use their content in new ways, the stronger their competitive advantage and future business becomes. So what’s stopping faster adoption across the industry? According to a Harvard Business Review article, “only
8% of firms engage in core practices that support widespread adoption” of AI*. The article points to challenges around rewiring the business and changing culture that slows AI adoption. Adopting AI is more than a technology challenge and the article recommends engaging cross- functional teams to look at its deployment from different perspectives. Perhaps most importantly, it recommends using a test-and-learn approach where end users are engaged in the projects. Here at GrayMeta, we have seen this in practice in the media and entertainment industry and so we developed a Metadata Value Accelerator (MDVA) approach. GrayMeta has helped accelerate the adoption of machine learning through our MDVA across a huge range of different content organisations, from studios to post-production houses, to traditional broadcasters and branded content distributors. Here are some of the lessons we have incorporated into this approach:
For instance, by looking at the entire content supply chain and interviewing a broad group of stakeholders, we helped a public broadcaster in Europe create a roadmap for machine learning involving news, sports, media operations, archive and audience
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