Generative AI. It’s been the hot topic for the past few weeks. From Jasper and Stability AI’s funding to DALL-E 2 opening access for all, and many more developments, visual content creation with the assistance of AI has taken center stage.
Because it’s visible and tangible and fun, many marketers and business leaders are starting with visual aspects of their marketing and sales to better grasp the concept of artificial intelligence and its role in their marketing and business strategies.
At MAICON 2022, our Chief Content Officer Mike Kaput sat down with Apoorva Dornadula (Viralspace), Stefan Britton (Shutterstock), and Kirk Iwanowksi (AnyClip) for a discussion on advancements and examples of vision AI at work.
AI can recognize and generate faces, analyze and produce videos, and edit and create images. The implications—positive and negative—are profound for marketers, brands and creative professionals.
As vision AI technology races forward in its capabilities, the only real limitations seem to be understanding what’s possible and having the imagination to bring smarter solutions to life.
But there is a dark side too, filled with bias and bad actors, and marketers must be ready for this new reality.
They discussed:
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Computer vision can help us extract data from ads to create a taxonomy of what is in the ads (copy, image, audio, video). This provides valuable insights into what’s working for us and our customers.
For example, Smartly/Viralspace is able to gather insights on colors that evoke certain emotions, and provide that data to their clients. It helps in strategy meetings, creative ideation, and more.
The challenge isn’t finding a use case, it’s narrowing down the specific use case for your company and team. Take our AI Score for Marketers to help you.
As marketers, we’re taught to repurpose, repurpose, repurpose! But what happens when your library of content and assets are outdated, not tagged, or done so by a teammate no longer at the company? AI can convert these files for you through optical character recognition, sentiment analysis, speech to text, facial recognition, and more. Visual content can (and should) become data, and we should use our content we invested so much time in creating.
We’ve seen it change dramatically just since this presentation at MAICON 2022. Whether it’s generating images based on descriptions, or even generating video based on images, this technology is advancing, and quickly. Now is the time to get access, get on waiting lists, and test out the technology. In the past two years, the quality of images has increased exponentially. There has been a massive movement in the encoders that develop the images.
As Stefan Britton says, “AI is stupid. It knows nothing. It has no imagination. And that’s where the human spark has to come in because generative AI can only create images based on images it’s already seen. So that inherently has some problems in it.”
Humans will still need to be there for the novel content, and for the creation and ideation of concepts.
Dornadula explained how her team helped a client use vision AI for SKU matching. The marketing team could tie this back to ads and images in ads to tie sales to products featured. It could also help the purchasing and operations team with inventory issues.
Kirk Iwanowski shared how his team ingested a client’s entire library so the client can query across their entire content library. Now this team can use the files, use the data and analytics, inform new content and creative decisions, investments, and more.
AI can slow down some jobs, but it can also create jobs. There are certain skills that are going to be developed now that don’t currently exist in the creative workforce. Being able to understand and manage software tools is key.
What would you add?
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