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The Future Is Multimodal: Why Brands Shouldn’t Be Scared to Explore the Potential of AI

Ever since ChatGPT was launched at the end of 2022, there’s been growing interest from the media, the public and the commercial sector in the rapid evolution of Artificial Intelligence (AI) and the large language models (LLM) that underpin it. 

For those old enough to remember the introduction of predictive text on their mobile phones, the latest breed of AI chatbots can seem mind-blowing and a bit overwhelming. In some ways, however, they are simply an evolution of predictive text, but on a much, much bigger scale. ChatGPT uses 40 gigabytes of training text and more than 1.5 billion parameters, so it can perform what look like amazing feats. Rather than simply guessing the next word you want to type, it can write a short story based on a few instructions, or draft a business plan, or generate computer code, or create an image to your specifications, and so on.

As a result of these enhanced abilities, digital advertisers are cautious about exploring the current and future potential of AI in fear that they’ll end up putting themselves out of a job. However, it’s not so much a matter of AI replacing jobs within the industry, but a matter of understanding how to utilize AI to improve jobs and manage it effectively. The capabilities of AI are expanding rapidly and in some very interesting ways that are worth paying attention to.

Multimodal thinking with Artificial Intelligence (AI)

For example, until recently, AI chatbots and LLM have predominantly only been able to process and interpret one mode of data at a time – usually text. This creates some limitations. 

By comparison, human brains do not handle single data types in isolation from each other. Unlike most traditional AI systems, we have multimodal capabilities: we understand the meaning of text, videos, audio, and images together in context. For instance, consider the way that internet memes often work, where the text and an image that seem innocuous when considered apart mean something entirely different when paired together. 

While AI has traditionally struggled with this sort of comprehension, the latest developments have seen the technology move towards a more multimodal system of understanding that opens up a whole new range of possibilities for digital advertising in terms of the deployment of AI.

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Consumers engage with hundreds of digital channels in a given week, so there is no guarantee they will interact with an ad even if it is the most compelling creative. Managing the vast number of digital channels and millions of potential consumers is too big a task for even the most competent marketers. This is where AI comes in. The ability to hyper-segment audiences means AI creates the data needed to determine the efficacy of campaigns and ensure that the right ads are getting in front of the right audiences. So, how can brands best leverage the incredible potential of generative AI?

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The search for AI’s sweet spot

There are a number of areas where AI can benefit brands, such as analyzing consumer data to provide contextual recommendations to maximize ad efficacy.  Whether that’s targeting a consumer with specific products they had previously shown an interest in, or contextual personalization of tailored messages based on preferred device or channel. AI can ensure the right message is put in front of the right consumer at the right time.

The use of AI for better personalization can also drive more predictive product recommendations based on browsing habits and observed preferences. This way, brands can be more specific with their recommendations to consumers based on purchase history or interests which not only creates a better user experience, but also promotes retention efforts.

AI can also help  to generate automatic product descriptions, assisting customers with queries about product availability, order tracking and better personalized recommendations. We’re also seeing some interesting sector specific fine-tuned versions of ChatGPT and other LLMs in domains like HR, legal services and medical advice.

However, marketers should be careful how they leverage AI in their content creation efforts as Google’s guidelines already regard some forms of automated content as a no-no. Its guidelines for webmasters say that they should avoid: “Automatically generated content intended to manipulate search rankings”,  and that “In cases where it’s intended to manipulate search rankings and not help users, Google may take actions on such content.”

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So, when it comes to content that requires thought leadership or creativity, AI might create content that falls short. Take, for example, product reviews: you can easily tell the difference between low quality recycled content compared to in-depth reviews. While automation may have a place in content creation, especially on large websites that produce hundreds of pages, it depends on the type of content and the purpose it is intended to serve. It’s about deciding when you should rely on AI and when you need that human input. 

While the debates around the legality and ethics of multimodal generative AI within digital advertising will continue to rage, in some ways, those conversations will be irrelevant to the market and societal impact of the technology. Change is happening quickly. It’s time to start thinking about the roles that AI could play in your organization.

[To share your insights with us, please write to sghosh@martechseries.com]

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