How Far Can AI Go?

Lensa - shelly palmer

If you haven’t already uploaded your 10-to-20 selfies to Lensa and let it turn you into a superhero, or a rock star, or an astronaut, you should give it a try. It’s fun, but it’s also instructive. You’ll learn about the type and quality of inputs generative AI needs in order to obtain satisfactory results, and you’ll experience the workflow and process of consumer-grade generative AI. But most importantly, when the model transforms you into a mystical creature in a cosmic setting, or an anime character, or a cyborg, you will find yourself asking one question: How far can this technology go?

A Quick AI Tool Check

Let’s say we wanted to create, produce, and distribute a video. Where might we use AI to assist us?

Scriptwriting: AI can be used to generate new storylines or suggest changes to existing ones, using natural language processing and machine learning algorithms.

Content creation: AI can be used to generate visual effects, such as background landscapes or special effects, or to create realistic 3D models of objects and characters.

Audio and video editing: AI can be used to automate tasks such as transcribing dialog, synchronizing audio and video, and identifying and removing background noise.

Sound mixing: AI can be used to help mix the final audio balancing dialog, sound effects, and music.

Audio processing: AI can be used to enhance the audio quality. It can also be used to help producers mimic the audio styles and sonic landscapes of existing masterworks. And it can be used to create new, never-heard-before sonic landscapes.

Language translation: AI can be used to translate content into different languages, using machine translation algorithms.

Quality control: AI can be used to automatically identify errors or inconsistencies in the production process, such as frame rates, dropout, lighting or sound issues.

Marketing and promotion: AI can be used to analyze viewer data and create personalized recommendations for shows, or to target ads to specific demographics.

SEO/SEM: AI can be used to generate key words and phrases and generally improve all aspects of search engine optimization and marketing.

Content recommendation: AI can be used to recommend content to viewers based on their preferences and viewing history, using techniques such as collaborative filtering and recommendation algorithms.

Audience analysis: AI can be used to analyze audience data and provide insights on viewer behavior, using techniques such as natural language processing and machine learning.

Automated content moderation: AI can be used to automatically flag inappropriate or offensive content, using techniques such as image and video analysis.

Virtual assistants: AI can be used for a clerical work such as resource and meeting scheduling as well as other productivity enhancements.

Note: This list is remarkably incomplete — in practice, there are already dozens of AI models at work for us — we just don’t interface with them directly.

What’s Next?

All of the areas mentioned above are the epicenters of nascent AI-assisted ecosystems. But at the moment, most of the available technology comes in the form of purpose-built, narrowly focused tools. For example: Adobe has a suite of AI tools you can access directly inside of Photoshop. Each tool does something specific (such as removing a background or changing the sky).

The roadmap is pretty obvious. Each purpose-built AI tool will improve at an exponential rate. Over time, we’ll start to see interfaces that allow us to layer and script various disparate AI tools. You can think of it as an AI model that is trained to understand the problem you are trying to solve, then sends data to other AI models and organizes the various outputs into results you can use. More simply stated, we can look forward to AI models that will harness the power of other AI models which will in turn harness the power of other AI models until we get to a point where AI-assisted productivity will be table stakes.

What happens then?

If you look back in 30-year blocks and think about what technology was available in 1990, 1960, 1930, 1900, 1870, and 1840, you’ll get a sense of how things may change. I don’t know any more about the future than anyone else, but I do know that today, you are experiencing the slowest rate of technological change you will ever experience for the rest of your life. So take a few moments to jump into the AI tools that are directly related to the work you are doing right now. Once you start to engage with AI, you’ll be amazed at where your imagination takes you.

Author’s note: This is not a sponsored post. I am the author of this article and it expresses my own opinions. I am not, nor is my company, receiving compensation for it. I am not a financial advisor. Nothing contained herein should be considered financial advice. If you are considering any type of investment you should conduct your own research and, if necessary, seek the advice of a licensed financial advisor.

About Shelly Palmer

Shelly Palmer is the Professor of Advanced Media in Residence at Syracuse University’s S.I. Newhouse School of Public Communications and CEO of The Palmer Group, a consulting practice that helps Fortune 500 companies with technology, media and marketing. Named LinkedIn’s “Top Voice in Technology,” he covers tech and business for Good Day New York, is a regular commentator on CNN and writes a popular daily business blog. He's a bestselling author, and the creator of the popular, free online course, Generative AI for Execs. Follow @shellypalmer or visit


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