The Deflationary Impact on Creative Services
Today, I want to show you how I used ChatGPT's multimodal features to quickly put together a voiceover script and make a video in less than an hour and a half. This method is how I usually think about making content or building generative applications on a large scale.
The Process
Setting the Scene: The starting point for the video was a mix of screenshots from our app and our overall messaging, positioning, and product features.
The Initial Steps: I began with a basic prompt, refined it for text-to-audio, and got it ready for video editing in Final Cut.
Gathering Content: I used a document that had all our key messages and positioning as a reference. I then added various screens from our app to give more context.
Creating the Script: With everything set up, I crafted a prompt for a voiceover script. A few tweaks here and there—like removing unnecessary parts and getting the length right—got the script ready for the next step.
Making the Voiceover: For the voice, I used 11labs, which is great for managing different voice tracks easily. This tool is a big part of how we update our audio for various sections.
Putting the Video Together: I recorded some simple demos with Loom for the video part. Then, in Final Cut, I combined these with the audio track, adding our usual opening and closing sections.
Finishing Up and Sharing: After I got the final video onto Vimeo, which is where we keep all our stuff, it was ready to be shared.
This quick run-through shows how you can use ChatGPT's multimodal features to make a simple product demo. By combining screenshots, text-to-audio, and video editing, I managed to create a decent video and a blog post in about 90 minutes. It's a straightforward way to create content fast.
Concluding Thought: The Deflationary Impact on Creative Services
The journey of creating a video in such a short time with ChatGPT's multimodal features goes beyond demonstrating efficiency. It stands as a clear example of the deflationary impact in the realm of creative services. Advancements in AI and technology have transformed tasks that once required hours and specialized skills into endeavors that are completed much quicker and often without extensive technical know-how. This evolution is reshaping the landscape of creative work by making it more accessible and altering the value and cost associated with these services.
Understanding the deflationary impact in this context involves recognizing the significant reductions in costs, as AI and software automation now handle tasks previously needing human labor, often at a much lower expense. This leads to decreased prices for certain creative services. Additionally, user-friendly technology boosts accessibility, enabling more people to create content or perform tasks that were once specialized, like editing a video or designing a website with minimal training.
Moreover, the increase in efficiency and productivity is undeniable. Technology has streamlined processes, cutting down the time for project completion from days to hours or even minutes. However, this shift brings a notable impact on employment, as machines and software begin to take over tasks traditionally done by humans, leading to changes in the job market and the emergence of new roles.
Yet, this rise in efficiency sparks a debate about the quality and creativity compared to what human professionals offer. While AI and automated tools can enhance productivity, some argue they might lack the nuanced understanding and originality of human creatives.
In sum, the deflationary impact on creative services is a testament to how technology is altering the economics and accessibility of creative work, affecting both the industry itself and its workforce. It's a compelling time for creators and businesses as we navigate this rapidly evolving digital landscape.
