The rate of change in all areas AI related can be overwhelming. In fact the closer you follow it, the more overwhelming it becomes! Technologies that didn’t exist a year ago, are iterating so quickly it’s hard to keep up.
Here’s the good news. You don’t have to keep up, at least not just yet. Take a deep breath, relax and keep an open, and curious, mind. Just don’t be complacent.
In reading how Generative AI, particularly ChatGPT and other Large Language Models, are being used in creative workflows and corporate support setting, it’s become very clear that GPT* devalues experience.
For my entire production life, I’ve heard the trope that you can have any two of “Fast, Good or Cheap,” and it has been true that entire time. Except that today’s release of Lumberjack Builder version four completely breaks the paradigm. For the first time you can have Fast, Great (accurate) transcripts for free, completely breaking the long held “truism.”
Anyone who’;s been in the production industries for any length of time has already navigated many technology changes: from analog to digital, SD to HD, SDR to HDR and so on. Avid Media Composer was first out the digital Non-Linear Editing gate, and pretty much every other interface was inspired by the design decisions made there, until Final Cut Pro X rethought some of those assumptions.
Now there is a whole new generation of editing tools that take very different approaches to video storytelling: from RunwayML, through Builder NLE, Reduct, Synthesis.io, to whatever Adobe’s Project Blink evolves into, that take quite different approaches to solving the problem of organizing media into compelling stories.
It’s no secret that I started to learn to sing back in 2014 because I had been very bad a Karaoke. Eight and a bit years later I’m “competent” as a singer. What’s mildly annoying about it that, in far less time, researchers have taught AI entities to sing, and even have them accepted as students in a musical academy.
A deepfake allows us to animate any face and have it say whatever we want that face to say. Useful in resurrecting long dead actors (or recently dead to finish a movie), but incredibly dangerous when it – inevitably – it moves into the political arena. Exonet describes the problem in great detail in this video. From 2017 when you needed a lot of money and a lot of source material to base the deepfake on, to 2022 where only 20 seconds of video are required to make a believable deepfake.
While video dominates most communication and entertainment, it seems like Artificial Intelligence thrives on text. There’s a lot of new and quite diverse tools for using text prompts for image generation, 3D model creation, Human avatar movement, Animation and editing, all driven with text prompts. While text prompts are the current interface, they are not the end game. After all we already have, in various stages of development and availability.
With examples like James Earl Jones “signing over rights to” his Darth Vader voice to an artificial intelligence startup, and Bruce Willis selling rights to his “image/personea” to a Deepfake company so his digital twin can continue to perform (and earn income for his family), it seems there is a career for your digital likeness long after a normal acting career would be over.
In the Amplified Actors article last September, I spoke of some experiments from 2018 and later at the BBC and NHK with synthetic newsreaders. Those “experiments” are now productized and available from Virtual Human startup Hour One, with their text driven AI anchors and newsrooms.
If I were staring my career now, I’d be focusing on Artificial Intelligence and Unreal Engine. One for making me more creative, and one opening a whole storytelling universe “on my desktop.” Given that I focused on post production because it had air conditioning, being able to control my “shooting universe” in air conditioning is definitely appealing. Unreal Engine has become a standard cinematic storytelling tool, and now with Netflix’s Validation Framework for it, it had de facto approval. Netflix have used Unreal Engine on 1899 and Super Giant Robot Brothers among other.
A Validation Framework not only ensures that all settings are correct and included files included, but also includes a support system to guide users through correcting any errors. And because I can, I’ve included a couple of Unreal Engine Cinematic examples.
Read more: Netflix’s Validation Framework for Unreal Engine Cements Unreal in the Cinematic UniverseNetflix has approved Unreal Engine on more than the productions noted above, and each iteration has been a learning experience, but one where each production has been “starting over.” With so many settings and permutations it’s easy to get the deliverables wrong. Enter Netflix’s Validation Framework for Unreal Engine, which is a plug-in for the app.
You can read the specific benefits from the framework in their blog entry.
Take a look at a representative sampling of the cinematic potential.
A “fan fiction” Matrix experience rendered in Unreal Engine. These examples render in real time on modest hardware like X-Box and Playstation, which is why its very popular for revisualization. This particular example shows the (current) limitations on Metahumans. They are very driven by the performance capture.
It’s an extended example which shows some of the cinematic possibilities of Unreal Engine. Like every creative endeavor, the level of finish and realism is driven by the skill of the creatives.
There’s an obvious attempt at a Metahuman Neo in the Matrix Awakens experience above, it’s harder to recreate a person than create a completely fictional character. Here’s an example of Hermione Granger Made Using Unreal Engine 5.
If you want to see more of what Unreal Engine is doing in the cinematic space, search Unreal Engine Demo on YouTube and you’ll find dozens of examples.