Speaking at Entertainment & Artificial Intelligence Event in Montreal
I just got back from Montreal with my brain full of thoughts about AI. Sharing these with you and looking forward to your reflections. Please feel free to comment back!
Adobe and Frame.io: Now it makes sense!
When Frame.io introduced Camera to Cloud I thought it was brilliant, but the level of technology that was required to implement it, led me to think that it was only for the “high end” of production, an area out of my experience. While often lucrative, that’s a fairly finite market, and I doubted C2C would ever be something I’d use. The (mis)belief that they were addressing a fairly limited market led to a little surprise with the Adobe valuation.
Amplifying Individual Music Composition
Three new tools use Machine Learning tools to compose music. Two with a gamified interface for free form composition, and the other a browser based custom music track creation tool, reminiscent of SmartSound, but with computer instruments.
ToneStone describes itself as a :musical creativity platform for everyone” and appears to be browser based. I say “appears” because I didn’t sign up for a trial. In their introductory video they describe using ToneStone as being “game like”.
The other gamified app is Vinyl Dreams on iOS describes itself as:
An innovative app that enables you, beginner or expert, to create high caliber productions anywhere, with just your fingers, eyes, and ears.
While I also chose to not invest the time in Vinyl Dreams or ToneStone, I did spend quite a lot of time with browser-based Sondraw, which creates custom-composed tracks. You set Mood, Genre/Style, Tempo and the general instrumentation, then within about 10 seconds Soundraw presents 15 tracks to your specifications!
The results are at least as good as library music I’ve paid money for in the past, although there is a slight “electronic” feel to the results.
The results can have further customization of instrumentation and which part are playing, on a segment by segment basis. You can even upload a video to preview the music against for timing and instrumentation. And it’s all done by Machine Learning.
The amazing thing about Soundraw is that we are at the point where it’s easier to get 15 custom composed tracks than pull up a music library online!
AI and Copyright: How many opinions (and a little outrage) do I need?
I recently read the article Art Created By Artificial Intelligence Can’t Be Copyrighted, US Agency Rules, which is an examination of the ruling by the US Copyright Office refusing to grant copyright to “creations” by an AI/ML: in this case images created by a Machine. These were deliberate test cases to determine the possibility of copyright and under what circumstances, but the Copyright Office “requires human authorship” in order to be granted copyright.
The test cases are important because there’s already a lot of money involved in the sale of the Machines’ creations. The article quotes the sale of one AI-authored ‘painting’ that sold fro $432,000, as a example.
My first response was to approve the Copyright Office ruling: it resonated that copyright had to have human involvement.
But then I considered the arguments being presented for granting copyright to the owner of a ‘creative’ Machine. It was argued that the owner of other types of machine were the owners of the output of the machine, and that’s quite valid. It almost swayed me for a moment, then I realized the fundamental difference is that other types of machine are churning out identical copies of the required output. There is no pretense that there’s anything creative in the output.
Even without copyright protection, people sell the output of all types of machines. The plaintiffs argument that they need copyright to control the use of the material (and make the most money from it) is somewhat undermined by arguing that the copyright should be in the owners’ names instead of the Machine to get around previous rulings of copyright ownership cited in the article.
Which bought me to my moment of outrage: “Why does every item of creative output have to be monetized?” The purpose of copyright is to provide limited protection for a limited time. It’s not designed to give perpetual ownership to an idea (a lesson Disney refuse to learn). It’s good for a culture when ideas can be shared and remixed into something new. Copyright control that’s too tight stifles this remixing and the society is lessened by it.
Given that the Machine can produce infinite numbers of “unique” creative works would likely undermine any potential value because of over-supply.
The deeper question is whether or not every item of creative expression has to be monetized. There’s an underlying assumption in the reporting on the ruling that everything should be monetized and there’s a deficiency somewhere when it cannot be. And that was my moment of outrage.
Creating People and Places as we want them
Storytelling has always been about painting pictures – in people’s mind or on a screen somewhere. One of the significant challenges for visual storytellers is creating the people and places from the storyteller’s imagination, into a more tangible medium, like digital bits! Artificial Intelligence (AI) and Machine Learning (ML) are dramatically simplifying the way we create our visual illusions.
We’re Getting Closer to ‘Mind Reading’
While NVIDIA’s Canvas isn’t reading minds, research projects suggest we are moving toward being able to capture images from brain waves, or even hear internal voices. These research projects are a very long way from the premises of that first sentence, but advances happen so quickly it won’t be long before they move out of the lab into our creative process.
Creativity gets a new Canvas
One of my deep regrets is that I have no native sketching skills, nor have I taken the time to learn, so it’s always a challenge when I have a mental picture that I’d love to visualize. Enter NVIDIA Canvas, which turns “simple” brush strokes into realistic landscape images.
The Future of Locations and Talent is Unreal
If the primary focus of my career was on creating visual stories, the most important skill set I could acquire would be a full and deep understanding of Unreal Engine. I do not have that deep understanding, but recognize that Unreal is going to revolutionize narrative filmmaking.
Synthesizing Human ‘Performance’
I became aware of Synthesia.io when researching my articles on Amplified Creativity. More accurately when I was updating my article just before publication three months later, and I had to rewrite my “three years out” prediction for something like the Synthesia service, because it became a reality within that three month window! Yesterday I became aware of another synthetic avatar (AI) tool that has a very different business model, and it’s avatars appear to be a step ahead of Synthesia, although it may be unfair to compare.
Ideas have their time
In a former lifetime I headed the team that created The DV Companion for FCP, Intelligent Assistants for Boris Red, Graffiti and FX, Media 100 and Media 100 Cleaner. These were world leading “knowledge at the point of need” as we referred to it, or (as we later discovered) what the rest of the world called an Electronic Performance Support System.
What we created and released was a tiny fraction of my original vision for a “Next Generation Training Product: Final Cut Companion On-Line, or FCCOL. I’m pleased my naming abilities improved by the time we got to Lumberjack System, which was originally On Set Real Time Logging Tool, or OSRTL, which is quite the mouthful.
The most ambition part of the vision was that the FCCOL would track the skill level and learning of the student and serve up appropriate levels of detail in the training. We scaled back the design to what was able to be built in 1999. We definitely leveraged the best of Apple technology of the time, but tracking student skill level eluded us.
The reason I bring this up now is because I discovered WalkMe, which has largely delivered the portion of my vision we were unable to. Of course, 20 years evolution of technology, and particularly the innovation that is Machine Learning, have changed the landscape of possibilities. It was left to someone else to fulfill the vision as my own interests moved on from the training field many years ago.
It is satisfying to see that the goal of my original vision was the right one, even when someone else is responsible for delivering it.
Anyway, if anyone wants to lift ideas from my original thinking, here it is.