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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.

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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.

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AI and CES

While CES seems to be very quiet this year, announcements were schedule anyway. As expected there are a few that feature Artificial Intelligence, or more likely Machine Learning. Hat tip to Phil Lelyveld of the Entertained Technology Center for the reporting.

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If You Lost 40% of Your Market, Would You Survive?

A few years ago I was on a panel about the impact of AI on production at the annual HPA conference, and was surprised when a fellow panelist said that most of the media consumed by his teenage children was produced by their peers. As I’m not exposed to teenage behavior i had no idea.

Then yesterday my Chiropractor tells me that he watches mostly YouTube video instead of conventional TV. He is most definitely not a teenager! I’m also watching more YouTube than previously, and a lot of on-demand programming, but we rarely watch live TV.

So when I saw an article at Variety – User-Generated Content Represents 39% of Time Spent With Media: Study – with that worrying headline, it rang true. The report found that overall:

… user-created content accounts for 39% of weekly media hours consumed by Americans vs. 61% for traditional media.

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The Trouble with Training Sets for Machine Learning

Although the title is Defining what’s ethical in artificial intelligence needs input from Africans is accurate, the author is more generally raising the issues of poor quality training data sets for Machine Learning leads to bias in the results.

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More Flexible Deepfakes lead to Deeper Problems

My original plan for this post was to comment on how Disentanglement is the Next Deepfake Revolution using CGI to fill in the “blanks” where data for the target identity is missing, and to point to a DYI guide to Deepfakes. When the site became unavailable when I first wrote this post, I feared it had been censored, but it is now back.

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Reading is Fundamental!

The best apps are developed from some personal need. From the original Photoshop to Lumberjack System, to our latest – Reading is Fundamental – the apps are first developed for one user!

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Super Resolution isn’t enhancing, it’s creating what it thinks it should be!

As we gain better and better AI based visual enhancing tools, and they are amazing. Every published research paper builds on the work of its predecessors. Two Minutes Papers frequently compares a current paper being discussed, with the previous research. As you would expect there are often dramatic improvements happening in just months, as researchers leapfrog each others’ work.

As exciting as results like this on Super Resolution, it’s always worth remembering that the AI is creating what it thinks should be there, not revealing what should be there. That’s okay if the results are accurate enough, but there is always room for some error, such as with the interpolated glasses in the examples.

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Final Cut Pro 10.6’s XML Bundle Format Explained

With the release of Final Cut Pro 10.6 Apple introduced a new XML format. The original FCP XML was known as fcpxml and was a single text file, as is all XML. The new format – fcpxmld – is a package, not a single file known as a Bundle. A ‘Bundle’ in macOS appears as a single file in the Finder, but is a special type of folder that is read as a single file. Most apps are packages. The FCP Library is a Bundle.

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Becoming an Amplified Creative

Beyond specific NLE implementations, ML is making it’s way into almost every part of the productions process: storyboarding, production breakdowns, voice casting, digital sets, smart cameras, synthetic presenters, digital humans, voice cloning, music composition, voice overs, colorizing, image upscaling, frame rate upscaling, rotoscoping, background fill, intelligent reframing, Aging, de-aging and digital makeup, “created” images and action, Logging and organization, automatic editing (of sorts), temporization of production, analytics and personalization, storytelling, and directing.

That’s a lot, and it’s only the examples that I’ve kept records of! I’m sure there are many more I’ve missed here.

This is a very detailed article, ultimately running to 12 posts. If you would prefer a briefer version I wrote an overview at the Frame.io blog. This version includes a lot more examples and references.