The present and future of post production business and technology | Philip Hodgetts

Sep/16

5

LWPG with Karl Soule

Karl Soule has been with Adobe for over 10 years, focused on the Pro Video and Broadcast market. Karl traveled worldwide as an Adobe Video Evangelist, inspiring video professionals on five continents. For the last 5 years, Karl has been living in Singapore and working in Asia, helping to grow the broadcast business and drive awareness of the video tools for that growing market.Karl Key 1Currently based in Los Angeles, Karl is supporting the Hollywood and Broadcast markets for the US West Coast.

(more…)

Terry Curren pointed me to this example where IBM Watson (one of the Smart APIs I referred to a couple of weeks back) was tasked with determining whether or not an Artificial Intelligence could “cut” a movie trailer. This is the result, with a very interesting insight into how they did it at the end.

IBM Watson pulled the selects based on action and emotion, but an editor created the trailer from the selects. Still, being able to locate the highlights and determine emotion is a big step forward.

 

The extensive article by Steven Levy – The iBrain is Here – is a fascinating read on how Apple are using Machine Learning, neural networks and Artificial Intelligences across product lines. It’s well worth the time to read through, but this quote from Phil Schiller stood out:

“We use these techniques to do the things we have always wanted to do, better than we’ve been able to do,” says Schiller. “And on new things we haven’t be able to do. It’s a technique that will ultimately be a very Apple way of doing things as it evolves inside Apple and in the ways we make products.”

The ways this could all be aligned with editing? Speech-to-text; keyword extraction (just like Magic Keywords in Lumberjack System); sentiment extraction; image recognition; facial detection and recognition; speech controlled editing (if anyone really wants that), and the list goes on.

I’d like to believe the Pro Apps Team are working on this.

UPDATE: Ruslan Salakhutdinov is Apple’s first Director of AI.

Aug/16

26

AI: Now it’s ‘making movies’

Buried in an article called The iBrain is Here about Apple’s use of Artificial Intelligence across a wide range of products and purposes was this gem:

Machine learning…. It even knows what good filmmaking is, enabling Apple to quickly compile your snapshots and videos into a mini-movie at a touch of a button

At one level this is certainly true, and likely. After all, Greg and I spent a summer analyzing how I made documentary-style edits. It was a fascinating experience for me, analyzing why “that” was the right place to start b-roll over an interview.

I would then have to turn that analysis into a rule of thumb that Greg could program. This was the basis of (the now gone) First Cuts app. That work will resurface at some time. It’s too valuable not to.

Aug/16

23

A little FCP X Project

Mostly I edit Lunch with Philip and Greg, product videos, or the occasional The semiSerious Foodies video. This last week I put together a demo piece for a friend, that was much more fun/creative.

It’s a competition piece, so if you’d all like to go to http://indi.com/7fqks and vote for Marlon Braccia, we’d appreciate it.

Edited in FCP X I used significant amounts of speed change, chroma key, crop and blur on the background. Those in LA can see it in person, and learn how it was done in detail at the August 24 meeting of LACPUG.

Aug/16

22

More AI: Hedge Fund AI Outperformed its Creator

Bloomberg reported yesterday about a Hedge Fund ‘Robot’ that “outsmarted” its human “master”. The quotation marks are all mine because it’s self learning, so it doesn’t really have a master, but rather someone that created it.

Still, the performance in the quoted instance is quite impressive. It’s currently in charge of about $35 million in investment.

Aug/16

22

Editing Audio in FCP X

When I discovered I could do in two keystrokes what took 9 mouse clicks and keystrokes in Soundtrack Pro, I never looked back and now edit all my audio only projects in FCP X.

I got together with Marcelo Lewin of DigitalMedia Pros and explained how I do it.

 

Most of the thinking – the little that’s done – around the affect of Artificial Intelligence and Robotics replacing jobs, is somewhat negative, so it was almost a relief to read John Hagel’s perspective that we could use this transition as an opportunity to rethink the nature of work.

(more…)

Aug/16

18

What we take for granted

I cut a short 30 minute competition entry for a friend today. A relatively simple single-take green screen over a Pond 5 background she purchased.

Except we used a bunch of technologies that were all non-existent just a few years ago.

Starting with some Blackmagic Design ProRes files, we:

  • Sped up the talent about 20% with no visible or audible artifacting
  • Keyed out the green background by using the built-in keyer in FCP X at the default settings
  • Repositioned the talent to better fit the background shot
  • Slowed down the background to 66% with no visible artifacting
  • Applied a real time blended mask and gaussian blur on the background (over a duplicate, not blurred copy to simulate depth of field
  • Used the Color Board to reduce the exposure on her face, while using a mask so her eyes continued to sparkle

all in real time on a 2015 Retina 5K iMac and Final Cut Pro X.

It wasn’t that long ago that applying a soft edge to a mask; or any gaussian blur, or any chroma key meant a render before playback.

Like in the machine learning/AI field, the video technologies also keep getting better all the time.

Maybe I’m pushing this subject a bit hard, but I really believe we are on the cusp of a wide range of human activities being taken over by smart algorithms, also known as Machine Learning. As well as the examples I’ve already mentioned, I found an article on how an “AI” saved a woman’s life, and how it’s being used to create legal documents for homeless (or about to be homeless) in the UK.

(more…)

<< Latest posts

Older posts >>

December 2016
M T W T F S S
« Nov    
 1234
567891011
12131415161718
19202122232425
262728293031