Category Archives: Artificial Intelligence

The New Media Stars: The Audience

I was privileged to be invited to a panel at 2018 HPA TR-X: Everything You Thought You Knew About Artificial Intelligence in M&E and What You Didn’t Know You Didn’t on a panel titled AI Vision Panel: What Will Happen and When?

It was an interesting topic, although our panel got quite pessimistic about the future of society if we’re not very careful with how AI/Machine Learning comes into our lives, but that’s a blog post for another time.

What has really set me thinking was a comment by John Motz, CTO Gray Meta that his 12 year old and her friends, spend more time creating media for each other than simply consuming it.

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The Growing Importance of AI and Machine Learning to Media & Entertainment

A simple indicator of the growing influence and impact of Artificial Intelligence and Machine Learning is the Hollywood Professional Association (party of SMPTE) inclusion of it in their annual retreat.

For the 2016 Retreat I proposed a presentation on AI & ML that wasn’t deemed relevant at that time.

For the 2017 Retreat I made pretty much the same proposal, which lead to a panel discussion at the Retreat that I was pleased to contribute to.

For the 2018 Retreat the half day tech focus the day before the main conference is:

A half day of targeted panels, speakers and interaction, this year focusing on one of the most important topics our industry faces, Artificial Intelligence and Machine Learning.

Two years ago it wasn’t relevant.

A year ago it was one panel in three days of conference.

This year it’s the tech focus day ahead of the conference!

I’ll be back on a panel this year – Novel AI Implementations: Real World AI Case Studies – and hope to see you there. The HPA Retreat is the closest thing to TED talks for our industry and discuss the topics that will be crucial to film and television production in 2-3 years. Get a heads up before everyone else.

AI, Machine Learning and Distribution Content Metadata

Well, from a couple of days of reading and email newsletters, but there is quite a focus.

MESA Alliance quotes Deluxe Entertainment Services Group chief product offer Andy Shenkler as saying:

“AI is obviously playing a fairly broad role, especially with the areas that we at Deluxe are working on,” he told the Media & Entertainment Services Alliance (MESA) in a phone interview. That includes “everything from the post-production creation process, localization” around advanced language detection and auto translation – “and then even down into the distribution side of things,” he said, noting the latter was “probably the least well-known and discussed” part of the equation.

That article goes on to talk about who’s technologies they use and how they use it to assign metadata to incoming assets. Speaking of Content Metadata (in this case about finished content, not for use in production) Roz Ho, senior vice president and general manager, consumer and metadata at TIVO, writes in a guest blog at Multichannel News:

Not only does machine learning help companies keep up with the tsunami of content, it can better enrich metadata and enable distributors to get the right entertainment in front of the right viewers at the right time.

Machine learning takes metadata beyond cast, title and descriptions, and enables content to be enhanced with many new data descriptors such as keywords, dynamic popularity ratings, and moods, to name a few.

Liz finishes with a short dissertation on how these machines, and people enhanced by them, will be the direction we take in the future.

And out of CES some headlines:

CES 2018: Consumer Technology Association Expects Major Growth for AI in 2018

CES 2018: AI Touted Heavily by LG, Samsung, Byton on Eve of CES

It seems like every day there is news yet another application of Machine Learning (AI) into the Media and Entertainment space, either in production – where it is helping decide what goes in to production as well as helping in production – through to helping people find more appropriate content.

Looking Forward to 2018

As part of the regular year end activities The Digital Production BuZZ invited me, and a bunch of other people, to look forward to 2018 and predict what the major themes will be.

Here is a link to the full show –  
Here is a link to the Transcript-  
And here are the links (including the MP3 version) to your individual interview – 

Believable Fake Humans

The uncanny valley has been a limiting factor on creating realistic humans, but a Nividia research team in Finland have created some amazingly realistic looking humans (and mostly quite attractive ones) using Artificial Intelligence in an approach that goes beyond the limits of training data (to some degree).

To recap, Machine Learning (what we’re really talking about here) has relied on massive amounts of marked up training data to derive it’s internal “algorithm” to match the marked up results on new material. Machines can also be challenged like Googles “walk upright.” To get that results, the machine was challenged to generate actions that “moved forward” and “stayed upright.” It took many iterations to get the results in the video.

This Nividia team has a double “AI” approach. The machine being challenged to create new human face “like but different from” its training set, it matched against another machine that’s been trained to recognize human faces. If machine one can fool machine too into believing it’s created a real face, that’s success.

The images are pretty incredible. Even the eyes are not much lifeless than the average human model!

For now they’re relatively low resolution still images, but we all know that still images will lead to motion images, which will lead – ultimately – to synthetic actors that are “like” your current favorite.

Thereby killing all future movie and TV acting jobs.

Thought’s about Larry Jordan’s “Worries on the future of Editing”

Larry Jordan got on his (self described) soap box this morning with a thoughtful post about the future of editing in an AI infested world. I think we should all be aware of what’s happening, and I’ve certainly been trying to do my part there, as recent posts attest, but I’m not sure I’m quite as concerned about editing jobs as Larry is. Assistants perhaps.

Larry shared his post with me, asking for feedback, and having written a fairly comprehensive response, I decided to share it here as well. While I mostly address the areas where AI/Machine Learning might be used, and why pervasive automated editing is probably way further in the future than Larry’s concern would indicate, none of that negates Larry’s excellent advice on managing your career.

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