Adobe is heading into AI/Machine Learning full steam ahead. A private room NAB demo showed picture search and dialog search powered by IBM Watson, and now this collaboration with Stanford organizes takes, matches them to lines of dialog, recognizes voices, faces and emotions, camera framing, and more and then builds dialog-focused stories in any style desired.

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Design is much more than the way things look. It encompasses every aspect of every interaction with the device, object or software package you’re using. Josh Clark published a talk he gave on behalf of his design studio big medium, that is focused on design in the era of the algorithm, or Artificial Intelligence.

It’s a very long and deep article, well worth the read if you design anything at all. I found it very relevant as we are currently designing our most complex and powerful app. Read on for a list of the topics.

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A new Market Watch article spells out the results of a study that pulled data from an employment report from University of Oxford, processed into a visual chart by Visual Capitalist.

Not surprising, but retail service jobs are likely to do poorly, while high-touch occupations like nursing and teaching are likely to remain. Overall – and quite unfortunately for society – most of the job losses will be among relatively unskilled workers.

While there have been huge disruptions to employment in the past, there have been new jobs created, which is hard to foresee from this chart.

Consider the chart a career planning guide! I’m somewhat relieved that “Software Developers and Programmers” are relatively safe, although surprised as code is increasingly written by code! There is a surprising amount of creativity that goes into designing the software, that isn’t directly related to the code, so I guess that’s the safe part?

There isn’t a direct category that I could slot production and post production into, but since creativity in general will be valued, I think that creativity will continue to be valued. On the other hand, relatively routine tasks like organization and preparing for editing is likely to be vulnerable.

For an indication of when the jobs will disappear, consider this article about a paper: “When Will AI Exceed Human Performance? Evidence from AI Experts.” In this study, experts where asked their expectation as to when jobs would be eliminated. Bottom line, they could all be gone in 125 years.

I’ve written here before, and Terry Curren and I have discussed repeated on The Terence and Philip Show, that many jobs are likely to be replaced by the combination of Artificial Intelligence and Robotics/Automation. It’s good to see people thinking and writing about these things, as does Caitlin Fitzsimmons of the Sydney Morning Herald (Australia), in an article – How to prepare for the jobs of the future when you don’t know what they are – that features an interview with Pulitzer prize-winning author and New York Times columnist, Thomas Friedman, who writes about the age of acceleration in his new book, Thank You For Being Late.

The whole article (and likely the book, which I’m about to buy) are worth the read, but I loved this paragraph from Ms Fitzsimmons:

That’s because the only way to equip children for the future of work is to develop their imagination, creativity and emotional intelligence. If the world is changing, the best thing you can do is equip them for change. They need to be emotionally resilient with a habit of self-directed lifelong learning.

While projecting the changes that Artificial Intelligence (AI) and Machine Learning (ML) might bring about in the future, it was interesting to look back and see just what didn’t exist 10 years ago. Keep in mind that the Internet itself is only just over 30 years old.

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It’s relatively easy to get an overview of the current state of Artificial Intelligence (AI). It’s probably easier to understand the benefits of machine learning, particularlyMachine Learning (ML) that’s already applied to common tasks that we can benefit from now because we’re fitting those new technologies within existing frameworks.

What is much harder to determine, is how machine learning will be directly applied to post production processes, and what role AI will take in our collective production future.

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Over the last couple of years I’ve become more and more interested in the ways that the research being done into Artificial Intelligence (AI) might be applied to production and post production. In this article I’ll be giving an overview of what AI is at this stage of development, and what technologies are being used. Later articles will cover immediate and future applications and implications.

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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.

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