AI tools in post-production


AI is already used in post-production, says Julian Nelson, the hdirector of Post Production and co-founder of Residence Pictures.

The media and entertainment (M&E) industry is no stranger to AI. In fact, the use of machine learning (ML) and deep learning algorithms is becoming more and more widespread in M&E.

As you may know, ML and DL are useful for recognizing patterns in large datasets. In turn, this can be used to inform decision-making processes that require a level of precision that humans alone cannot achieve on their own.
For example, ML helps create concept art in filmmaking or TV production by automatically suggesting possible aesthetic choices based on existing datasets containing thousands or millions of images from other movies or TV shows. . So far, this technology has mainly been used in the Hollywood blockbuster Avengers: Endgame, which grossed $2 billion worldwide, to generate over 100 million facial expressions for its characters based on their appearances. precedents in different Marvel movies over time!

facial recognition
Facial recognition is a sophisticated artificial intelligence technology that can be used for many purposes. It can also be used for nefarious reasons. Facial recognition technology allows us to identify people based on their facial characteristics, which makes it useful for law enforcement and marketing purposes, but also presents a threat to privacy in the wrong hands. .
In recent years, this technology has been used by video games and social media platforms like Facebook to identify users’ photos to suggest new friends or suggest content they might like to see the next time they log in. However, governments have also begun to use facial recognition technology: police departments across the country have adopted such systems both as tools for solving crimes and more insidiously as surveillance tools (especially when they are combined with other technologies).

deep learning
Deep learning is a type of machine learning that uses neural networks. Deep learning uses multiple layers of artificial neurons to process data and make predictions. Neural networks were first developed in 1958 by Warren McCulloch and Walter Pitts, who used them to create an algorithm that could recognize specific numbers. More recently, deep learning has been applied to image recognition, speech recognition, natural language processing (NLP), object detection (e.g. in self-driving cars) and other apps.
Deep learning has also enabled new advances in facial recognition technology. For example: Facebook’s DeepFace system can recognize faces with 97% accuracy; Google’s Inception-v3 model can identify objects with 98% accuracy; Yann LeCun’s Resnet50 model can recognize handwritten digits with 99% accuracy; Microsoft Research Asia’s ResNet V2 model can recognize traffic signs from satellite images 90% of the time; OpenAI Five defeated five human experts in Dota 2 after training for just two weeks.

I’ll stop there for a second, the full disclosure of this article so far has been generated using AI with the accompanying image. I used to generate the text by typing in the box: “AI Tools in Post Production”, adding the keywords “AI, technology, post production, editing, HDR, video, concept art, color grading, future”. I then ended by asking him to deliver the article in a witty tone. I looked it up via who said there was 0% similarity with no risk of plagiarism.
The image was generated using In the prompt, I typed “a very detailed, hand-drawn -ar 16:9 flowchart exploring AI technology”. After having the computer generate a few versions, I enlarged the image to the maximum and that is what is used here.
The text and image are unpublished and not modified at all. With hardly any work on my part and little input, I created a rather compelling article about AI using AI.

Is this the future of the post?
With the increasing use of AI and ML in post-production, we need to stay aware of its importance to us as professionals but also take advantage of what it can offer us as artists. While there are many benefits to using this technology, there will also be risks associated with its adoption. We need to be vigilant in how we use it so that we can ensure that our work remains authentic and true to our craft. (This last section was also generated using AI)

Pippa Considine

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