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In truth, AI tech has been around for a while, but it’s only recently taken a more central role, and is doing a better job than traditional approaches. That’s how the world’s post offices automated the sorting of mail, and the same basic strategy is how we have OCR today, live on our phones in photos and videos we capture. To teach a computer to understand human handwriting, you could show it many pictures of handwritten characters, tell the computer which characters the images represent, and then use that trained neural net to identify new handwritten letters. Training a machine learning model is essentially showing a computer what you want by example, many times over, by providing it with a data set (inputs) and telling it what it means (outputs). Training a neural network, a prompt given to Stable Diffusion Yes, you could train a neural network, and you could use fuzzy logic for crude tasks, but today’s tech has upped the speed and scale of what’s possible by several orders of magnitude - here’s a technical primer. Today it’s often known as Machine Learning, or ML, and the latest chips from Apple and Intel both include modules designed to improve the speed of ML operations.īack at university, where I studied Information Technology, I majored in Artificial Intelligence and Artificial Life, but the pieces weren’t in place in the 1990s for a true revolution - “game-changing AI” was always a year away.

Artificial Intelligence encompasses many areas: natural language processing, neural networks, expert systems, machine vision, and more.

Let’s take a step back and look at some broad brushstrokes. Here, I’ll take you through the ideas behind the tech, along with specific examples of how modern, smart technology will change your post workflow tomorrow, or could today.

While a variety of AI-based technologies have been improving steadily over the past several years, it’s the recent giant strides made in image generation that’s potentially groundbreaking for post production professionals. Siri doesn’t quite understand what you’re asking Google Translate can’t yet seamlessly bridge the gap between languages, and navigation software still doesn’t always offer an accurate route. Artificial Intelligence has promised so much for so long, and in many ways, it’s been less than perfect.