The topic of generative AI comes up frequently in my newsletter, Actuator. I admit that I was a bit hesitant to spend more time on the subject a few months back. Anyone who has been reporting on technology for as long as I have has lived through countless hype cycles and been burned before. Reporting on tech requires a healthy dose of skepticism, hopefully tempered by some excitement about what can be done.

This time out, it seemed generative AI was waiting in the wings, biding its time, waiting for the inevitable cratering of crypto. As the blood drained out of that category, projects like ChatGPT and DALL-E were standing by, ready to be the focus of breathless reporting, hopefulness, criticism, doomerism and all the different Kübler-Rossian stages of the tech hype bubble.

Those who follow my stuff know that I was never especially bullish on crypto. Things are, however, different with generative AI. For starters, there’s a near universal agreement that artificial intelligence/machine learning broadly will play more centralized roles in our lives going forward.

Smartphones offer great insight here. Computational photography is something I write about somewhat regularly. There have been great advances on that front in recent years, and I think many manufacturers have finally struck a good balance between hardware and software when it comes to both improving the end product and lowering the bar of entry. Google, for instance, pulls off some truly impressive tricks with editing features like Best Take and Magic Eraser.

Sure, they’re neat tricks, but they’re also useful, rather than being features for features’ sake. Moving forward, however, the real trick will be seamlessly integrating them into the experience. With ideal future workflows, most users will have little to no notion of what’s happening behind the scenes. They’ll just be happy that it works. It’s the classic Apple playbook.

Generative AI offers a similawow” effect out the gate, which is another way it differs from its hype cycle predecessor. When your least tech savvy relative can sit at a computer, type a few words into a dialogue field and then watch as the black box spits out paintings and short stories, there isn’t much conceptualizing required. That’s a big part of the reason all of this caught on as quickly as it did — most times when everyday people get pitched cutting-edge technologies, it requires them to visualize how it might look five or 10 years down the road.