I mean that when a computer can visually understand a document and reformat and reinterpret it in any imaginable way, who cares how it’s stored? When a png or a pdf or a markdown doc can all be be read and reinterpreted into an infographic or a database or an audiobook or an interactive infographic the original format won’t matter.
I don’t think control center actually uses the liquid glass elements. They don’t respond to accessibility options like reduce transparency, for one thing.
I had the same thought, but it sounds like this operates at a much lower level than that kind of thing:
> Then, a physics-based neural network was used to process the images captured by the meta-optics camera. Because the neural network was trained on metasurface physics, it can remove aberrations produced by the camera.
Software calendars are so poor compared to this. There’s no concept of importance, of impact, of life. Just times and titles, every one equivalent. Digital calendars have hardly evolved since the palm pilot.
Imagine if apps just… worked like this, somehow. Start off with a realtime visualization and point and click commands, and as you learn them you can evolve into a straight CLI…
Explaining that semi-obscure reference: Barry Lyndon is a Kubrick film that famously has shots lit by only candlelight. This was accomplished by using extremely ”fast” lenses created by NASA for (I believe) the Apollo missions.
AlphaGo uses discovery when it evaluates potential moves and iterates.
Claude Code uses discovery when it generates a script and the evaluates whether it works or not.
He’s saying we need to allow ai systems to do the evaluation and iteration themselves for science and engineering the same way we do for code.
Basically, harness engineering for engineering.