barremian

> When judging which alternative will succeed, lower perceived human cost beats lower machine cost every time.

Yup this is it. No architect considers using protos unless there is an explicit need for it. And the explicit need is most times using gRPC.

Unless the alternative allows for zero cost startup and debugging by just doing `console.log()`, they won't replace JSON any time soon.

Edit: Just for context, I'm not the author. I found the article interesting and wanted to share.

I think the it-just-works nature and human readability for debugging JSON cannot be overstated. Most people and projects are content to just use JSON even if protos offer some advantages, if not only to save time and resources.

Whether the team saves times in the longer when using protos is a question in its own.

> it codes fully functioning Windows and Apple OS clones, 3D design software, Nintendo emulators, and productivity suites from single prompts

> As is so often the case with AI, that is exciting and frightening all at once

> we need to extrapolate from this small example to think more broadly: if this holds the models are about to make similar leaps in any field where visual precision and skilled reasoning must work together required

> this will be a big deal when it’s released

> What appears to be happening here is a form of emergent, implicit reasoning, the spontaneous combination of perception, memory, and logic inside a statistical model

> model’s ability to make a correct, contextually grounded inference that requires several layers of symbolic reasoning suggests that something new may be happening inside these systems—an emergent form of abstract reasoning that arises not from explicit programming but from scale and complexity itself

Just another post with extreme hyperbolic wording to blow up another model release. How many times have we seen such non-realistic build up in the past couple of years.