> JSON is much easier to directly access and manipulate in JS compared to XML
That doesn't sound like a hard thing to fix? JS already comes with a ton of APIs and “web technologies”, but creating an XML equivalent to JSON.parse/JSON.stringify is somehow outside the realm of the thinkable?
> At this point it's abundantly clear that the productivity gain is real and massive.
Oh? Where is it? Why am I not seeing it as a user if it's abundantly clear? In none of the software I've used frequently in the last year have I seen any of those “real and massive” improvements. Not saying they don't improve at all, but the rate hasn't increased since the advent of LLMs.
I'm still waiting for that shiny new era of software productivity to impact any actual users.
I wrote several tools for myself that have a huge impact on my personal life (a calorie/food tracker, a very custom Todo app that works by combining several strategies that I learned over the years, a personal knowledge base that surfaces information better for me). But it's a personal app, I'm not gonna make it public
Congrats? I used to write one of these every so often in a couple hours when I was learning a new programming language.
Don’t take this as directed at you because I don’t know your background, but I’m starting to wonder if many who called themselves engineers here that have similar takes to this ever knew how to actually program to begin with.
No not fully fledged and feature complete. But a baseline POC with the core functionality? Isn’t every react tutorial these days a Todo app?
Anyways my point wasn’t to try and make myself out to be some John Henry (I could have done without the snarky "congrats", apologies). It’s that drowned out in the noise of AI based development, we forget that there are amazing software engineers out there (I’m not placing myself in this category) that were incredibly productive in a short amount of time. Quite some time ago, I watched, in awe, a live stream of two prominent Go developers completely rewrite the HTTP package, for example. And this was over the course of a night.
We need a new metric to gauge AI usefulness other than “I built this thing quickly”
It used to be that most programmers were good enough to reimplement a basic database app in a few hours as a way of learning a new language or framework.
The pool of programmers today is many times larger and less trained and so correspondingly most of today's programmers simply aren't very good and are astounded by feats that were once basic learning tasks.
I mean in total it's about 300k lines of code (across all the tools I built for myself). It's a poor metric, but it's not something you put together in a couple of hours.
Oh, and specifically the food logging part: no, you didn't do that in a couple of hours years ago. Taking pictures of food and having estimates grounded in your personal "recipe" library was a major research project until vLLMs came out.
There is still like 20 free versions of these on the market (pre-ai) I am sure yours is barely different. You just wasted time and tokens and pat yourself on the back for it and somehow feel this can be applied generally as "productivity" and "massive imporvements in software"
> HN has a lot of people [...] upvoting AI-generated content
And I'm not afraid to say that I'm one of them. I upvoted it because I liked it. I don't see what difference it makes who or what wrote it.
It feels like everyone has been forcibly converted to some anti-AI religion. You're no longer allowed to enjoy text on its own merit. You have to like the human writing, even the hard to read, and loudly espouse hatred of everything that comes out of an LLM. Do not ever say, or even imply, that an LLM can help a blogger write something that is readable. That's blasphemy.
I was actually surprised to see Trinity in the list. Not only does it remind me of The Matrix (1999), I also don't think I've ever encountered someone with that as a real name.
On the one hand, the paper (and especially the headline) overstates and overhypes the results.
On the other hand, the overstated results, if they were true, would be tantamount to saying “we're speedrunning exactly the kind of recursive self-improvement that is a major ingredient in every human extinction scenario”, and yet it is both presented and received as an exciting opportunity.
Brains and neural nets are already quite different things and difficult to compare, but at least you can wave your hands and vaguely say that both are “thinking” by some means of “abstraction or generalization”. DNA is absolutely nothing like that. DNA is more like an encoding for a flowchart for a recipe for building a specific body.
Well yeah... in a time before audio recordings and films, bards and poets were the entertainment superstars. Today it's singers and actors, and we still give them millions for their output.
That doesn't sound like a hard thing to fix? JS already comes with a ton of APIs and “web technologies”, but creating an XML equivalent to JSON.parse/JSON.stringify is somehow outside the realm of the thinkable?
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