Edit 2 to add: I think it's important to be specific about what the computing is for. If you just need to solve a small number of equations, then yes, you can do that with a slide rule. But in the written communication case above, the computing is only useful when done with at least the speed of an early microcomputer and paired with digital storage and/or networking and a variety of I/O devices. Still, we don't strictly need our modern supercomputers for that use case, except that it's now considered weird and limiting to use anything less. Also, I bring up the written communication use case because there is a rising backlash against allowing personal computers at all in certain contexts, such as education, because of AI-based cheating. I don't want disabled people like me to lose what we've gained from personal computing in the specific use case I described above. Maybe the solution is to normalize using less than a maximally powerful, Internet-connected personal computer in such contexts.

- The usual advantages of vector graphics: resolution-independence, zoom without jagged edges, etc.

- As a consequence of the above, vector graphics (particularly SVG) can more easily be converted to useful tactile graphics for blind people.

- Vector graphics can more practically be edited.

I'm partially blind, and I know many fully blind people. None of us have being sighted as our one dream.

As someone who saw what impact WPF had on average users running average hardware in the late 2000s to early 2010s, I disagree.

In 2011, my brother was in seminary, using an average Windows Vista-era laptop that he had been given in 2008. When he was home for Christmas in 2011, we were talking about his laptop, and he told me that the Logos Bible software ran sluggishly on that laptop. He said something about how, for reasons unknown to him, the current version of Logos required advanced graphics capabilities (I forget exactly how he phrased it, but he had learned that the slowness had something to do with graphics). Bear in mind, this is software that basically just displays text, presumably with some editing for adding notes and such. At the time, I just bought him another laptop.

A few years later, I happened to read that Logos version 4 was built on WPF. Then, remembering my brother, I found this Logos forum thread:

https://community.logos.com/discussion/6200

This shows that Logos users were discussing the performance of Logos on machines with different graphics hardware. For a program that was all about displaying and editing text, it shouldn't have mattered. WPF had made a bet on then-advanced graphics hardware for reasonable performance, and that was bad for these users. And that's just the one example I know about.

Have we really reached the limit of how much we can reliably automate these things via good old metaprogramming and/or generator scripts, without resorting to using unreliable and expensive statistical models via imprecise natural language?

> Refusing to use AI out of principle is as irrational as adopting it out of hype.

I'm not sure about this. For some people, holding consistently to a principle may be as satisfying, or even necessary, as the dopamine hit of creation mentioned in the article.

So was the learned helplessness already ingrained by 2000? How far back does it go?

So we need to pay attention to every detail that doesn't have a single obviously correct answer, and keep the volume of code we're producing to a manageable enough level that we actually can pay attention to those details. In cases where one really is just literally moving data from here to there, then we should use reliable, deterministic code generation on top of a robust abstraction, e.g. Rust's serde, to take care of that gruntwork. Where that's not possible, there are details that need our attention. We shouldn't use unreliable statistical text generators to try to push past those details.

Comments URL: https://news.ycombinator.com/item?id=46996269

Points: 20

# Comments: 1

That's not the only question worth asking though. It could be that the tool is useful, but has high negative externalities. In that case, the question "what kind of person uses/rejects this" is also worth considering. I think that if generative AI does have high negative externalities, then I'd like to be the kind of person that rejects it.