Note to PR folks: I'm not the InfoQ.com editor named Matt Campbell. Please don't email me about your upcoming press release. If anyone knows a better way to clear up this confusion, please contact me.
I'm a software developer specializing in accessibility for blind and visually impaired people. From mid-2017 to late 2020, I worked for Microsoft on the Windows accessibility team, though my comments were always my own opinion posted on my own initiative.
I'm legally blind myself; I have enough sight to read a desktop computer screen up close with slightly enlarged fonts, but I often use a screen reader when browsing the Web, doing email, and other tasks that don't involve code. (Don't get me wrong; totally blind people can program, but I never got used to doing it that way myself.)
Of course, there's more to me than visual impairment. When it comes to programming, I'm also particularly interested in the challenges of developing cross-platform applications that integrate smoothly with the host platform. Outside of programming, I love music and love to sing. Pre-COVID, I often did karaoke (of course, I memorize the words). And like many nerds, I read science fiction.
Do we have evidence that this will actually happen? Maybe the belief that it won't pass is what requires evidence, but I think there's a widespread feeling right now that things are just getting permanently worse and this is one example.
Compiler developers didn't hoover up as much human creative work as they could, legally or not, to evolve a giant inscrutable thing that does what it does probabilistically, with the explicit goal of replacing as much human labor as possible for the enrichment of the already rich. Whatever benefits we get out of generative AI are just a side effect, and one that may not last when the investors stop subsidizing our access to the big models.
Well, the frontier models aren't freely available in the same way that the training data (the public web) is; they're only available as a limited no-cost tier of a paid service.
There are models where the weights are released and you can run them locally, but one counter-argument I've seen is that these aren't really the models that people are excited about and making extraordinary claims about.
Rust with wxWidgets via wxDragon has recently become a viable option for some kinds of apps. It even has dark mode now. wxWidgets comes with a disappointing amount of bloat though.
I invested about $4,000 in an NVIDIA DGX Spark several months ago. 128 GB of unified RAM, and the NVIDIA GB10 chip. With the RAM, the several CPU cores, and the 4 TB NVMe SSD, it's a very capable ARM64 Linux computer even without the GPU, and so far I've mostly been using it as such. But I wonder, what's the most capable model, specifically for coding, that can run well on that hardware?
Have you found evidence that the code is actually low-quality, or is that just an assumption based on the fact that it's evidently largely LLM-generated?
IMO the word "compute" is too generic here. To me, the most valuable thing that personal computers have brought us so far is the ability to communicate smoothly across (dis)abilities through digital text. Think of a blind student writing an assignment that can be read by a sighted teacher, or a sighted student and a blind teacher, with no transcriber mediating between them, and a blind writer being able to know what they're actually writing and correct it (as opposed to, say, using a typewriter blind). We should be able to do that, with a variety of assistive technologies for different disabilities, with far less computing power than we're using now. Edit to add: And indeed we did, decades ago, including in battery-powered devices. But now we're convinced that our "one device" needs to be able to do everything, thus it needs to have as much computing power as modewrn technology allows.
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.
Are there any models that are specifically trained to produce diagrams as SVG? I'd much prefer that to diffusion-based raster image generation models for a few reasons:
- 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.
That's fine, if we only care about ourselves. I guess the harder part is convincing everyone else to unplug from mass media and not raise their kids on it.
Your argument presupposes that we should accept escalating baseline hardware requirements as good or even necessary, for a desktop computing world that was, from the user's perspective, doing pretty much the same thing as before. I reject that.
Yes, text shaping and layout are complex. My point is that the program wasn't doing anything that should have required a GPU, particularly for the resolutions that were common back then.
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:
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.
I hope we can still get to a point where wasm modules can directly access the web platform APIs and get JS out of the picture entirely. After all, those APIs themselves are implemented in C++ (and maybe some Rust now).
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.
I'm a software developer specializing in accessibility for blind and visually impaired people. From mid-2017 to late 2020, I worked for Microsoft on the Windows accessibility team, though my comments were always my own opinion posted on my own initiative.
I'm legally blind myself; I have enough sight to read a desktop computer screen up close with slightly enlarged fonts, but I often use a screen reader when browsing the Web, doing email, and other tasks that don't involve code. (Don't get me wrong; totally blind people can program, but I never got used to doing it that way myself.)
Of course, there's more to me than visual impairment. When it comes to programming, I'm also particularly interested in the challenges of developing cross-platform applications that integrate smoothly with the host platform. Outside of programming, I love music and love to sing. Pre-COVID, I often did karaoke (of course, I memorize the words). And like many nerds, I read science fiction.
Email: [email protected]
Twitter: @mw_campbell
Blog: http://mwcampbell.us/blog/
Location: Wichita, Kansas, US
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