maegul
Joined 7 years ago
Joined 7 years ago
For better/worse, and whether completely so or not, the time of the professional keyboard-driven mechanical logic problem solver may simply have just come and gone in ~4 generations (70 years?).
By 2050 it may be more or less as niche as it was in 1950??
Personally, I find the relative lack of awareness and attention on the human aspect of it all a bit disappointing. Being caught in the tides of history is a thing, and can be a tough experience, worthy of discourse. And causing and even forcing these tides isn’t necessarily a desirable thing, maybe?
Beyond that, mapping out the different spaces that are brought to light with such movements (eg, the various sets of values that may drive one and the various ways that may be applied to different realities) would also certainly be valuable.
But alas, “productivity” rules I guess.
For me I’m vaguely but persistently thinking about a career change, wondering if I can find something of more tangible “real world” value. An essential basis of which being the question of whether any given tech job just doesn’t hold much apparent “real world value”.
And more so with AI software/tools, and IMO frighteningly so.
I don’t know where the open models people are up to, but as a response to this I’d wager they’ll end up playing the Linux desktop game all over again.
All of which strikes at one of the essential AI questions for me: do you want humans to understand the world we live in or not?
Doesn’t have to be individually, as groups of people can be good at understanding something beyond an individual. But a productivity gain isn’t on it’s a sufficient response to this question.
Interestingly, it really wasn’t long ago that “understanding the full computing stack” was a topic around here (IIRC).
It’d be interesting to see if some “based” “vinyl player programming” movement evolved in response to AI in which using and developing tech stacks designed to be comprehensively comprehensible is the core motivation. I’d be down.
> we aim for a computing system that is fully visible and understandable top-to-bottom — as simple, transparent, trustable, and non-magical as possible. When it works, you learn how it works. When it doesn’t work, you can see why. Because everyone is familiar with the internals, they can be changed and adapted for immediate needs, on the fly, in group discussion.
Funny for me, as this is basically my principal problem with AI as a tool.
It’s likely very aesthetic or experiential, but for me, it’s strong: a fundamental value of wanting to work to make the system and the work transparent, shared/sharable and collaborative.
Always liked B Victor a great deal, so it wasn’t surprising, but it was satisfying to see alignment on this.
Is this valid rust (it’d be new to me)?!
If not, I’m guessing, from memory, the only way at this in rust is to through traits?
The only silver lining I can see is that a new perspective may be forced on how well or badly we’ve facilitated learning, usability, generally navigating pain points and maybe even all the dusty presumptions around the education / vocational / professional-development pipeline.
Before, demand for employment/salary pushed people through. Now, if actual and reliable understanding, expertise and quality is desirable, maybe paying attention to how well the broader system cultivates and can harness these attributes can be of value.
Intuitively though, my feeling is that we’re in some cultural turbulence, likely of a truly historical magnitude, in which nothing can be taken for granted and some “battles” were likely lost long ago when we started down this modern-computing path.
I suspect for many who’ve touched the academic system, a popular voice that isn’t anti-intellectual or anti-expertise (or out to trumpet their personal theory), but critical of the status quo, would be viewed as a net positive.
Not sure exactly irony you mean here, but I’ll bite on the anti-LLM bait …
Surely it matters where the LLM sits against these values, no? Even if you’ve got your own program from the LLM that’s yours, so long as you may need alterations, maintenance, debugging or even understanding its nuances, the nature of the originating LLM, as a program, matters too … right?
And in that sense, are we at all likely to get to a place where LLMs aren’t simply the new mega-platforms (while we await the year of the local-only/open-weights AI)?
Fair! I was just aspiring to a place where web pages and documents converge more.
Thanks for the recommendations!
Last time I looked into it, a while ago, my impression was that it would get rickety too soon. It’d be a good place to be, I think, if web and “document” tech stacks could have nice and practical convergence.
Having intentionally stayed away from going down the PDF rabbit hole, but now confronting it again recently … what’s the deal with how sparsely populated the space is with solid and (relatively) light weight rendering solutions/back-ends?
Am I missing something or am I right in thinking that there’s a kinda pandoc/FFmpeg shaped hole in the document tooling space that no one wants to (or can’t) fill? Where tex and chrome based solutions are arguably just too heavy for a number of needs but all we really have?
But to be fair, I’m not sure what the average dev/eng is supposed to do against a climate of regular change, many disparate opinionated groups with disparate tech stacks, and, IMO a pretty ~~pure~~ poor engineering culture of actually weighing the value of tech/methods against relevant constraints and trade offs.