Also, not just followers. There’s a kinda “merchant” behaviour too I think … signalling and trading in hype perspectives.
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.
Indeed, likely a useful lens on the current moment I’d say.
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.
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”.
Agreed. And I feel it fair to argue that this is the intended interface between proprietary software and its users, categorically.
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.
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.
Rings true for my impression too. In the end, she’s a YouTuber now, for better or worse, but still puts out what look like thoughtful and informative enough videos, whatever personal vendettas she holds grudges over.
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.
> Ironically, the best answer to many of the article's suggestions (thousands rather than millions, easy to modify, etc.) is to write your own software with LLMs.
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)?
This, for me, has been the question since the beginning. I’m yet to see anyone talk/think about the issue head on too. And whenever I’ve asked someone about it, they’ve not had any substantial thoughts.
Are there good deep dives on how far you can practically this? Especially in combination with headless browser pdf generation?
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?
Certain corners of the world have absolutely cared about and employed the proper use of all the “dashes” well before but all the way up to 2022. I’d imagine LLMs have just consumed some of that material.
The point is that trust is a major component of scientific work and how it functions collectively. A effect being that when that is violated a lot breaks down with a god amount of collateral damage.
With increasing complexity in research and pressure to produce and publish more, it’s a growing weakness.
Bottom line is that team work and trust are now indelible parts of research in a culture predicated on individual success and contributions.
I feel like the new kinda-alternative on the rise is to support federation with either ActivityPub, BlueSky/ATProto or both.
That is, instead of going for search engines, go for open social. It’s obviously a new and relatively unpopular ecosystem, but makes much more sense than this SEO stuff IMO.
Wordpress have rolled out their AP support and it seems to be working well so far. I just “replied” to a blog post on mastodon today without even realising it was from a blog.
> 1. Always sad for me to know how much popular are wireless chargers, wasting 47% more energy aprox for charging the same as a wired charger.
Lots of sibling replies pointing out that the absolute energy loss is negligible and reasonable price for the convenience.
That’s fine.
But there’s a bigger point. This convenience is being used as a justification for sticking with big brand phones. Which maybe tips the balance on the reasonableness, and, more broadly, raises the general issue of how much buying for convenience is a slippery slope. Maybe just charge with a cable?
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.