@tiotasram@kolektiva.social2025-07-17 13:31:49
To add a single example here (feel free to chime in with your own):
Problem: editing code is sometimes tedious because external APIs require boilerplate.
Solutions:
- Use LLM-generated code. Downsides: energy use, code theft, potential for legal liability, makes mistakes, etc. Upsides: popular among some peers, seems easy to use.
- Pick a better library (not always possible).
- Build internal functions to centralize boilerplate code, then use those (benefits: you get a better understanding of the external API, and a more-unit-testable internal code surface; probably less amortized effort).
- Develop a non-LLM system that actually reasons about code at something like the formal semantics level and suggests boilerplate fill-ins based on rules, while foregrounding which rules it's applying so you can see the logic behind the suggestions (needs research).
Obviously LLM use in coding goes beyond this single issue, but there are similar analyses for each potential use of LLMs in coding. I'm all cases there are:
1. Existing practical solutions that require more effort (or in many cases just seem to but are less-effort when amortized).
2. Near-term researchable solutions that directly address the problem and which would be much more desirable in the long term.
Thus in addition to disastrous LLM effects on the climate, on data laborers, and on the digital commons, they tend to suck us into cheap-seeming but ultimately costly design practices while also crowding out better long-term solutions. Next time someone suggests how useful LLMs are for some task, try asking yourself (or them) what an ideal solution for that task would look like, and whether LLM use moves us closer to or father from a world in which that solution exists.
@aardrian@toot.cafe2025-07-17 22:00:33
Also a probable WCAG SC 2.5.8 violation.
https://masto.hypertelia.com/@pete/114868028319356678
@ErikJonker@mastodon.social2025-07-17 19:36:37
@burger_jaap@mastodon.social2025-07-17 08:23:13
It's great to see car OEMs integrating smart charging solutions directly into their EVs. ev.energy’s platform allows users to automatically optimise for a range of smart and dynamic tariffs and on-site solar, while responding to local and (inter)national grid needs in flex markets.
https://t…
@primonatura@mstdn.social2025-06-18 11:00:01
"AI is gobbling up water it cannot replace – I’m working on a solution"
#AI #ArtificialIntelligence #Technology
@hanno@mastodon.social2025-06-18 07:20:22
As long as error messages like this can happen, I refuse consider the possibility that matrix could be a secure messaging solution for the masses. I mean... you can't be serious?
If your goal is average users, your No 1 design principle must be that you never bother users with the details of your technical design, which they don't understand anyway. That's a main reason why PGP failed, and people still don't get it. (I mean... I don't understand what that means, and …
@Techmeme@techhub.social2025-06-16 05:30:35
Aspora, which makes financial tools like remittance services for the Indian diaspora, raised a $50M Series B co-led by Sequoia and Greylock at a $500M valuation (Ivan Mehta/TechCrunch)
https://techcrunch.com/2025/06/15/aspora-ge…
@kubikpixel@chaos.social2025-06-18 06:05:31
»Kommentar – Stoppt die sinnfreie KI-Schwemme!
KI-Tools sind überall, verbrauchen viele Ressourcen, schwächen Denken – ihr Einsatz sollte überdacht werden, meint Greta Friedrich.«
Auch meine Meinung, da sich sehr viele sich freiwillig stumpf schalten und dadurch Unmengen an Energie verschwenden. Wie prüft mensch ob die KI eine fortschrittliche Lösung präsentiert?
👉
@arXiv_csSE_bot@mastoxiv.page2025-06-18 08:37:09
Instruction and Solution Probabilities as Heuristics for Inductive Programming
Edward McDaid, Sarah McDaid
https://arxiv.org/abs/2506.13804 https://…
@jake4480@c.im2025-06-17 14:45:43
