@fanf@mendeddrum.org2025-08-01 14:42:03
from my link log —
Algebraic effects: another mistake carried through to perfection?
https://kjosib.github.io/Counterpoint/effects.html
saved 2025-05-10
@fanf@mendeddrum.org2025-08-01 14:42:03
@bmariusz@techhub.social2025-06-04 18:29:39
Day 2:
TL;DR:
❌ `composite: true`
❌ `tsconfig.build.json`
✅ `paths` in `tsconfig.base.json`
✅ `include` shared libs explicitly where needed
✅ `turbo run build` just works
Wrestled for hours (~3) with TypeScript `project references` and `paths` in a Turbo monorepo (NestJS, ESM).
Turns out: if you want global aliases like `@my-lib/foo` to *just work* across apps — skip `composite: true` and `tsc --build`.
Project references and alia…
@tiotasram@kolektiva.social2025-07-30 17:56:35
Just read this post by @… on an optimistic AGI future, and while it had some interesting and worthwhile ideas, it's also in my opinion dangerously misguided, and plays into the current AGI hype in a harmful way.
https://social.coop/@eloquence/114940607434005478
My criticisms include:
- Current LLM technology has many layers, but the biggest most capable models are all tied to corporate datacenters and require inordinate amounts of every and water use to run. Trying to use these tools to bring about a post-scarcity economy will burn up the planet. We urgently need more-capable but also vastly more efficient AI technologies if we want to use AI for a post-scarcity economy, and we are *not* nearly on the verge of this despite what the big companies pushing LLMs want us to think.
- I can see that permacommons.org claims a small level of expenses on AI equates to low climate impact. However, given current deep subsidies on place by the big companies to attract users, that isn't a great assumption. The fact that their FAQ dodges the question about which AI systems they use isn't a great look.
- These systems are not free in the same way that Wikipedia or open-source software is. To run your own model you need a data harvesting & cleaning operation that costs millions of dollars minimum, and then you need millions of dollars worth of storage & compute to train & host the models. Right now, big corporations are trying to compete for market share by heavily subsidizing these things, but it you go along with that, you become dependent on them, and you'll be screwed when they jack up the price to a profitable level later. I'd love to see open dataset initiatives SBD the like, and there are some of these things, but not enough yet, and many of the initiatives focus on one problem while ignoring others (fine for research but not the basis for a society yet).
- Between the environmental impacts, the horrible labor conditions and undercompensation of data workers who filter the big datasets, and the impacts of both AI scrapers and AI commons pollution, the developers of the most popular & effective LLMs have a lot of answer for. This project only really mentions environmental impacts, which makes me think that they're not serious about ethics, which in turn makes me distrustful of the whole enterprise.
- Their language also ends up encouraging AI use broadly while totally ignoring several entire classes of harm, so they're effectively contributing to AI hype, especially with such casual talk of AGI and robotics as if embodied AGI were just around the corner. To be clear about this point: we are several breakthroughs away from AGI under the most optimistic assumptions, and giving the impression that those will happen soon plays directly into the hands of the Sam Altmans of the world who are trying to make money off the impression of impending huge advances in AI capabilities. Adding to the AI hype is irresponsible.
- I've got a more philosophical criticism that I'll post about separately.
I do think that the idea of using AI & other software tools, possibly along with robotics and funded by many local cooperatives, in order to make businesses obsolete before they can do the same to all workers, is a good one. Get your local library to buy a knitting machine alongside their 3D printer.
Lately I've felt too busy criticizing AI to really sit down and think about what I do want the future to look like, even though I'm a big proponent of positive visions for the future as a force multiplier for criticism, and this article is inspiring to me in that regard, even if the specific project doesn't seem like a good one.
@StephenRees@mas.to2025-05-30 16:53:28
Put away pipelines, go with grids!
By David Suzuki with contributions from Senior Editor and Writer Ian Hanington
It’s good to see ideas such as increasing self-sufficiency and diversifying trade partners emerging in response to U.S. attacks on Canada’s economy and threats to our sovereignty. As usual, though, the fossil fuel industry and its supporters are taking advantage of this “crisis” to push for more oil and gas infrastructure, particularly pipelines.
@jtk@infosec.exchange2025-07-28 19:57:53
rsyslog lead dev on AI, and also see this: https://www.rsyslog.com/clarifying-ai-first-what-it-really-means-for-rsyslog/
@mapto@qoto.org2025-06-18 10:17:30
On July 1st, I'll be presenting our work on the BogoSlov project (https://4euplus.eu/4EU-1150.html) at the conference "Transfer of Ideas in European Intellectual History: From Medieval Manuscripts to Interactive Online Content" held at the Institute of Slavistics of the University of Innsbruck
@philip@mastodon.mallegolhansen.com2025-07-11 17:57:33
@… @… I’m really sorry to hear this. Over the years I’ve noodled with a few app ideas, and frankly I’ve always been excited to maybe one day get a project to a spot where I was worthy of engaging you all for an icon!
@arXiv_hepex_bot@mastoxiv.page2025-07-16 08:47:21
Community Report from the 2025 SNOLAB Future Projects Workshop
M. D. Diamond, P. Abbamonte, A. Arvanitaki, D. M. Asner, D. Balut, D. Baxter, C. Blanco, D. Boreham, M. Boulay, B. Broerman, T. Brunner, E. Caden, A. Chavarria, M. Chen, J. P. Davis, A. Drlica-Wagner, J. Estrada, N. Fatemighomi, J. Foster, D. Freedman, C. Gao, J. Hall, S. Hall, W. Halperin, M. Hirschel, N. Hoch, Z. Hong, A. Ianni, C. Jillings, D. Johnson, Y. Kahn, C. B. Krauss, T. Laframboise, M. Lai, M. R. Lapointe, B. Lil…
