@UP8@mastodon.social2025-07-30 02:08:16
🏳️🌈 Commodore 64 Ultimate is a new FPGA-based computer that should be compatible with most classic C64 games and software
https://liliputing.com/commodore-64-ultimate-is-a-new-fpga-based-computer-t…
@Techmeme@techhub.social2025-07-31 15:55:42
Microsoft's FY 2025 report excludes the names of rivals, breaking from a common industry practice; its last report designated 25 companies as competitors (Jordan Novet/CNBC)
https://www.cnbc.com/2025/07/31/microsoft-competitors-filings.html
@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.
@arXiv_quantph_bot@mastoxiv.page2025-06-30 09:54:00
Robust quantum reservoir computers for forecasting chaotic dynamics: generalized synchronization and stability
Osama Ahmed, Felix Tennie, Luca Magri
https://arxiv.org/abs/2506.22335
@fanf@mendeddrum.org2025-05-31 14:42:03
from my link log —
comrak: a CommonMark and GFM compatible Markdown parser and renderer in Rust.
https://github.com/kivikakk/comrak
saved 2025-03-31 …
@arXiv_csLO_bot@mastoxiv.page2025-06-30 08:35:10
Computation by infinite descent made explicit
Sebastian Enqvist
https://arxiv.org/abs/2506.22206 https://arxiv.org/pdf/2506.22206
@Techmeme@techhub.social2025-07-30 07:30:53
A look at OneChronos, as it seeks to create "smart markets" that would allow firms to trade GPU compute like other commodities, such as electricity and oil (Alex Konrad/Upstarts Media)
https://www.upstartsmedia.com/p/one-chronos-auctionomics-launc…
@johnleonard@mastodon.social2025-05-30 15:07:31
Data privacy experts are calling on the government to urgently tighten regulation around facial recognition technology, amid growing concerns over its unregulated use by police forces and private companies across the UK.
https://www.computing.co.uk/news/202…
@johnleonard@mastodon.social2025-05-30 15:11:05
Xerox is one of the three big players in a shrinking market for print. This uncomfortable position means it is having to reinvent itself, pushing for growth through a new global business services organisation and pursuing novel revenue streams.
https://www.computing.co…
@Techmeme@techhub.social2025-07-30 10:30:55
Sources: the US intelligence community persuaded the DOJ that allowing the HPE-Juniper merger was essential to US national security and competing with Huawei (Mike Allen/Axios)
https://www.axios.com/2025/07/30/merger-hpe-juniper-networks-national-security
