Of the changes made last week to the license, this one stands out:
- None of the Work may be used in any form as part, or whole, of an integration, plugin or app that integrates with Atlassian’s Confluence or Jira products.
That is a weird carve-out, so I’d guess the license revision (and technically the reason it’s no longer open source) somehow has to do with Atlassian or their plugin marketplace?
Feel like the (totally impractical) fediverse end-game would be for each individual to have their own activitypub service, and federation happening on a person-by-person basis. So you retain some control over anything you publish, and your history is yours to keep.
As others have said, changing UPS batteries is required maintenance, and I agree 18-24 months is the typical service life for even high-end UPSs. However, you may want to look into LiFePO4 based UPSs, which can handle many more charge-discharge cycles and often have 5-year warranties. More expensive and potentially not as recyclable as lead acid batteries, but maybe appropriate for your use case.
This is a good, short read. For those who are unfamiliar with the AGPL license that the author proposes we all start using, the main difference (and I am not a lawyer) is that under the AGPL, the source code including any modifications must also be made available to all users interacting with the software over a network. This prevents companies from making proprietary versions of AGPL software that are only accessible as a web service, which is one of the big ways that corporations are able to profit from GPL source code contributions these days.
Cat software running on dog hardware.
(As opposed to a cheetah, which is dog software running on cat hardware)
I heard someone won an award for the fjords…
This is so terrible it physically pains me.
“Aerospace chocolatiers” would be a great name for an experimental, new-age music troupe.
The interesting part of the article:
The new flexible polymer and carbon composite boom is coupled with a twelve-unit (12U) CubeSat built by NanoAvionics. After the mission launches atop a Rocket Lab Electron rocket from the company’s Launch Complex 1 in Māhia, New Zealand, the spacecraft will go into a Sun-synchronous orbit at an altitude of about 600 miles (~1,000 km) and the sail will deploy in about 25 minutes to cover an area of 860 ft² (80 m²) with the boom unfolding from the size of a hand to 23 ft (7 m) long. Once deployed, the sail will adjust the vehicle’s orbit by angling itself in relation to the solar wind.
From the slide deck (which is well worth a read IMO), "The Trust Index is the average percent trust in NGOs, business, government and media. ". The same deck indicates that government is seen as, “as Far Less Competent and Ethical than Business.” So what this really tells me is that business (as a whole) is doing a FAR better job of marketing/PR than governments are, which is to be expected I suppose.
Mine’s more like an LLM - exposed to a vast quantity of technical terms that they don’t really understand, but can mash them together well enough to make coherent-sounding statements in JIRA
Ugh, I forgot what April fools is like on the internet.
In UNIX-y systems ./ is your current local directory, so if I was in /usr/home/will and I extracted your file I would expect any file that was like ./foo.txt to be extracted to /usr/home/will/foo.txt, and if there were files like ./testar/bar.txt, they would be extracted to a new directory /usr/home/will/testar/bar.txt – or is that not what you’re talking about?
Who is your PM or senior assigning the tasks? You need to take this up with them – everyone always needs a couple of quick hits in their back pocket. When you stall out grinding on task after impossible task it kills your motivation and productivity, and that’s your boss’s job to fix.
Play stupid games, win stupid prizes.
Fair enough. ML ⊆ AI then. But these days when everyone talking breathlessly about AI taking away jobs they’re almost always taking about LLMs. This article is about ML in particular which is a different discipline with different applications.
ML =/= AI. There are legit uses for ML that don’t have anything to do with LLMs and the cloud. I worked on an ML project 3 or 4 years ago to listen for fan noise that might indicate that it was about to fail soon. We trained a tiny GAN on good and bad noises. It runs on a tiny CPU, locally. Highly specialized work, and I have to imagine there are and will continue to be lots of similar opportunities to bring efficiencies by getting computers to make good observations and decisions - even if only about “simple” things like “does this thing seem like it’s about to break?”
draw.io is a capable web-based flowcharting program. Source code is on github but I’ve never tried locally hosting.
How the fuck is this still a tight race? I just for the life of me cannot understand (I mean, I can, but… I just can’t).