Elementary, Redox and Gentoo already banned it. Nix and Fedora allow it with disclosure. Now Debian and Arch are debating whether to adapt or seal their fate alongside Gentoo. Nix and Fedora got it right. Debian and Arch are deciding whether they want to remain relevant or fade into irrelevance.

Alternatively, I think much better results could be had by computing the cosine similarly using DINOv2 ONNX (@xenova/transformers).

My guess is that the results are greatly limited by relying on the current metrics.

Even better, attach toModelOutput directly to drawTool so it returns the rendered canvas image immediately upon drawing.

Red dwarfs are known to be cooler (the habitable zone is therefore closer) and unstable.

I don't think LHS 1140b is "Earth-like" at all. Rather, it's more like a mini-Neptune, being boiled off by its star.

Edit: JWST emission spectroscopy of LHS 1140b as it passes behind its star rules out a mini-Neptune. https://arxiv.org/abs/2406.15136

https://hnpwa.com/

- “Your app should only collect the minimum user data required for providing service and should avoid collecting unnecessary data.”

- “LG performs security reviews on submitted apps before distribution, using the vulnerability analyzing system.”

- “All app developers must complete and submit well-defined and comprehensible data safety information detailing collection, usage, and sharing of user data.” They explicitly classify the "IP address" under Device Identifier Information.

https://webostv.developer.lge.com/develop/guides/privacy-gui...

Blatant lies.

HE shows 41% ASNs support v6: https://ipv6.he.net/

https://github.com/jdevalk/specification.website/blob/main/p...

https://github.com/jdevalk/specification.website/blob/main/m...

The narrator's interjections were a great touch. It's rare to see a post that is this technically deep but also so fun to read. The journey through optimizing the aliasing query felt like a detective story. We, the readers, were right there with you, groaning at the 50GB memory usage and cheering when you got it down to 5GB.

Fantastic work, both on the code and the prose.

It's not just the sweetener itself. It's the whole shift. More processed crap in everything, sweeteners included. Cheaper, easier, engineered to be addictive. That's the real change that lines up with the weight gain.

Focusing just on sweeteners is missing the point. They're just one piece of the bigger processed food takeover. That's the simpler, more likely explanation.

It’s the same old story. New tool comes along, people freak out about what we’re “losing.” But they’re missing the point. It’s never about losing skills, it’s about shifting them. And usually, the shift is upwards.

Take GPS. Yeah, okay, maybe you can’t navigate with a paper map anymore. So what? Navigation isn’t about memorizing street names. It’s about getting from A to B. GPS makes that way easier, for way more people. Suddenly, everyone can explore, find their way around unfamiliar places without stress. Is that “dumber”? No, it’s just… better navigation. We optimized for the outcome, not the parlor trick of knowing all the streets by heart.

Same with the printing press. Before that, memory was king. Stories, knowledge – all in your head. Then books came along, and the hand-wringing started. “We’ll stop memorizing! Our minds will get soft!” Except, that’s not what happened. Books didn’t make us dumber. They democratized knowledge. Freed up our brains from rote memorization to actually think, analyze, create. We shifted from being walking libraries to… well, to being able to use libraries. Again, better.

Now it’s AI and coding. The worry is, AI code assistants will make us worse programmers. Maybe we won’t memorize syntax as well. Maybe we’ll lean on AI to fill in the boilerplate. Fine. So what if we do?

Programming isn’t about remembering every function name in some library. It’s about solving problems with code. And AI? Right now, it’s a tool to solve problems faster, more efficiently. To use it well in its current form, you need to be better at the important parts of programming:

- Problem Definition: You have to be crystal clear about what you want to build. Vague prompts, vague code. AI kind of forces you to think precisely.

- System Design: AI can write code snippets. As of right now, designing a whole system? That’s still on you. And that’s the hard part, the valuable part.

- Testing and Debugging: AI isn’t magic. At least, not yet. You still need to test, validate, and fix its output. Critical thinking, still essential.

So, yeah, maybe some brain scans will show changes. Brains are plastic. Use a muscle less, it changes. Use a new one more, it grows. Expected. But if someone’s scoring lower on some old-school coding test because they rely on AI, ask yourself: are they actually worse at building software? Or are they just working smarter? Faster? More effectively with the tools available today?

This isn’t about “dumbing down.” It’s about cognitive specialization. We’re offloading the stuff machines are good at – rote tasks, memorization, syntax drudgery – so we can focus on what humans are actually good at: abstraction, creativity, problem-solving at a higher level.

Don’t get caught up in nostalgia for obsolete skills. Focus on the outcome. Are we building better things? Are we solving harder problems? Are we moving faster in this current technological landscape? If the answer is yes, then maybe “dumber” isn’t the right word. Maybe it’s just... evolved. And who knows what’s next?

https://tulio.org/blog/dumber-no-different/