You can use a deque as a stack (First In, Last Out) or as a queue (First In, First Out). Lists are especially inefficient when adding/removing from the beginning of the list, but, for deques, it’s a O(1) operation.

I’m with you. Also, it seems like it would be much more efficient to do carbon capture at the source, where the fuel is being used, like a power plant, where the concentrations are relatively high, compared to atmospheric capture where CO2 is less than 0.1%.

I wish Apple wouldn’t restrict them as much as they do.

I used to be an ORM-hater, but my experience with Django has changed my mind, somewhat. I still think there are projects where ORM is unnecessary or even harmful, but for some projects, being able to lean on an ORM to create simple queries/updates or to handle DB migrations is a big time saver. And you can always fall back to hand-written SQL when you need to as long as the ORM allows it, which it absolutely should.

And it’s written in Java. Even though I’m not a huge fan of Java, it’s almost refreshing to see a new project claiming high performance that isn’t written in Rust or Go.

I’m seeing a lot of commenters shitting on Texas here, and while it’s not completely undeserved, I’d like to point out that Texas is 1st in the nation in wind power generation. Texas will implement things – even “Blue” things – if the economics make sense.

I feel like this is the ad-equivalent of the sub-prime mortgage situation, pre-crisis. With mortgages, you had loans that no individual bank or bank manager would want, and then you had an automated process that obfuscated the individual loan details and produced financial products that could be sold as high quality. In the ad world, it’s the same thing. You have these websites that nobody would buy ads from, individually, but somehow, through an automatic process offered by Google and friends, the worthless product becomes valuable.

The DEA says that “manufacturers only sold approximately 70 percent of their allotted quota”, but we don’t get our medications from “manufacturers”; we get our medication from pharmacies, who often only carry 1 generic version of each medication in addition to the brand version. What percentage of generic manufacturers have hit their quota? My guess is that most of the slack is held by manufacturers of brand-name medication, while most of the limits are hitting manufacturers of generics.

Also, the “70 percent” stat is for “amphetamine products”, but what is that referring to, exactly? Adderall? Vyvanse, which is an amphetamine prodrug? All stimulants? (It wouldn’t surprise me, coming from the agency that likes to refer to all illegal drugs as “narcotics”.)

This narrative that the FDA and DEA is pushing – that manufacturers are somehow deciding not to make and sell medication that there is obvious demand for – does not pass the smell test. Maybe the DEA quotas aren’t to blame, but the notion that drug companies are deciding not to make and sell medication – the one thing we’ve been able to count on them to do historically – for some unknown reason that nobody is able to figure out is ludicrous.

I wish there was a way to turn off predictive radar. It sometimes has the storm completely changing direction. So inaccurate.

I’ve noticed the same thing. I was somewhat optimistic about Apple’s purchase of DarkSky and planned integration of DarkSky technology into Apple Weather. I mean, DarkSky was awesome. Surely, DarkSky technology + Apple’s resources would result in the ultimate weather app! Boy, was I wrong. Apple obviously took a wrong turn somewhere because the new and improved Apple Weather is anything but.

That’s a really great idea. Makes a lot more sense than relying on official accounts on 3rd party platforms like Twitter, Reddit, and Facebook.

If there was an easy answer, someone would have implemented it already. Obviously, it’s a challenging problem, and I don’t claim to have the solution.

I think expanding the voting dimensions (a la Slashdot) would make it easier to create an algorithm, but it pushes complexity to the user, so that’s a tradeoff.

But, even with up/down votes, I think there are potential ways of identifying users whose votes deserve more weight. For instance, someone who up-votes both sides of an argument chain (because both sides are making good-faith responses and adding to the conversation) should be boosted.

We need the karma-equivalent of PageRank. Every vote should not be treated the same, just as Google doesn’t weight every link equally. The “one user one vote” system is the equivalent of pre-Google search engines that would rank pages by how many times they contained the search term. But it can’t be as simple as “votes from higher-karma users are worth more” because the easiest way to build insane karma is to build a bot or spam low-effort replies to every rising post. Still, the system needs to be able to extract the wisdom of the crowd from the stupidity of the crowd, and the only way to do that is to apply a weighting gradient to users and their votes.