I also noticed Gemini's habit of getting stuck on things I said. It became evident quite quickly. I haven't noticed this in the same way in any other model. Something's wrong with that boy
You're not using the good models and then blaming the tool? Just use claude models.
Copilot's main problem seems to be people don't know how to use it. They need to delete all their plugins except the vscode, CLI ones, and disable all models except anthropic ones.
The Claude Code reputation diff is greatly exaggerated beyond that.
Not my experience at all. Copilot launched as a useless code complete, is now basically the same as anything. It's all converging. The features are converging, but the features barely matter anyway when Opus is just doing all the heavy lifting anyway. It just 1-shots half the stuff. Copilot's payment model where you pay by the prompt not by the token is highly abusable, no way this lasts.
Gambling sites probably do have it in their user agreements.
Further, "insider trading" in prediction markets is probably fundamentally illegal under existing commodities fraud laws in the US (I am not a lawyer,) but there's probably nobody actively policing it, and probably no precedent in how to prosecute the cases.
Your own wiki link disagrees with you, most of the article uses landlordism as the base-level example. You've just discovered how "rent seeking" is used as a more broad term to describe many phenomena, but they're still describing them essentially in the metaphor of landlordism.
I think they were referring to the costs of training and hosting the models. You're counting the cost of what you're buying, but the people selling it to you are in the red.
In my experience owning private stock, you basically own part of a pool. (Hopefully the exact same classes of shares as the board has or else it's a scam.) The board controls the pool, and whenever they do dividends or transfer ownership, each person's share is affected proportionally. You can petition the board to buy back your shares or transfer them to another shareholder but that's probably unusual for a rank-and-file employee.
The shares are valued by an accounting firm auditor of some type. This determines the basis value if you're paying taxes up-front. After that the tax situation should be the same as getting publicly traded options/shares, there's some choices in how you want to handle the taxes but generally you file a special tax form at the year of grant.
Postgres nationalists will applaud the conclusion no matter how bad the reasoning is.
Don't get me wrong, the idea that he wants to just use a RDMBS because his needs aren't great enough, is a perfectly inoffensive conclusion. The path that led him there is very unpersuasive.
It's also dangerous. Ultimately the author is willing to do a bit more work rather than learn something new. This works because he's using a popular tool people like. But overall, he doesn't demonstrate he's even thought about any of the things I'd consider most important; he just sort of assumes running a Redis is going to be hard and he'd rather not mess with it.
To me, the real question is just cost vs. how much load the DB can even take. My most important Redis cluster basically exists to take load off the DB, which takes high load even by simple queries. Using the DB as a cache only works if your issue is expensive queries.
I think there's an appeal that this guy reaches the conclusion someone wants to hear, and it's not an unreasonable conclusion, but it creates the illusion the reasoning he used to get there was solid.
I mean, if you take the same logic, cross out the word Postgres, and write in "Elasticsearch," and now it's an article about a guy who wants to cache in Elasticsearch because it's good enough, and he uses the exact same arguments about how he'll just write some jobs to handle expiry--is this still sounding like solid, reasonable logic? No it's crazy.
That's how I've always characterized them. But if you think about it, it's not really true.
The LLM is "lossily" containing things an encyclopedia would never contain. An encyclopedia, no matter how large, would never contain the entire text of every textbook it deems worth of inclusion. It would always contain a summary and/or discussion of the contents. The LLM does, though it "compresses" over it, so that it, too, only has the gist at whatever granularity it's big enough to contain.
So in that sense, an encyclopedia is also a lossy encyclopedia.
the quality is definitely not better, not since the early 2000s when everything was fully digital and everything is single tracked, rhythm shifted to metronome grid, autotuned--the really big budget producers like max martin will put a little effort into the mixdown but by and large they're not even trying to make thing sound good, they're just pumping out minimal effort productions with default settings.
Second guy says he's had a bad philosophy class, implying it's a bad, naive, amateur, or uninformed take on the philosophical subject at hand.
First guy says he's had many, implying he's actually studied philosophy extensively, perhaps majored in it in college or obtained a degree, refuting the idea that the original take was amateur or uninformed.
The LLMs do have "latent knowledge," indisputably, the latent knowledge is beyond reproach. Because what we do know about the "black box" is that inside it, is a database of not just facts, but understanding, and we know the model "understands" nearly every topic better than any human. Where the doubt-worthy part happens is the generative step, since it is tasked with producing a new "understanding" that didn't already exist, the mathematical domain of the generative function exceeds the domain of reality. And, second of all, because the reasoning faculties are far less proven than the understanding faculties, and many queries require reasoning about existing understandings to derive a good, new one.
I claim it's normal to hate public transport. Online, there are some loudmouthed public transport enthusiasts. To them, everyone who isn't doing public transport is a racist, boomer, redneck, luddite, and whatever aspersion you've got.
The real reason America has so many cars is people like cars better, and America developed in a time where people were rich enough to make it happen. People don't like public transport. I asked someone who grew up in another country, in a huge city with only public transport--and reputedly good, clean public transport at that--what they think of public transport, and they said it's gross and for poor people. (It wasn't a code for racism, their country was ethnically monotone.)
People like that don't visit threads like this though. You just get this echo chamber of young, childless, cosmopolitans who only care about a certain kind of efficiency in transport.
I think it's because software engineers are the only group that can unanimously operate LLMs effectively and build them into larger systems. They'll automate their own jobs first and move on to building the toolkits to automate the others.