Any chance you have an nvidia card? Nvidia for a long time has been in a worse spot on Linux than AMD, which interestingly is the inverse of Windows. A lot of AMD users complain of driver issues on Windows and swap to Nvidia as a result, and the exact opposite happens on Linux.

Nvidia is getting much better on Linux though, and Wayland+explicit sync is coming down the pipeline. With NVK in a couple years it’s quite possible that nvidia/amd Linux experience will be very similar.

“they can’t learn anything” is too reductive. Try feeding GPT4 a language specification for a language that didn’t exist at the time of its training, and then tell it to program in that language given a library that you give it.

It won’t do well, but neither would a junior developer in raw vim/nano without compiler/linter feedback. It will roughly construct something that looks like that new language you fed it that it wasn’t trained on. This is something that in theory LLMs can do well, so GPT5/6/etc. will do better, perhaps as well as any professional human programmer.

Their context windows have increased many times over. We’re no longer operating in the 4/8k range, but instead 128k->1024k range. That’s enough context to, from the perspective of an observer, learn an entirely new language, framework, and then write something almost usable in it. And 2024 isn’t the end for context window size.

With the right tools (e.g input compiler errors and have the LLM reflect on how to fix said compiler errors), you’d get even more reliability, with just modern day LLMs. Get something more reliable, and effectively it’ll do what we can do by learning.

So much work in programming isn’t novel. You’re not making something really new, but instead piecing together work other people did. Even when you make an entirely new library, it’s using a language someone else wrote, libraries other people wrote, in an editor someone else wrote, on an O.S someone else wrote. We’re all standing on the shoulders of giants.

18 months ago, chatgpt didn’t exist. GPT3.5 wasn’t publicly available.

At that same point 18 months ago, iPhone 14 was available. Now we have the iPhone 15.

People are used to LLMs/AI developing much faster, but you really have to keep in perspective how different this tech was 18 months ago. Comparing LLM and smartphone plateaus is just silly at the moment.

Yes they’ve been refining the GPT4 model for about a year now, but we’ve also got major competitors in the space that didn’t exist 12 months ago. We got multimodality that didn’t exist 12 months ago. Sora is mind bogglingly realistic; didn’t exist 12 months ago.

GPT5 is just a few months away. If 4->5 is anything like 3->4, my career as a programmer will be over in the next 5 years. GPT4 already consistently outperforms college students that I help, and can often match junior developers in terms of reliability (though with far more confidence, which is problematic obviously). I don’t think people realize how big of a deal that is.

825,000 chickens per year in the U.S are accidentally boiled alive or drowned before their intended slaughter. https://animalclock.org/ this isn’t prevented because prevention mechanisms cost money, as in they eat into profits.

It’s standard practice for male pigs to have their tails and testicles ripped out without pain relief https://www.vox.com/future-perfect/23817808/pig-farm-investigation-feedback-immunity-feces-intestines this link also showcases how people abuse pigs for fun. Objectifying animals you kill is a coping mechanism for humans, engaging in that much killing is unnatural and unhealthy for humans, it also leads to vastly higher rates of domestic violence and crime, as it normalizes violence as a solution.

It’s normal for foxes to have their skin ripped off while they’re alive. Animals have their beaks ripped off so they can’t kill each other in distress, as they go literally insane, abandon normal social hierarchies, and start simply trying to kill each other given the lack of space. http://www.nationearth.com/

I understand ignorance of how horrible the conditions are is a normal part of how humans justify our atrocities. However what always baffles me is people who appear genuinely concerned about animal welfare can be so absurdly uninformed on the practices that they directly support with their purchases, while criticizing practices that you have absolutely no influence over in a place on the other side of the planet.

What’s the cat abuse situation over there? Is it worse than our pig/cow/chicken abuse situation?

Depends on what you’re looking for. I had a high paying tech job (layoffs op), and I wanted a fun car that accelerates fast but also is a good daily driver. I was in the ~60k price range, so I was looking at things like the Corvette Stingray, but there are too many compromises for that car in terms of daily driving.

The Model 3 accelerates faster 0-30, and the same speed 0-60. Off the line it feels way snappier and responsive because it’s electric, and the battery makes its center of gravity lower, so it’s remarkably good at cornering for a sedan, being more comparable to a sports car in terms of cornering capabilities than a sedan.

Those aren’t normally considerations for people trying to find a good value commuter car, so you would literally just ignore all those advantages. Yet people don’t criticize Corvette owners for not choosing a Hyundai lol

On the daily driving front, Tesla wins out massively over other high performance cars in that price range. Being able to charge up at home, never going to a gas station, best in class driving automation/assistance software, simple interior with good control panel software, one pedal driving with regen breaking.

If you’re in the 40k price range for a daily commuter, your criteria will be totally different, and I am not well versed enough in the normal considerations of that price tier and category to speak confidently to what’s the best value. Tesla does however, at the very least, have a niche in the high performance sedan market.

Like sure fuck Elon, but why do you think FSD is unsafe? They publish the accident rate, it’s lower than the national average.

There are times where it will fuck up, I’ve experienced this. However there are times where it sees something I physically can’t because of either blindspots or pillars in the car.

Having the car drive and you intervene is statistically safer than the national average. You could argue the inverse is better (you drive and the car intervenes), but I’d argue that system would be far worse, as you’d be relinquishing final say to the computer and we don’t have a legal system setup for that, regardless of how good the software is (e.g you’re still responsible as the driver).

You can call it a marketing term, but in reality it can and does successfully drive point to point with no interventions normally. The places it does fuckup are consistent fuckups (e.g bad road markings that convey the wrong thing, and you only know because you’ve been on that road thousands of times). It’s not human, but it’s far more consistent than a human, in both the ways it succeeds and fails. If you learn these patterns you can spend more time paying attention to what other drivers are doing and novel things that might be dangerous (people, animals, etc ) and less time on trivial things like mechanically staying inside of two lines or adjusting your speed. Looking in your blindspot or to the side isn’t nearly as dangerous for example, so you can get more information.