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Isn't treesitter integrated to nvim anyways at this point, even if it's experimental support?

You could probably make things work without nvim-treesitter, but it's an additional maintenance burden you're taking on. As the repo itself says, it's an abstraction layer. You don't _need_ it, but it's nice to have.

Because it wouldn't look good for the EU

Ah yes you choose Switzerland. The country that is famously so affordable to live in.

Last time I have been there food has costed literally double than in my home country which is also in the Alps, also has that standard of living, etc.

But hey, you moderately save on taxes if you finally manage to settle there, which csn be a bit of a challenge since switzerland isn't the most easy country to get permanent residence in.

As a European who has traveled to nearly all European countries and lived in 6 different ones, the idea to only look at the taxrate when chosing your future home country sounds so ridiculously simplistic and money-focused that it could only have come from an American author.

The point of having more money is to lead a happy live. In some countries you need more money to do that than in others. And depending on your character, hobbies and goals in life some countries will make it much more expensive than others.

For example if you like enjoying a beer in the sun and you start living in Island because of the tax rate, your first winter depression will make you question how smart that really was. Or you will just travel to southern Europe on a regular basis, but then why not live there in the first place.


If your country is Italy that might be the case, but groceries are at most 30% more expensive than France, and some are nearly the same price (vegetables). Meat and fish do cost an arm and a leg (100% tax on border crossing).

Meanwhile, median net salary in CH is 5'000-5'500 per month, double to triple its neighbors. So food is actually very affordable.

The food that costs more is the one someone cooked for you, which is logical considering the cook is likely paid more than your engineer (assuming that's your case) salary. But then again, minimum wage Italians are not eating out at the restaurant with any frequency. If you were an engineer in Switzerland instead, you could afford eating out there. The restaurants and terraces are never empty, anyways.

Now, if you want to enjoy a beer in the sun, you can get a 2CHF can at the supermarket and go fire up a barbecue at the lake of Zurich, I see people doing that all the time.


Another project without running real benchmarks. It's very easy to generate tokens, it's much harder to solve tasks locally.

Here is a reference https://www.sharpai.org/benchmark/ For specific tasks, local model could achieve workable level.

It doesn't look like RAM, CPU GPU or bandwidth is getting cheaper if that helps you, quite the opposite.

Marc Andereseen has talked about the downside of RLHF: it's a specific group of liberal low income people in California who did the rating, so AI has been leaning their culture.

I think OpenAI tried to diversify at least the location of the raters somewhat, but it's hard to diversify on every level.


Do you have any links to documentation of this? Andreesen has a definite bias as well, so I'm not about to just accept his say-so in a fit of Appeal to Authority.

(eg: "Cite?")


He was talking about it in the Lex Friedman interview after Trump was elected. And he was talking about a lot of things the Biden administration forced on Silicon Valley at that time (since then Google lost a case about one of these back-deals).

So no evidence then. Kind of like Lex touting his bona fides as a professor.

For anyone else unfamiliar with the term:

RLHF = Reinforcement Learning from Human Feedback

https://en.wikipedia.org/wiki/Reinforcement_learning_from_hu...


What do low income people have to do with it, when AI companies and research is borne out of Silicon Valley culture of rich, liberal Californians?

I'm still waiting for models based on the curt and abrasive stereotype of Eastern European programmers, as contrast to the sickeningly cheerful AIs we have today that couldn't sound more West Coast if they tried.


Low income and liberal is usually code for certain “undesirables” that conservatives tend to dislike. Better watch what LLM your kids use or they might end up speaking Spanish and listening to rap ;).

It's not about liking / disliking, but conservatives tend to prefer staying together even if it's a bad relatioship, and liberals prefer splitting by default if there are serious problems.

The syncopath style is clearly categorized as more liberal (do what you feel is good).


Does that explain Trump's numerous wives?

Reading your comments is a wonderland of right wing bias.


Eh, or grow up hating American and thinking they need to fly to Cuba to explain to the people are great communism is for them. Who knows.

Poor people, to the billionaire, clearly are morally and ethically unsound.

https://pmc.ncbi.nlm.nih.gov/articles/PMC9533286/


> What do low income people have to do with it, when AI companies and research is borne out of Silicon Valley culture of rich, liberal Californians?

RLHF is "ask a human to score lots of LLM answers". So the claim is that the AI companies are hiring cheap (~poor) people from convenient locations (CA, since that's where the rest of the company is).


Yes, this precisely it. There isn't going to be hard evidence to prove it though. Survey data that underpins some empirical studies have similar transparency issues too. This is far from a new problem.

If you adjust your mindset slightly when searching online, it's not hard to find communities of people looking for quick side work and this was huge during the covid lockdown era. There were people helping train LLMs for all kinds of purposes from education to customer service. Those startups quickly cashed out a few years ago and sold to the big players we have now.

I don't get why this is hard for people to believe (or remember)?


"Poor" in California means earning $80k/year, so they probably are not doing that. Africa / Indonesia / Philippines are better places to find English speaking RLHF workers.

Talked about as in lied about it and you taking his words for gospel without verifying it? Looks just as bad as "Yes-Men" AI models.

Marc Andreesen should get HF on his own RL, because he's completely wrong.

This sounds like something Elon would say to make Grok seem "totally more amazeballs," except "anti-woke" Grok suffers from the same behavior


huh? this is completely inaccurate

You're absolutely right!

It's not really shameful, if you want LIDAR, just buy a new Xiaomi SU7.

What's much worse is that Tesla is hiding the reasons for the crashes in the crash reports (the only company with FSD).


I want every other cars that is a danger to me to have LIDAR.


Probably it's true from reputation standpoint.

Some people in Europe were not that happy when Biden told on public television that the Nord Stream pipeline will be blown up somehow, but luckily the media was good in not talking too much about it and later he listened to his own advisors better about how to communicate.


> The right way might be to fight AI slop with AI enforced guard rails.

Whenever I you tried to develop using guardrails with LLMs, I found out that they are much better at ,,cheating'' than a human: getting around the guardrails by creating the ugliest hacks around them.


Mostly works for me. Most of my projects I have some guardrails for what to do around testing, deploying, etc. Seems to work. You are right that LLMs are good at avoiding work and finding loopholes to do so. But generally if you ask codex to "hey look at my gh prs and label the ones that don't meet the contributor guidelines with 'slop'" it might do a decent enough job. Maybe add a skill that spells out criteria. Maybe set up openclaw or similar to do this every morning and then give you the list of prs it will auto close after you say the word.


There are even simpler things: the rating system. There's no guarantee that the driver won't see what I rated him, so I won't report them.

There are ways to report if a man has been sexual with a woman, but they somehow just don't get kicked out of the driver network.

Also just a simple example: Uber engineering blog is full of examples of how they rewrote their app in native Android then web then native again, but nothing about how to solve the real problems humans experience when driving with them.

It just feels that they view Uber as a simple logistic problem where drivers / riders are interchangeable and less like Tinder that tries to match people with similar scores abd kicks out the worst.


The main problem I see is adding things slowly instead of automatic rewrites.

I remember adding lifetimes in some structs and then wanted to use generics and self pointing with lifetimes because that made sense, and then it didn't work because the composition of some features was not yet part of Rust.

Another thing: there are annotations for lifetimes in function signatures, but not inside the functions where there is a lot of magic happening that makes understanding them and working with them really hard: after finally the borrow checking gave me errors, that's when I just started to getting lots of lifetime errors, which were not shown before.

Rust should add these features but take out the old ones with guaranteed automatic update path.


The edition mechanism covers your last paragraph.


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