First, you'll take home slightly over half of that net of various taxes and deductions, but let's be generous and say your take-home is 200k. You live very frugally, don't go out, don't really buy anything and keep your costs at 50k a year, including rent (!). That leaves you with 150k a year, so after 5 years you have 750k. This allows you to buy a modest 2-3 bed row house with a postage stamp sized garden in one of the less desirable areas of the city.

If you want something that doesn't look like a shed, you are looking at 1 million pounds and up, more like 1.5 million. If you want in a nice area and large garden, make it 2 million.

To be clear: my objection is not at all about enjoying the finer side of life, there's nothing wrong with that. Harrods and a lot of the surrounding areas are not about that. By and large, the crowd who likes that area (and I'm not placing you among them) are there because they want to appear among the rich and flash their shitty LV or Gucci bag which they probably picked up somewhere at a discount.

There are two kinds of drivers of expensive cars:

1. Those who drive their Bentley Continental GT because they appreciate the craftsmanship and the smooth ride

2. Those who are inching along in traffic in Kensington because they want the world to see they have a Bentley.

One of these groups is genuinely wealthy and have class will be driving their grand tourer somewhere in France or Italy on nice roads to their villa, or if they don't like driving, they'll be driven by staff. If they aren't nepo babies, they'll be just as dismayed about the difficulties that 99% of the population lives under, because ultimately we are all in the same boat. If 99% of the crew are unhappy, eventually the captain and the officers will be thrown overboard to the sharks. If the captain wants to have a good time, they have to make sure the crew aren't unhappy at least.

Nevermind that I hate Harrods and that entire area with a passion. It's a tasteless, glitzy tourist trap.

My post was all about the fact that barring a tiny percentile of people who a) live in an affluent area and b) are willing to pay 2-3x the regular supermarket prices, you cannot get good quality food. And you say "ah it's simples, just go to the most egregiously flashy beacon of division between the rich and poor and you can get good fruit"

Thank you, I can still get good fruit at my local grocer in Wimbledon, because it charges 2-3x over the regular high street prices and there are people around who can pay this. Doesn't help someone living in Croydon and having to go to Tesco, does it now.

Gone are the days when you could ask the grocer or farmer to give you a peach to taste. People got used to having 24/7/365 access to everything, and supermarkets optimized purely for looks instead of taste and nutrition, because you aren't allowed to taste anything there. The only thing you can go by is the looks. This means looks sell.

I'd hazard a guess the vast majority of brits don't even know what a proper strawberry tastes like, because the only thing they can buy are beautifully polished turds. Everything tastes watery and crap, or conversely just generic "sweet".

I wouldn't even blame farmers. Their life is hard enough. They are operating on razor thin margins in a very uncertain environment. The consumer (against their own interests) demands that they produce beautifully and cheap turds, so that's what they'll produce. And if you try to do the right thing, you simply run out of money because you can't compete with the turds at the supermarket.

I only have empirical evidence for this, but it got much worse since Brexit as well. The variety has gone down a lot, I see shelves routinely empty at supermarkets and they all seem to be focusing on the same ultraprocessed crap.

Polars is able to lazy evaluate query plans without any unnecessary intermediate allocations, if I want to do algebra on dataframes, I'd use polars.

The narrow usecase seems to be that you have large matrices such that memory efficiency is a concern, but not so large that they don't fit into memory at all.

My point was that this seems like a very narrow niche to me, where I'd still rather use numba or taichi purely because I don't have to evaluate raw strings and can still rely on linters.

But it also isn't a free exchange of ideas. It's a concentration of capabilities in the hands of a few corporations.

This is not some altruistic entity striving for the betterment of humankind. Practically nothing that comes out of the techbro culture is. This is pure and simple greed and the chances that AI can be a vehicle of altruism when it is owned by megacorps is basically zero.

1. People copying others' work, made much easier by AI.

2. AI companies effectively harvesting all the accessible information on an industrial scale and completely sidestepping any permissioning or licensing questions.

I believe both of these are bad and saying "people copied each others' works before the advent of AI" is a poor cop out. It's tantamount to saying that there's no reason to regulate guns more than say knives, because people have used knives to kill each other before guns were invented. The capabilities matter.

The way LLMs empower wholesale "stealing" rather than collaboration is quite evident: why collaborate when you can just feed an entire existing project into the agent of your choice and tell it to spit out a new implementation based on the old one, with a few tweaks of your choice, and then publish it as your work? I put "steal" in quotes because it's perhaps not really stealing per-se, but there's a distinct wrongness here. The LLM operator often doesn't actually possess any expertise, hasn't done any of the hard work, but they can take someone else's work wholesale, repackage it and sell it as their own.

Then there's the second, and IMO much more egregious transgression, which is that the LLM companies have taken what is effectively a public good, but more specifically content that they haven't asked permission to use, and just blanket fed it into their models.

Legally speaking, it's perhaps A-OK because it's not copyright infringement (IANAL). But people on this site often hold the view that if something is a-priori legal, it is also moral (I'm not accusing you of this). What the LLM companies have done is profoundly immoral. They extracted a fortune of the goods and work made by others, without even bothering to ask for permission - or even considering this permission. And then they resell access to this treasure to the public.

Perhaps AI will bring an era of prosperity to humankind like we haven't seen before, perhaps it won't, but that changes nothing about the wrongness of how it started.

Numexpr seems to sit in a sort of odd niche of having to do relatively simple arithmetic on in-core matrix data fast. For anything more complex, Polars seems more powerful and yet easier to understand, Numba and Taichi are both much more flexible in that they can be used to implement much more complex arithmetic (at the cost of writing lower level python code).

Numexpr basically evaluates raw strings, which makes any sort of heavy usage basically immune to linting, code inspection and refactoring.

Pandas has the eval() method on the Dataframe that uses numexpr as backend, but we generally never use it because of the upper mentioned maintenance issues and the availability of better alternatives.

I'm not sure how this works in the legal sense. A human could ostensibly study an existing project and then rewrite it from scratch. The original work's license shouldn't apply as long as code wasn't copy & pasted, right?

What happens when an automated tool does the same? It's basically just a complicated copy & paste job.

The FedEx founder got lucky. The countless others who tried a similar gamble didn't and unfortunately their story doesn't seem to be taught because "desperate founder gambled the employees salary and lost" just doesn't have the same ring.

Who will be held responsible when an AI agent messes up the HR system and the company is exposed to losses due to a mistake? Who is going to be responsible when your SEO agent overspends?

Ultimately, it's going to be you most likely, because I can't see AI firms taking this responsibility.

You might argue that right now it also falls on the employer, since employees are rarely held responsible for genuine mistakes, even if it ends in disaster, however you have a lot of agency over what an employee is doing. Their motivation is generally correlated with doing well, because past success ensures future career growth.

An AI agent has no such incentives. The AI company will just charge you some minimal fee to provide the service, and if it messes up, will wash their hands of responsibility and tell you that you should've been more careful in using it.

I dislike Taleb for various reasons, but using AI agents is basically the definition of a fragile system. It works 99% of the time, lulling people into this sense of security where they can just offload all their work very conveniently. And then 1% of the time (or 0.01% of the time), it ends in utter disaster, which people are very bad at dealing with.

There are already means of passing around bulk data with zero copy characteristics in python, but there's a lot of bureaucracy around it. A true solution must work with the GIL (or remove it altogether), no?