edenhyacinth

I wonder if this encouraged people to be more open with their ideas also.

If I could say things knowing that if I made a mistake, someone might friendly correct me with "Ah, you're the liar today, S3 doesn't support that format", I'd be happier to make them.

Pretty much! There's only three major fears remaining

* Co-pilot fails to detect it, and you have a potential lawsuit/ethical concern when someone finds out. Although the devil on my shoulder says that if Co-pilot didn't detect it, what's to say another tool will?

* Co-pilot reuses code in a way that still violates copyright, but is difficult to detect. I.e. If you checked via a syntax tree, you'd notice that the code was the same, but if you looked at it as raw text, you wouldn't.

* Purely ethical - is it right to take licensed code and condense it into a product, without having to take into account the wishes of the original creators? It might be treated as normal that other coders will read it, and pick up on it, but when these licenses were written no one saw products like this coming about. They never assumed that a single person could read all their code, memorise it, and quote it near-verbatim on command.

We have seen Co-Pilot directly output (https://docs.github.com/en/github/copilot/research-recitatio...) the zen of python when prompted - there's no reason it wouldn't write the Psalms exactly when prompted in the right manner.

A machine learning isn't really the same as a person learning - people generally can code at a high level without having first read TBs of code, nor can you reasonably expect a person to have memorised GPL code to reproduce it on demand.

What you can expect a person to do is understand the principles behind that GPL code, and write something along the same lines. GitHub Co-Pilot is not a general ai, and it's not touted as one, so we shouldn't be considering whether it really knows code principles, only that it can reliably output code that fits a similar function to what came before, which could reasonably include entire blocks of GPL code.

Massive fan of Convivial Society, although I think some pieces necessarily won't give the full background of Illich's belief that technological progress is not necessarily a good thing, and should be examined.

I feel that archery is much the same way to me as baseball is discussed here - I enjoy shooting a recurve bow without sights or counterweights or additions. I could improve my shooting drastically in all common metrics if I wanted to swap to a modern bow, I'd be more accurate, using more force, at a greater distance.

But as none of those metrics measure how satisfied I feel after shooting, it doesn't matter to me and I won't swap.

>Google Analytics is free, although it is not. Google Analytics makes money off the personal data they collect from their customers.

This isn't strictly true though. Google Analytics has a free and a paid tier with GA360, which is for larger businesses.

More to the point, half of these aren't suitable for marketing decisions when you have multiple paid entrypoints to your site. The major, but simple, ones for marketing;

* Channel Groups - being able to merge multiple UTM tags or referrers into a single channel for comparison

* User Retention - even privacy first, it's important that you can track user activity onsite via a logged-in user ID.

* Bot Removal & IP removal - Excluding an office from the GA stats is important to track actual users compared to your colleagues checking in on details.

* Channel comparison for conversion rate - i.e. Google Ads vs FB Ads.

Fathom seems like the top one from this, but it still doesn't have any of these features. It has self removal via the console, but that's not quite the same. The dashboard Pirsch shows doesn't show any of these features, and most of them seem to have filters, but no general comparison windows. Same for Umami.

I agree - I definitely think that how we treat deer in the UK as a food source and as a wild population is a sensible way of 'farming' animals.

My only concern is with domesticated stock. Cows couldn't possibly survive in nature, and would suffer greatly, for example. If we're concerned with raising animals for food that also live enriched lives, do we also have an obligation to breed them in ways that enrich them?

The article presents the case that writing code with a specific style - OOP compared to Data Oriented - is responsible for slowing down performance. That code architecture is primarily the cause, regardless of the actual implementation, because some architectures will never work well with the compiler.

I get that like the major parts of picking algorithms that are N over N^2 is always going to be more important, but it doesn't seem like the article is disagreeing with you at all, just another area where people need to consider their decisions.

That argument assumes women aren't interested in those roles, and that their disinterest is the only or primary thing that causes an imbalance.

You have to know that isn't true, which makes this a great example of why people are frustrated about discussing anything 'political' in the workplace.

The intention was to show that there is another party involved in the content, even if you intend on the content being private and unpublished.

That party can say that they don't want to be involved with content, regardless of its type.

If I were an editor, and someone passed me their amatuerish version of Lolita to edit through, I'd be well within my rights to say that I didn't want to be involved in it.

More broadly, the editing company I worked for could say - even if you don't intend on releasing this and even if our individual editors don't mind reviewing it - we don't want to have to edit it, and we don't want to be associated with it.

This is no different, but at scale. AI Dungeon, due to their agreement with OpenAI, don't want to have to work with this content. They've found a pretty awful way of implementing it to save the relationship with OpenAI, and hopefully they'll find a better one in the future.

"Your honour, I think you'll find that someone broke into my house and planted drugs"

This type of logic has been used plenty in court, it being in your possession, digital or not, is sufficient.

The claim here is that due to the vulnerabilities Cellebrite has, the offending item may never have been on your device. This is more similar to saying that the images the police took in your house of drugs were kept on an unsecured server, there are recorded vulnerabilities for it, and therefore the images could have been digitally edited to show drugs where none were present.

I think what you're missing is that Signal does not need to place any files on any phones for their purpose, and likely will not ever do so.

Their intention is to render using Cellebrite for court evidence worthless by suggesting that the record could have been tampered with at any point, if any phone the user scanned had Signal on it.

Proving that no phones ever had an 'aesthetic' file that could cause damage to Cellebrite is impossible, and they've provided clear reason why it is impossible to prove.

Given that it's via pyO3, you could even pass the numpy arrays using https://github.com/PyO3/rust-numpy and get ndarrays at the other side.

Same no copy, slightly more user friendly approach.

Further criticism of the actual approach - even if we didn't do zero copy, there's no preallocation for the vector despite the size being known upfront, and nested vectors are very slow by default.

So you could speed up the entire thing by passing it to ndarray, and then running a single call to sum over the 2D array you'd find at the other end. (https://docs.rs/ndarray/0.15.1/ndarray/struct.ArrayBase.html...)

It's more the latter, if you read the rest of the thread you'll get a feel for the issue - there's no broad consensus on what Python should do for package management.

Flit is not an unreasonable pick, but it's not a silver bullet.

The left-pad situation wasn't simply that lots of projects were relying on left-pad directly, it was that they were relying on projects that were relying on projects that were relying on left-pad.

Some dependencies are too large to rewrite yourself - most statistical suites would fall under this definition - and while accepting their direct code might be acceptable, it's not usually feasible to fork their code and rewrite the parts that aren't. Lots of smaller parts you could write yourself quickly add up.

The judgment alleges that indicating that you believe a company to be a scam - insofar as providing an unsatisfactory service for payment could be considered a scam - is on par with accusing someone of urinating on war memorials.

It even says that couching the statement in an opinion "To me it was a scam" wouldn't be sufficient to avoid this. Would it all have been saved if he'd said "It was like a scam"?

It also says that the claimaint's belief that "after a single review went up, we saw a drop in inquiries" (para) is sufficient for £25,000 of damages! That has to be considered outrageous, surely?

I have! Used FastAPI as a frontend to do some minor data modification, and passed the data for model inference in Rust.

Works really nicely, although given how little work I'm doing in the Python side I honestly prefer using Rocket instead of FastAPI and then using pyo3 to call the Python library in Rust, rather than the other way around.

Been using Maturin for a little while professionally, and it's surprisingly good. There's a few bugbears here and there - I haven't found a way to have Cargo Test & a pyo3 library working at the same time - but overall it's a lot more pleasant than working with Rust and R was.

I believe they're saying that if you were to do that bootcamp for 4 years it would work out to ~1M, i.e. ridiculously more than any college.

I think it'd be 876,000 (36.5K * 6 * 4), but that's beside the point.