Tired of this trope. Learning data structures and algorithms is not about memorizing the specifics of some particular algorithm. That’s like thinking that learning math is about memorizing formulas.

DS&A is about learning *algorithmic thinking" and how common data structures actually work, so you can begin to build a toolbox of things you can use when making your own data structures. Software engineers that are actually good know this shit backwards and forwards, because it does actually come up all over the place (and these are the kind of people that actually write libraries). Even the basic things you learn in school are actually incredibly useful for understanding the implementation details of databases and how query planners and indexes work, for example (very helpful when trying to understand query performance).

And don’t get me started on just how fucking much directed acyclic graphs come up in the real world. Git? DAG. Any package manager? DAGs. Nix? DAGs. Open Telemetry? DAGs (the main data structure is a tree which is a special case of DAGs, but if you use linked spans, it would form a DAG). Hell, I’m working on something right now that needs to be modeled as a DAG. It’s almost comical how useful they are.

We should be encouraging people to learn and grow more, not less.

It’s not, they are correct. There are so many telltale signs of AI code it’s not even funny. The most obvious being the absolutely garbage comments that people invariably leave in. And the god awful naming of things.

But it’s more than that. If you’re in this industry long enough, you get pretty good at reconstructing a real author’s thought process when they wrote the code. Part of understanding code is understanding why it was written the way that it was, which means understanding how the author thought. Sure, there was plenty of garbage code and stupid thinking, but it was still thought and usually had its own kind of internal consistency. AI code has no thought process, no reason. It is pure mimicry, an amalgamation of millions of authors all at once. It has no internal consistency. It produces code no human ever would, because it doesn’t make any fucking sense. It’s like reading an alien language, where the constructs it produces are so aberrant to how any human would ever think that it could be nothing but an LLM.

I definitely can’t tell you everything about a piece of code by reading it, but I sure as hell can smell an LLM in it, because it fucking stinks.

I work remote, so no.

Hmm, every company monitors their web traffic. That’s standard operating procedure.

Slop commenting. The litany of AI slop websites that have popped up, polluting search results. The absolute flood of AI slop pull requests being submitted to open source projects, to the point at which many open source maintainers are buckling under the weight of garbage being thrown their way. Bots everywhere. The list goes on and on and on.

The internet is already a dessicated husk of what it once was.

I’m saying that AI companies have repeatedly shown a flagrant disregard for licenses, contracts, and the law, and have engaged in massive theft. Why should we expect that any contract would actually be honored? The whole thing is a huge fucking grift.

I was not talking about your specific lawsuit, or TLS.

Companies trust other companies all the time, and it’s foundational to most all SLA/SLOs. Any time I’ve voiced concerns around how AI companies are using the data we are giving them (like giving them access to our codebase), it’s brushed off as “we have an agreement with them”. It’s just a load of hogwash. They can and will abuse all data they have access to, just as they have done thus far.

In this particular case, we are talking about a data center, and it is not at all reasonable to assume that the data that flows to said data center is in any way protected, especially one run by Musk.

Still means jack shit. Companies will lie through their teeth and violate any and all they can get away with.

They are not to be trusted.

I do use quite a bit, but I also do a lot of different things. Compiling code, running docker containers, local web servers, an android emulator, slack, browser tabs for Jira/confluence/figma/etc., all adds up pretty quick.

8GB is definitely nowhere near enough, at least for what I need to do.

What the actual fuck, Guardian.

Did the headline change? The current headline is Torvalds: “100% of Their Code is Written by Compilers” Too

The title of this post makes for a dumb headline, at any rate. Linus, in response to claims in the industry that projects are now “99% written by AI”, drew an analogy to compilers by saying that all machine code for projects are written by compilers, yet no one says their project was 100% written by a compiler. It’s just talking about stupid hype, which is valid.

That being said, it’s still quite unfortunate that Linus has fallen into the trap of LLMs.

This is what happens when you don’t take a stand against this shit. He brought it on himself.

Yes. They are con artists with a proven track record of lying and stealing. We shouldn’t take anything they say seriously, especially when the reporting reads much more like marketing rather than an incident report.

Fave: vim First: vim Future: vim Honorable mention: vim Loathed: anything other than vim Current: vim Longest: believe it or not, vim

It’s not getting POSIX compliance done, that’s for sure. Or compatibility with normal scripts.

It’s not that far from the truth, it’s just the thing they pick is what they saw on Fox News that morning.

How is this a response to a comment about AGI?

LLMs are not currently, nor ever will be, anything remotely resembling AGI. AGI is still entirely within the realm of science fiction, like teleportation or time travel.

It doesn’t need nearly as many. AI inference is orders of magnitude more expensive than a single search query (ignoring the fact that Google does it’s own inference with search queries now). And that doesn’t even include training, which is stupidly expensive to do.

That’s not lying. There’s nothing linguistic about numerical computation.