haha, all of a sudden I see a tab "waifu pillow" on Amazon, and think I have a split personality that runs searches in between consciousness shifts, and then I come back to a funny message.

I vibecoded a suitcase handle months ago with its Python interface. A pleasant experience.

Would like to hear more about how you did it. Did you connect it up to Claude Code?

Just asked for boxes, curved shapes, cylinders, cuts, mirroring, gave exact dimensions and it built up to ~400 lines of FreeCAD python.

3d printed handle was exactly how i wanted it to be

Your “what about plants” argument is such a worn-out trope that you must have seen it before and read a valid explanation of why it makes no sense.

Peter Singer has been writing on the topic for decades, including others. What-about-plants needs to fade away.

That's fair, but "what about animals" is to "we should not torture human brain organoids" as "what about plants" is to "we should not torture animals".

I am suffering substantially more psychic damage from being forced to watch videos of pig euthanasia at meathouses than any pig has ever suffered from being euthanized at one of those meathouses, because I have 10x the neurons as a pig and therefore e^10 more capacity for pain.

I had a similar feeling trying to calculate some combinatorial structures. At some point the LLM made a connection to extremal combinatorics and calculated tighter bounds and got me to the solution faster.

Felt flashbacks of playing chess against humans online as a teen by copying moves from a chess engine.

Whats the point haha

Libraries create boundaries, which are in most cases arbitrary, that then limit the way you can interact with code, creating more boilerplate to get what you want from a library.

Abstractions are the source of bloat. Without abstractions you can always reduce bloat, or you can reduce bloat in your glue, but you can't reduce glue.

It takes discipline to NOT create arbitrary function signatures and short-lived intermediate data structures or type definitions. This is the beginning of boilerplate.

So many advances in removing boilerplate are realizing your 5 function calls and 10 intermediate data structures or type definitions, essentially compute a thing that you can do with 0 function calls and 0 custom datatypes and less lines of code.

The abstraction hides how simple the thing you want is.

Problem is that all open source code looks like the bloat described above, so LLMs have no idea how to actually write code that is without boilerplate. The only place where I've seen it work is in shaders, which are usually written to avoid common pitfalls of abstraction.

LLMs are incapable of writing a big program in 1 function and 1 file, that does what you want. Splitting the program into functions or even multiple files, is a step you do after a lot of time, yet all open source looks nothing like that.

> Abstractions are the source of bloat. Without abstractions you can always reduce bloat, or you can reduce bloat in your glue, but you can't reduce glue.

I don’t think I agree. Here is an example.

QTcpSocket socket; socket.connectToHost(QHostAddress::LocalHost, 1234);

Vs:

int clientSocket = socket(AF_INET, SOCK_STREAM, 0);

    sockaddr_in serverAddr;
    serverAddr.sin_family = AF_INET;
    serverAddr.sin_port = htons(1234);
    inet_pton(AF_INET, "127.0.0.1", &serverAddr.sin_addr);

    connect(clientSocket, (sockaddr*)&serverAddr, sizeof(serverAddr))

Yep, people not understanding the value of abstraction is exactly why LLM coded apps are going to be a shit show. You could use them to come up with better abstractions, but most will not.

White colar work is just a lucky place to be, 99% of it is completely made up, there's people doing nothing, and people doing work of 10 people, does not matter, the work itself has no impact on anything.

A nice way to realize why this AI wave hasn't produced massive economy growth, it is mostly touching parts of economy which are parasitic and can't really create growth.

No. There is good signal in IMO gold medal performance.

These models actually learn distributed representations of nontrivial search algorithms.

A whole field of theorem provingaftwr decades of refinements couldn’t even win a medal yet 8B param models are doing it very well.

Attention mechanism, a bruteforce quadratic approach, combined with gradient descent is actually discovering very efficient distributed representations of algorithms. I don’t think they can even be extracted and made into an imperative program.

On reddit it's even worse, I feel like Reddit is internally having their own bots for engagement bait.

As someone who loves LaTeX, I can't imagine ever spending so much time on typography on online forums, italics, bold, emdashes, headers, sections. I quit reddit and will quit hn as well if situation worsens.

I have the sneaking suspicion that reddit has allowed and facilitated astroturfing for over a decade. As in, providing accounts, eliminating rate limits, artificially boosting posts and comments, and aggressively shadow banned contrary opinions. This is definitely a known phenomenon on a auto moderator level but I bet reddit ownership is complicit in it too

This behaviour is also openly acknowledged to have been used in early-Reddit growth hacking. So why not?

They were caught multiple times doing shady automated things. Most recently auto-translating posts and misleading search engine users with this. At this point there is no goodwill.

Funny how pydantic is used to parse and not validate but then there are post conditions after parsing which you should parse actually or which can be enforced with json schema and properly implemented constrained sampling on the LLM side.

Pipelines are often dynamic, how is this achieved?

Pipelines are just a description of computation, sometimes it makes sense to increase throughput, instead of low latency, by batching, is execution separate from the pipeline definition?