maintaining a fork on the zig version works short term but does open some questions about longterm stability/approach and if features should be cut to make maintenance easier; ie Bun.Image, fetch("", {grpc: true}), Bun.redis since it never got finished, etc
Give them a break. Why doesn't the OP just help develop a highly efficient SwiftUI extension for Markdown if it's that important? Remember that there are many efficient MD libraries for Swift/ObjC which would in any case be the sensible approach here (and it also explains why he can't find a SwiftUI alternative to his liking).
He is hurrying, but his $1.7 Billion militia and ICE will soon be fighting behind an El Cid propped up rider. It looks like he has had repeated strokes. Not the golf kind.
But fight they will because he will fully become a chatbot. FIRST DECEASED LEADER.
The Hallucinating ChatGPT Presidency[0]
Tue, Apr 29th 2025 09:34am - Mike Masnick
> We generally understand how LLM hallucinations work. An AI model tries to generate what seems like a plausible response to whatever you ask it, drawing on its training data to construct something that sounds right. The actual truth of the response is, at best, a secondary consideration.
> But over the last few months, it has occurred to me that, for all the hype about generative AI systems “hallucinating,” we pay much less attention to the fact that the current President does the same thing, nearly every day. The more you look at the way Donald Trump spews utter nonsense answers to questions, the more you begin to recognize a clear pattern — he answers questions in a manner quite similar to early versions of ChatGPT. The facts don’t matter, the language choices are a mess, but they are all designed to present a plausible-sounding answer to the question, based on no actual knowledge, nor any concern for whether or not the underlying facts are accurate.
> This is not the response of someone working from actual knowledge or policy understanding. Instead, it’s precisely how an LLM operates: taking a prompt (the question about job losses) and generating text based on some core parameters (the “system prompt” that requires deflecting blame and asserting greatness).
> The hallmarks of AI generation are all here
• Confident assertions without factual backing
• Meandering diversions that maintain loose semantic connection to the topic
• Pattern-matching to previous responses (“ripped off,” “billions of dollars”)
• Optimization for what sounds good rather than what’s true
In a way it's worse because at least with int you're not really expecting to run the same binary on architectures with different int lengths, and also for several decades there have only been two realistic options (32 or 64), which makes it easy to deal with.
With RVV (and SVE I assume) there are a wider range of realistic options - at least 128, 256 and 512. The RVV spec allows up to 65536! Also it's totally reasonable to want a single binary to work with all of them so then you're into compiling parts of your code multiple times with runtime dispatch which is a right pain.
I haven't looked into how Highway does it but I don't really know you you write length-agnostic code in high level languages. It's easy in assembly, but it sucks if you have to do it in assembly.
I've only looked into one device en detail, the Jolla.
Okay, no touch typing, maps apps don't start or don't find your location, WhatsApp probably doesn't work and I guess I don't have to start with banking apps.
reply