And as things fell apart / Nobody paid much attention

Some implementations seem vectorization-friendly like the C one that uses a bit-twiddling trick to avoid the `x = -x` line that the Odin implementation and others have.

When you put these programs into Godbolt to see what's going on with them, so much of the code is just the I/O part that it's annoying to analyze

He explicitly endorsed JD Vance in a past stream. Buying his games directly fuels authoritarianism.

Unless you feed a spec to the LLM, and it nitpicks compiled TLA+ output generated by your PlusCal input, gaslights you into saying the code you just ran and pasted the output of is invalid, then generates invalid TLA+ output in response. Which is exactly what happened when I tried coding with Gemini via formal verification.

This looks very similar to the SDL3 GPU API and other RHI libraries that have been created at first glance.

If you look at the details you can clearly see SDL3_GPU is wildly different from this proposal, such as:

- It's not exposing raw GPU addresses, SDL3_GPU has buffer objects instead. Also you're much more limited with how you use buffers in SDL3 (ex. no coherent buffers, you're forced to use a transfer buffer if you want to do a CPU -> GPU upload)

- in SDL3_GPU synchronization is done automatically, without the user specifying barriers (helped by a technique called cycling: https://moonside.games/posts/sdl-gpu-concepts-cycling/),

- More modern features such as mesh shading are not exposed in SDL3_GPU, and keeps the traditional rendering pipeline as the main way to draw stuff. Also, bindless is a first class citizen in Aaltonen's proposal (and the main reason for the simplification of the API), while SDL3_GPU doesn't support it at all and instead opts for a traditional descriptor binding system.

SDL3 is kind of the intersection of features found in DX12/Vulkan 1.0/Metal: if it's not easily supported in all of them, it's not in SDL3-- hence the lack of bindless support. That means you can run on nearly every device in the last 10-15 years.

This "no api" proposal requires hardware from the last 5-10 years :)

Yup you've actually pointed out the most important difference: SDL3 is designed to be compatible with the APIs and devices of the past (2010s), whereas this proposal is designed to be compatible with the newer 2020s batch of consumer devices.

Can't imagine a worse angle for regaining trust than doubling down on AI slop.

UUIDs make enumeration attacks harder and also prevent situations where seeing a high valid ID value lets you estimate how much money a private company is earning if they charge based on the object the ID is associated with. If you can sample enough object ID values and see when the IDs were created, you could reverse engineer their ARR chart and see whether they're growing or not which many companies want to avoid.

Ah, yes. If the thing that is false is true, all kinds of interesting things happen! For example, if I became the queen of France, I could make people do silly dances! That is an interesting hypothesis that could play out in my imaginary world!

SaaS maintenance isn't about upgrading packages, it's about accountability and a point of contact when something breaks along with SLAs and contractual obligations. It isn't because building a kanban board app is hard. Someone else deals with provisioning, alerts, compliance, etc. and they are a real human who cannot hallucinate that the issue has been fixed when it hasn't. Depending on the contract and how it is breached, you can potentially take them to court and sue them to recover money lost as a result of their malpractice. None of that applies to a neural network that misreads the alert, does something completely wrong, then concludes the issue is fixed the way the latest models constantly do when I use them.

This looks AI-generated, including the linked code. That explains why the .zig-cache directory and the binary is checked into Git, why there's redundant commenting, and why the README has that bold, bullet point and headers style that is typical of AI.

If you can't be bothered to write it, I can't be bothered to read it.

The front page this weekend has been full of this stuff. If there’s a hint of clickbait about the title, it’s almost a forgone conclusion you’ll see all the other LLM tics, too.

These do not make the writing better! They obscure whatever the insight is behind LinkedIn-engagement tricks and turns of phrase that obfuscate rather than clarify.

I’ll keep flagging and see if the community ends up agreeing with me, but this is making more and more of my hn experience disappointing instead of delightful.

By making up numbers and not supplying any evidence, you can come to any conclusion you like! Then you get to draw a graph with no units on it. Finally, you can say things that are objectively false like "These assertions are rapidly becoming completely false".