Ah, yes, that pesky FCC for regulating a public shared frequency spectrum. Im sure everybody will just behave in a vacuum of rules and wouldnt possibly do anything bad.
No, but "free as in speech" effectively precludes making money from sales of the software. As soon as you sell it to one person, that person can give it to others for less than he paid you (all the way down to free), so nobody has a reason to pay you any more. There's a reason FOSS survives on donations or service, rather than selling copies of the software.
The only llmism I sensed is the use of "load bearing". Im usually queasy after reading llm slop, and stop before the end. This didn't have that effect.
Maybe the llms are getting better, but either way, this article reads like a real hunan write the whole thing.
Humans don't write things like: "Now, the popular way to tell this story is "the system is breaking," and I don't think that's right, and the distinction matters."
This statement just makes me think of a line from The Diamond Age in which two kids in a post-nanotech future first see a scrap of hand-woven cloth and after thinking decide that it must have been made by nanomachines because no human could make something so regular.
Id say that it is a lot more likely for the in-house, at least half a decade old library to be correct and performant than 3000 lines of an LLMs mediocre regurgitation of that code.
I think software engineering in general is in a bit of a discoverability crisis. So many problems actually have solutions implemented... Somewhere. If you know about them. And are speaking the same vocabulary as the original implementer to realize the solution might be applicable to your problem. It's one of the reasons that jokes exist about microservice frameworks (https://www.youtube.com/watch?v=y8OnoxKotPQ) and how "We use Hadoop to store the output from our Kafka pipe, that's populated from our Traefik layer, all monitored with Grafana in front of Loki and Prometheus, of course" is a real sentence that has actual meaning and not a fever-dream.
LLMs are actually pretty impressive at being able to pull together disparate information from various domains into one place.
I'm not sure I follow. C++ just added a SIMD library for this exact problem. And even then, SIMD-intrinsic-free C++ with the right data structures and some basic hardware understanding gets you mostly there in a hardware agnostic portable way.
They've added a new library to a language and stdlib so crammed full of features that its specification exceeds the size of the King James Bible by wordcount.
That's what I mean about "discoverability crisis." This post is how I learned about the existence of the SIMD library.
I'd absolutely still use Highway, and do. My experience is that even two separate implementations diverge over time and I'd have low confidence in bringing the same updates and improvements to all, even with LLM assistance.
Our programming model is 1) an agent+human to generate the algorithmic approach, 2) a C++ library (Highway) to translate to intrinsics, while filling in gaps + allowing customization, 3) a compiler to generate the actual code with some optimizations.
Asking the compiler to do #1 is a pipe dream: compiler friends tell me they are not going to devise new shuffles/data layouts (like what VQSort does). Conflating #2 and #3 means a custom compiler/IR which has high engineering costs (ABI boundaries, hard to debug/profile/sanitize).
And doing #3 at runtime (JIT), or moving fusions into #3 (MLIR), vastly complicates the compiler. We can still get runtime adaptability thanks to Highway's multi-target support. Fusion has been much easier to implement manually for LLMs than to construct a general fusion infrastructure. Templates hide most data type differences and we see 2-5x speedup vs llama.cpp for 128k prefill+batch decode on Zen5.
Instead of requiring a compiler to do heroic transforms at runtime, and get it right every time, we can do all kinds of agentic exploration, then verify the result/approach, check in the source code, then we 'just' have a C++ compiler afterwards. And if/when something breaks, it's easy to update centrally, in code we can modify directly, rather than indirectly via updating a compiler.
Nothing absurd about that. What do you think an "Executive producer" is? A "Director" ? Does Peter Jackson get credit for creating the Lord of the Rings Trilogy films? Christopher Nolan for his films? But did he make them ? No, it was the collective effort of thousands of individuals all working under their direction.
Just like if somebody creates software today, and the end result is generated by the collective effort of thousands of agents, the "Director" still gets credit.
What does it matter who receives more credit? The producer produces the film and the director directs it. If I pick my phone and record a video, I'm now the producer and director of the film and the sole creator of it.
If there were multiple people involved in the creation of a film I helped to create, I cannot factually say I created it. Just like if someone builds something using code generated by AI, they can't factually say they created it.
There's a bit more nuance to it though, I think, because traditionally there has been more of a firm line between humans and tools.
For example, most people would agree with this line you wrote: "If I pick my phone and record a video, I'm now the producer and director of the film and the sole creator of it." A pedant could say "woah hang on, that's ignoring the fact that actually the iPhone is the one recording the images that make up the film, how can the human get all the credit", yet nobody would actually make that argument when discussing who created the film.
Generative AI is pretty much the first time (maybe there are some niche contradictions to this claim?) we consider a tool to be contributing enough creativity to the process that we don't all agree "only one person was operating this tool, so that person is the sole creator" - but some people DO still hold that line, and do consider the human who wrote the prompt to be the creator.
And I don't think there's any objective technical metric we can use to say who's right, it comes down to our collective judgement deciding where the line is.
That’s an interesting way to look at it, and still generous to the llm.
By which I mean it puts the llm in the role of actor and such… people practicing an art. It seems harder to make a case that the llm is actually making creative decisions rather than aping a synthesis of past human decisions and expressions of taste, strictly, at every turn.
Though I guess it’s all “shades of grey”. I never felt like I was contributing a ton when I was essentially wrapping a large, capable library that some smarter person or people made, either.
Tangentially… remember back when we used to see headlines like “12 year old made a web browser!” and we all thought, “No. No they didn’t.”
Its a nightmare because it erodes trust. Doctors are not "always right" which is why "always get a second opinion" is codified in culture.
But AI's problem is that its completely full of shit, sometimes, and the people most qualified to evaluate whether its full of shit are the doctors, not the patients, but just like OP's original article, patients are left feeling like their second opinion from AI might be more trustworthy than their doctors opinion.
> But AI's problem is that its completely full of shit, sometimes
It's now quite unusual that it's "Completely full of shit". If it contradicts something your doctor said I don't see why you should feel ashamed to bring it up.
Sure it complicates the doctor's work, having ignorant obedient patients must be more comfortable for the doctor, but the end result could be more accurate diagnosis.
But those are obvious errors. What if the AI tells you to up your intake of X and it seems plausible? So you up your intake of X by taking some supplement, but upping the intake of X makes your body deplete more of Y and now you have a new or compounding problem.
A doctor might have never recommended upping X, because they would know what it does to your body. Or they might have suggested additional supplementation to avoid this.
The fact that LLMs are trained on all public knowledge is a huge red flag, because there are more wrong infos out there than right ones. Especially about health, diet, etc.
I was about to respond but your last statement implies fundamental misunderstanding of how LLMs work. I don’t think you even know about RLHF and you think good and bad ideas are spread in proportion to how much they are seen on the internet.
