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Your point is terribly weak unless you cite the article in question. The hallmark of an edit war is two editors who are each absolutely convinced that they are editing in good faith while the other has an ideological axe to grind.

I understand this is a confusing time, and we all feel vulnerable to being duped. But please be a bit more circumspect with these confident accusations, because they can be genuinely hurtful. You are factually wrong here: I don't use LLMs to write or revise personal content.

This advice is too coarse. I believe LLMs have made me a better writer of technical reports. I have a keen ear for language, and I can usually tell when a sentence or a paragraph is orbiting around a point rather than landing on it firmly. Some writers insist that unclear prose is dispositive proof of unclear ideas -- a sign the writer has not thought things through. My experience is different: I often have a clear idea in mind that I cannot quite find the right idiom to express. Sometimes I can find it if I keep revising, but staring at a sentence too long can entangle you in a particular linguistic frame that can be hard to escape.

LLMs are helpful because their idiom-list is vast and they are indefatigable and infinitely patient. You can keep iterating on a sentence and it will keep giving you fresh takes. Eventually, whether through careful steering or brute-force iteration, it will come up with something that has the right resonance. Like a word on the tip of your tongue, you recognize it when you hear it.

For me, the end result of this writing-process is often a document where much of the language first came from the agent, but the voice is recognizably mine, and I feel a clear sense of authorship. It is still my work because of the microscopic attention I paid to every word. The marble is the agent's, but the chisel and mallet are in my hands.

If you have an Intel CPU, there is a good chance you have a KVM built-in (whether you wanted one or not): Intel AMT. Its reputation was tarnished by Intel's dissimulation and opacity about the technology, and a streak of critical vulnerabilities disclosed in late 2017. I chose to take my chances with it anyway for my homelab server. It is secured with a password, mutual TLS (client has to provide a cert), and restricted to the LAN via a physical firewall. It gives me serial console, KVM, and power control.

I like it. It works pretty well. I don't see a reason to trust it any less than closed-hardware, closed-source solutions. I would trust a fully-open-source PIKVM more, however.

The tooling and documentation for setting up Intel AMT via open-source tools is meagre, so I had to roll my own. I only need a small nudge to package it for others to re-use, so reply to this post if you are interested.

We don't know exactly what Google's leadership was thinking, nor how the AI race will shape up in the coming months and years. Calling it a "failure" seems presumptuous and premature. But supposing your read is correct: what made this outcome predictable, in your view?

How do you avoid being the Xerox to the Microsofts and Apples of AI?

The money contributed to the Rust Foundation by large corporate members supports initiatives[0] that benefit all users of Rust, and I am happy for it. The slow and deliberative approach the Foundation took to crafting the AI policy, and even the hedging language in the policy itself, are indicators of a healthy open organization. The author's scorn shows immaturity.

  [0]: https://rustfoundation.org/#initiatives

Excellent write-up!

Is the magic a property of the broader language-family (and could be experienced with Janet, Racket, whatever), or Common Lisp specifically? When people praise the core execution environment they're typically praising Common Lisp specifically.

What's the quintessential "now I get it" experience, in your mind?

What exactly would you have done differently?

Cargo made its debut in 2014, a year before the infamous left-pad incident, and three years before the first large-scale malicious typosquatting attacks hit PyPI and NPM. The risks were not as well-understood then as they are today. And even today it is very far from being a solved problem.