atdt

Her reporting is superb and you should follow her: https://www.citationneeded.news/.

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.

Your trust score on ScamAdvisor is 26/100 ("likely unsafe"); https://www.scam-detector.com/ gives you a trust score of 38.6 ("questionable").

I am not implying that your start-up is a scam, nor that Google is acting on these trust scores. What I am pointing out is that to an algorithmic assessment of trustworthiness, your website looks a little sketchy: hardly anyone links to you; your domain is less than a year old; your whois info is anonymized; the text content is LLM-generated[1]; and the specific niche you're in (people finding services) is rife with scams. If I ran my own search engine, I don't think I'd include you.

  [1]: https://www.pangram.com/history/65314d99-8205-4613-b9bd-a069d5717920?ucc=Yqx88GTmJnK

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.

Uploaded here: https://github.com/atdt/amt-tools

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

You're incorrect. The letter ו (vav) is pronounced /v/ in modern Hebrew but /w/ in Biblical Hebrew and other ancient Semitic languages, which is why the letter is referred to as Waw and transliterated as 'W'.

https://www.biblexika.com/bible-lexicon/navah-h5115

https://hebrew-academy.org.il/%D7%93%D7%A3-%D7%9E%D7%99%D7%9...

https://biblehub.com/hebrew/5116.htm

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.

Please share this with someone who doesn't know the story yet. Ingenuity alone can't save our species. We also need the will to do good. We are living through a moment of deep cynicism about our ability to solve existential problems. Let this be a reminder of what we are capable of.

Having worked with both kinds, I have generally preferred three-dimensional human beings to cut-outs from a compliance training manual. Being fundamentally kind and collaborative is prerequisite, of course. But so is having a modicum of spite, misanthropy, pettiness, irony, and dark humor. An appreciation for the tragic sense of life. How do you get through the day if all you get from your coworkers are patriotic slogans?

Flame graphs have an official web site, maintained by Brendan Gregg, who invented them: https://www.brendangregg.com/flamegraphs.html. It's a useful starting point.

My hunch is that the same is true of Wikipedia's choice of Lua for template scripting, made back in 2012.

https://lists.wikimedia.org/hyperkitty/list/wikitech-l@lists...

> you might not understand what the problem is for working and middle class people quickly finding themselves surrounded by a sea of people with dramatically different cultures, values, and religions

Of course. That is why Trump received the highest voter support in counties with the lowest levels of immigration.

https://latino.ucla.edu/press/report-finds-white-voters-supp...

I am interested in this topic, but this textbook is too daunting for me. What I'd love is a crash course on Bayesian methods for the working systems performance engineer. If you, dear reader, happen to be familiar with both domains: what would you include in such a course, and can you recommend any existing resources for self-study?

It has access to the current page, so you can ask Gemini questions about its content.

Your content is great, and the participation of non-native English speakers in this community makes it better and richer.

The level of intellectual engagement with Chomsky's ideas in the comments here is shockingly low. Surely, we are capable of holding these two thoughts: one, that the facility of LLMs is fantastic and useful, and two, that the major breakthroughs of AI this decade have not, at least so far, substantially deepened our understanding of our own intelligence and its constitution.

That may change, particularly if the intelligence of LLMs proves to be analogous to our own in some deep way—a point that is still very much undecided. However, if the similarities are there, so is the potential for knowledge. We have a complete mechanical understanding of LLMs and can pry apart their structure, which we cannot yet do with the brain. And some of the smartest people in the world are engaged in making LLMs smaller and more efficient; it seems possible that the push for miniaturization will rediscover some tricks also discovered by the blind watchmaker. But these things are not a given.

OK, I will be the useful idiot. I don't fully understand your anecdote. Could you explain what is exactly it that you perceived and that the other engineer failed to see?

For someone new to time series analysis, how did you choose these particular algorithms? Are they standard in the field, or more of a personal selection?

What is it about Zed that you find superior to VS Code?

I am starting to understand why these luminaries warn us about a future that is dominated by a solitary superintelligence, self-obsessed and uninterested in humanity.

POCSAG is an ideal for broadcasting low-sensitivity push notifications, like "report to your local commanding officer by 15:00 today". These messages don't need encryption, just a reliable way to reach militants without revealing their location.

Armin advocates for 'uv' to dominate the space, but acknowledges it could be rug-pulled due to its VC backing. His solution to this potential issue is that it's "very forkable." But doesn't forking inherently lead to further fragmentation, the very problem he wants to solve?

Any tool hoping to dominate the Python packaging landscape must be community-driven and community-controlled, IMO.

This brings to mind Chernoff faces[1], a type of visualization where facial features are mapped to data points.

  [1]: https://en.wikipedia.org/wiki/Chernoff_face

When using Jpegli as a drop-in replacement for for libjpeg-turbo (i.e., with the same input bit-map and quality setting), will the output produced by Jpegli be smaller, more beautiful, or both? Are the space savings the result of the Jpegli encoder being able to generate comparable or better-looking images at lower quality settings? I'd like to understand whether capitalizing on the space efficiency requires any modification the caller code.