You can make it lowercase and replace the em-dashes with hyphens, but we can still tell. That said, interesting article. I look forward to reading the PLDI when it comes out. Eliminating an O(n^2) in a primitive as important as regex is extremely valuable, so this is impressive work and clearly wasn't easy
I'm of the opinion that their post is still human-written. They describe in their first blog post that it's human written (which could be a lie, but oh well) and their other blog posts seem to have the same informal lowercase hyphenated writing style. Sentance length varies throughout the posts. Sure, you could prompt this writing style, but I lean towards thinking that the piece is human written.
The fact that terms like Aho-Corasick, PLDI, Go, etc. are properly capitalized, including if they begin sentences, but otherwise sentences are uncapitalized, makes me think it's an explicit LLM instruction "don't capitalize the start of sentences" rather than writing style.
ChatGPT also loves Aho-Corasick and seems to overuse it as an optimization fall back idea. ChatGPT has suggested the algorithm to me but the code ended up slowing down a lot.
No, this is just what that writing style looks like. Names and acronyms are usually capitalized normally.
I keep being surprised by the magnitude of the disconnect between this place and the other circles of hell. I'd have thought the Venn diagram would have a lot more overlap.
I also have the impression that the writing was at least "enhanced" with an LLM. For example, the amount of " - " dashes (over 60) is much higher than in a normal text.
These are some multilingual dictionaries^[1] I made. They're designed to be useful to language learners. They have some cool features I haven't seen elsewhere.
1. you can see the frequency of each meaning of each word. For example, the french word "bois" commonly means "drink" and rarely means "wood": https://yap.town/d/french-to-english/bois/
2. Each meaning also comes with a huge number of example sentences, taken from "real" sources (movies mostly)
3. It also has definitions for common phrases and constructions. For example, "c'est" is technically two words in french, but you should just learn it as one unit, so it gets its own entry: https://yap.town/d/french-to-english/c-est/
You can also see a list of phrases for any language of interest: https://yap.town/d/french-to-english/top-1000-phrases/ . The phrases were discovered via the "unigram" tokenization algorithm (originally invented for training LLMs!)
Something remarkable about the phrases is that you can often understand the meaning of a sentence just from the meaning of each phrase in it. The concatenated phrases sometimes even form grammatical english. And of course, if the same phrase has multiple meanings, those are separated and have their own example sentences, just like the words do.
^[1]: And by "I", I mean I wrote code to ask an LLM to generate each dictionary entry.
Does the article you cited cost money to read? I found a description on google scholar:
> Ten years left to redesign lithium-ion batteries
> Reserves of cobalt and nickel used in electric-vehicle cells will not meet future demand. Refocus research to find new electrodes based on common elements such as iron and silicon, urge Kostiantyn Turcheniuk and colleagues.
I notice that the article was published in 2018. So I guess we only have to wait two more years to decide if it's right or not. Will we be out of cobalt and nickel by then? I'd be happy to take a bet with you, assuming you stand by the article you cited.
> If you want this to work across ARM and x86 (or even multiple ARM vendors), you are screwed, and need to restrict yourself to using only the basic arithmetic operations and reimplement everything else yourself.
Is this problematic for WASM implementations? The WASM spec requires IEEE 754-2019 compliance with the exception of NaN bits. I guess that could be problematic if you're branching on NaN bits, or serializing, but ideally your code is mostly correct and you don't end up serializing NaN anyway.
They make more than they would in Japan. But people can make $0 in any country. Regardless, part-time Walmart greeters are fortunately not paying full price for health insurance in the US.
I'm curious what you're implying. Is there a country where the poorest person is so rich they can get all the insurance and care they require without government subsidy?
It interacts badly with insurance being offered as workplace benefit. If you quit or lose your job, you'd lose your health insurance. And any plan you signed up for after that would then treat you as "pre-existing embers" and expect you to pay accordingly. The bundling of health insurance with workplace seems like the healthcare original sin to me.
Obama couldn't change that, so the ACA redesigned the system to work with it. Despite being called insurance, health insurance is no longer really viewed or designed to be any kind of insurance. Instead, it's supposed to be Netflix for healthcare. You pay a flat rate, and then get unlimited healthcare. Obviously, the issue with this is that if you don't need healthcare you can just not sign up for the subscription. So the ACA tried to solve this by requiring everyone to sign up. Once everyone is required to sign up, it's not right to discriminate against preexisting conditions. It may not be an especially good system, but it is coherent.
The US is allergic to taxes. Maybe it's a marketing thing. Benefits paid for by society.
Maybe a department of Return on Investment. See what those taxes pay for. Contrast to buying private versions of the services at the same SLA or better.
It’s more that the US is more like a collection of 50 little countries, and it’s supposed to be hard to accomplish much at a federal level. That separation has eroded a bit in the last 50 years but it’s still very much a part of our political ideology.
> I haven't seen a single "AI evangelist" address any concerns and limitations
You see what you choose to focus on. I come across many people who are excited about the possibilities of AI-assisted coding, who are frustrated by its limitations, who share strategies for overcoming or avoiding those limitations, and s on. For a concrete and famous example, I would put Andrej Karpathy in this category. Where are you looking that you're not finding any of these people? linkedin?
In my experience the people who are excited about ai assisted coding are people who aren't good at coding in the first place and don't care about quality, consistency, or understanding what they are having it write, and people who have a vested interest in ai coding tools being used (leadership who want to say "my team uses ai" and "ai experts" who have a personal brand dependent on ai being successful)
AI assisted coding is really good as an enhanced auto-complete, often better as it picks up patterns in the code and will complete whole lines or chunks of code. There, I'll assess the results like any other auto-completed suggestions.
For other things like when asking questions I won't just blindly copy what the LLM is suggesting. I'll often rewrite it in a style that best fits the style of the codebase I'm working on, or to better fit it into what I'm trying to achieve. Also, if I've asked it for how to do a specific one-line query and it has rewritten a whole chunk of code, I'll only make use of that one line, or specific fix/change. -- This also helps me to understand the response from the LLM.
I'll then do testing to make sure that the code is working correctly, with unit tests where relevant.
The user you're replying to has made many similar posts like this. I previously tried engaging in good faith. I try not to fall into the XKCD 386 trap now, my time is better spent with Claude Code. Hope I can help save you some time too!
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