South_korea_ln

The Hijacking of Bitcoin - Brownstone Institute https://brownstone.org/articles/the-hijacking-of-bitcoin/ Someone in a crypto group I'm part of sent this article yesterday. I stopped reading after this paragraph: > Lightning works like opening a tab at a bar: you and the bar settle later. It is faster and cheaper for small payments, but it relies on middlemen (called hubs) who hold your money in channels and can see what you are doing. It is not the same as handing someone cash. It adds points where someone else can interfere or shut things down. When I told him I stopped reading after this uninformed paragraph on the LN, they asked me, _what is LN_? Yet, he based his current negative sentiment on Bitcoin on this article. This resonates with the article @Darthcoin just posted (https://stacker.news/items/1452620/r/south_korea_ln). This is what we are up against. Willful and/or accidental misinformation campaigns. The LN works. People are working on making it better, but it works. https://stacker.news/items/1452632

Massacre of girls at Minab school: human error or artificial intelligence? https://en.ilsole24ore.com/art/minab-school-girls-massacr… I already vented about the human side of this massacre here (https://stacker.news/items/1448847/r/south\_korea\_ln), but posting this article as it turns out this could have been influenced by the heave use of AI. > The preliminary report, according to rumours in the New York Times, reveals that the school was destroyed because Central Command, the military command engaged in the Middle East, relied on outdated intelligence information, provided by the Defense Intelligence Agency (Dia), the Pentagon's intelligence service. And which, inexplicably, was not checked, a procedure that traditionally takes place at several levels and can draw on hundreds of analysts and military experts. To me, the title is misleading. If it is AI that incorrectly assigned the school to be a military target because of outdated data, then it is *very much* a human error. But then again, as with coding, people don't seem to take responsibility for the code their LLM spawns. In an ideal world, someone would take responsibility for this shitshow. Yet, this market will likely resolve with a *no*: [https://beta.predyx.com/market/pete-hegseth-out-as-secret…](https://beta.predyx.com/market/pete-hegseth-out-as-secret…) https://stacker.news/items/1452627

The Obvious Problem That No One Can Agree On - Veritasium What are you? Please answer the question before getting into the explanation part of the video (starting at 3:32). https://www.youtube.com/watch?v=Ol18JoeXlVI&t=709s This is one of the better Veritasium videos I've watched. I especially like the comments on free will, how to live your life, and rationality. > Whether we do or don't have free will, you have to live as though it exists. This resonates with me because in my mid-20s, I entered a (quasi)depressive mindset where, after reading several books touching on this topic, it made me feel like whatever I did, it didn't matter. I then, at some point, just decided to live by the idea that free will exists, as the alternative was not worth living anymore (and also, it almost alienated a few people around me when I tried to elaborate on those metaphysical ideas). https://stacker.news/items/1451423

The Ordinals BIP got rejected https://x.com/SomsenRuben/status/2029515060893106418 > Short summary: we weighed pros and cons, seemed to fall slightly to the con side, but nobody felt strongly enough about it so it sat in limbo. A decision had to be made, and eventually one of us did. > I'll share more of my thoughts in this thread https://stacker.news/items/1448187

US has begun ‘major combat operations’ in Iran after Israel launches strikes https://www.theguardian.com/world/live/2026/feb/28/israel… https://stacker.news/items/1444488

Guidelines for Papers, Theses, Posters and Talks - Jan von Delft (2002) https://homepages.physik.uni-muenchen.de/~vondelft/JansSt… Once in a while, one stumbles on a random blog post. With a ton of valuable information. If you're in academia, this one might be useful. > Below we offer numerous guidlines, hints, suggestions and strong(!) opinions on how to effectively communicate the results of your research. Communicating your results effectively is an invaluable part of doing science, and one that requires considerable effort and experience. Of course, communication is ultimately a very personal matter; accordingly, personal styles differ widely and you may disagree with some points below. But even if you do, the guidelines will at least encourage you to think of a good reason why you disagree, thereby serving their original purpose yet again, namely to > _encourage you to devote a lot of thought to communicating science effectively._ > Implementing some of these suggestions may require huge amounts of time and effort. Nevertheless, don't shirk these! Just as in a market economy, > _only polished products sell well !_ > The reader of your paper or the audience of your talk (=customer, buyer) expects and deserves to see only the final, optimized product (the history of its development seldom interests them). If your product is too far from perfect, they'll rapidly stop paying attention. This matches very well the thinking of my last advisor... However, this sometimes led to breaking the known adage saying "perfect is the enemy of good"... once too often, we did not ship because the product did not reach the standards he set for himself. Academics would probably benefit from doing an internship in a company where one has stricter deadlines on when to ship. https://stacker.news/items/1441953

How AI helps break the cost barrier to COBOL modernization | Claude https://claude.com/blog/how-ai-helps-break-cost-barrier-c… Related (but focused on the stock aspect of it all): https://stacker.news/items/1440907/r/south_korea_ln > COBOL is everywhere. It handles an estimated 95% of ATM transactions in the US. Hundreds of billions of lines of COBOL run in production every day, powering critical systems in finance, airlines, and government. I'd be interested in getting similar numbers on Fortran (or cpp) in the context of legacy physics code... > Despite that, the number of people who understand it shrinks every year. > The developers who built these systems retired years ago, and the institutional knowledge they carried left with them. Production code has been modified repeatedly over decades, but the documentation hasn't kept up. Meanwhile, we aren't exactly minting replacements—COBOL is taught at only a handful of universities, and finding engineers who can read it gets harder every quarter. Yeah, I was the only one willing to use Fortran in the group I worked at previously. Young people don't like those old codes. I'm happy I've joined a group now where the number of Fortran devs is a bit higher, still. > COBOL modernization differs fundamentally from typical legacy code refactoring. You aren’t just updating familiar code to use better patterns, you’re reverse engineering business logic from systems built when Nixon was president. You’re untangling dependencies that evolved over decades, and translating institutional knowledge that now exists only in the code itself. Rhaaa, I find #AISlop patterns everywhre now. > Modernizing a COBOL system once required armies of consultants spending years mapping workflows. This resulted in large timelines and high costs that few were willing to take on. > AI changes this. > These tools can: - Map dependencies across thousands of lines of code - Document workflows that nobody remembers - Identify risks that would take human analysts months to surface - Provide teams with the deep insights they need to make informed decisions > With AI, teams can modernize their COBOL codebase in quarters instead of years. I'll let you read the rest of the article if you're interested in more specifics. > https://resources.anthropic.com/code-modernization-playbook I'd be happy to find a similar playbook for my old legacy FORTRAN code. Not to rewrite it in a different language, but to get rid of all the spaghetti-code... Even without playbook, if there is one thing LLMs are good at, it's refactoring code. I'm just too chicken to let it do it more aggressively without my oversight... https://stacker.news/items/1441289

How AI helps break the cost barrier to COBOL modernization | Claude https://claude.com/blog/how-ai-helps-break-cost-barrier-c… Related (but focused on the stock aspect of it all): https://stacker.news/items/1440907/r/south_korea_ln > COBOL is everywhere. It handles an estimated 95% of ATM transactions in the US. Hundreds of billions of lines of COBOL run in production every day, powering critical systems in finance, airlines, and government. I'd be interested in getting similar numbers on Fortran (or cpp) in the context of legacy physics code... > Despite that, the number of people who understand it shrinks every year. > The developers who built these systems retired years ago, and the institutional knowledge they carried left with them. Production code has been modified repeatedly over decades, but the documentation hasn't kept up. Meanwhile, we aren't exactly minting replacements—COBOL is taught at only a handful of universities, and finding engineers who can read it gets harder every quarter. Yeah, I was the only one willing to use Fortran in the group I worked at previously. Young people don't like those old codes. I'm happy I've joined a group now where the number of Fortran devs is a bit higher, still. > COBOL modernization differs fundamentally from typical legacy code refactoring. You aren’t just updating familiar code to use better patterns, you’re reverse engineering business logic from systems built when Nixon was president. You’re untangling dependencies that evolved over decades, and translating institutional knowledge that now exists only in the code itself. Rhaaa, I find #AISlop patterns everywhre now. > Modernizing a COBOL system once required armies of consultants spending years mapping workflows. This resulted in large timelines and high costs that few were willing to take on. > AI changes this. > These tools can: - Map dependencies across thousands of lines of code - Document workflows that nobody remembers - Identify risks that would take human analysts months to surface - Provide teams with the deep insights they need to make informed decisions > With AI, teams can modernize their COBOL codebase in quarters instead of years. I'll let you read the rest of the article if you're interested in more specifics. > https://resources.anthropic.com/code-modernization-playbook I'd be happy to find a similar playbook for my old legacy FORTRAN code. Not to rewrite it in a different language, but to get rid of all the spaghetti-code... https://stacker.news/items/1441289

The Darkest Web: Inside the internet’s most hidden corners to save kids https://www.youtube.com/watch?v=mNUku0jd4FA Pretty well-made documentary, but hard watch. https://stacker.news/items/1437796

Mathematicians issue a major challenge to AI—show us your work https://www.scientificamerican.com/article/mathematicians… Cfr what I mentioned here: https://stacker.news/items/1433533/r/south_korea_ln?comme… > But none of these tests were controlled experiments. Olympiad problems aren’t research questions. And LLMs seem to have a tendency to find existing, forgotten proofs deep in the mathematical literature and to present them as original. One of Axiom Math’s recent proofs, for example, turned out to be a misrepresented literature search result. > And some math results that have come from tech companies have raised eyebrows among academics for other reasons, says Daniel Spielman, a professor at Yale University and one of the experts behind the new challenge. “Almost all of the papers you see about people using LLMs are written by people at the companies that are producing the LLMs,” Spielman says. “It comes across as a bit of an advertisement.” > First Proof is an attempt to clear the smoke. To set the exam, 11 mathematical luminaries—including one Fields Medal winner—contributed math problems that had arisen in their research. The experts also uploaded proofs of the solutions but encrypted them. The answers will decrypt just before midnight on February 13. I haven't seen articles yet about the outcome, but I guess it'll be there soon enough with this Feb 13th deadline. https://stacker.news/items/1433704