Full title, "...than ever": 64 characters
Another title currently on the front page has 74 characters: "The Many Roots of Our Suffering: Reflections on Robert Trivers (1943–2026)"
6,322 karma · joined December 9, 2011
Another title currently on the front page has 74 characters: "The Many Roots of Our Suffering: Reflections on Robert Trivers (1943–2026)"
- serif was claimed to lead to better horizontal tracking... so better for long prose readability
- sans serif was claimed to lead to better spot-recognition of characters... so better for spot-character/word recognition and legibility
Those effects were never very strong, and varied depending on the exact fonts in use (and for digital, font rendering characteristics).
There's also probably an effect based on what you're used to. If most of the books you read are serif (which they would be for older people, since almost all printed books were serif), and your exposure to sans serif was largely via the internet, and you don't like most of what's written on the internet, that might sway you toward serif. Conversely, if you mostly read modern internet text, you might have the opposite bias.
No RPN. Every modern graphing calculator needs a mode (doesn't have to be the default) with RPN and a visible (4+ entry) stack. Once people actually learn how to use that for rapid, efficient calculations, they won't go back, but they never learn because all the major calculators don't even offer it as an alternate mode. That's the killer app for "graphing" calculators, because they can show multiple stack entries.
RPN may not be useful for math classes, which tend not to have as many problems involving many sequential calculations, but it's extremely valuable for science and engineering.
Limiting the poll to 200 books (if I'm understanding it right... the cited le monde page is paywalled), selected by the elite French-literati, who then polled sub-elite French-literati, is a questionable basis for a list of "books of the century", even in France. Numbers of votes for each book would've been nice, to see how unanimous the top selections were.
8/100, in any language, are from the last third of the century (after 1967). Of those, 4 are well-known in North America (Styron, Eco, Rushdie, Solzhenitsyn). Of those, only two, Styron and Rushdie, are originally in English.
The most recent -en- works prior to those two were Kerouac in 1957 and then Nabokov and Tolkien in 1955.
year: number (fr/en/other)
1900s: 7 ( 1 / 4 / 2)
1910s: 4 ( 3 / 0 / 1)
1920s: 20 ( 8 / 7 / 5)
1930s: 12 ( 6 / 5 / 1)
1940s: 19 (10 / 4 / 5)
1950s: 20 (13 / 6 / 1)
1960s: 12 ( 7 / 0 / 5)
1970s: 4 ( 1 / 1 / 2)
1980s: 2 ( 0 / 1 / 1)
totals: 49 / 28 / 23
If its responses were perfect so that you could chain them, or if you could ask "please give me words 10-15 of chapter 3 paragraph 4 of HPatSS, and it did so, then you'd have a better case to complain. Still, the counterargument is that repeated prompting like that, explicitly asking for copyright violation, is the real crime. Are you going to throw someone in prison if they memorize the entirety of HPatSS and recite arbitrary parts of it on demand?
Combining both issues: that LLMs are only regurgitating mostly accurate continuations, and they're only providing that to the person who explicitly asked... any meaningful copyright violation moves downstream. If you record someone reciting HPatSS from memory, and post it on youtube, you are (or should be considered) the real copyright violator, not them.
If you ask for an identifiable short segment of writing, or a piece of art, and get something close enough that violates copyright, that should really be your problem if you redistribute it (whether manually or because you've coded something to allow 3rd parties to submit LLM prompts and feed answers back to them, and they go on to redistribute it).
Blaming LLMs for "copyright violation" is like persuading a retarded person to do something illegal and then blaming them for it.
(excluding things like administration of organization-wide infrastructure key material)
Cheddar, the kind of cheese allegedly at issue in this outbreak, appears to be a low-heat cheese, so you wouldn't start by heating the milk to pasteurization temps. If the milk isn't already pasteurized, the resulting cheese might be contaminated.
European soft cheese makers allegedly follow protocols to ensure that there's not substantial bacterial contamination in the beginning; they carefully handle the milk through the beginning of the cheesemaking process, after which the culture and salt and acidification stall any further bacterial growth; then aging cuts down any bacterial population to safe levels, and it's never reached a level where it could produce dangerous levels of toxins.
Competent American raw-cheese makers would do the same thing, but in the interest of supplying "raw milk product" fanatics, unscrupulous businesses will cut corners for profit. High contamination levels of the initial raw milk, or substantial cross-contamination after aging, is probably what led to this and the company's previous cheese contamination problems.
As you said, it's lossy. Try it with any other distinctive but non-famous passage, and you won't get a correct prediction for the immediately following clause, much less for multiple sentences or paragraphs.
That's the case even when an LLM correctly identifies which book the prompted text is from. It still won't accurately continue on from some arbitrary passage. By the time you ask it to reproduce hundreds of words, you're into brand new book territory. Even when it's slop content, it's distinct slop.
The exceptions are cases where a significant number of humans would also know a particular quote from memory. Then, chances are, a frontier LLM will too.
You know how else you can reproduce a quote? Search for it on google, and search the resulting top hits; if it's a significant quote, multiple people have probably quoted it -- legally. You can also search a pirate library for the actual book, and search the book for the quote; while illegal, it's very simple to do, so unless you propose to make the free and open internet illegal, I'd suggest that banning LLMs for being "derivative work" creation engines is not so different from destroying the internet.
> I predict, no pun intended, that a time is coming when the idea that it's not a derived work will be challenged in mainstream law.
If judges have any sense whatsoever, LLM generations (without specific prompt crafting to mimic existing works) will be judged to not be derived works and therefore not be violating copyright, in the same sense that you can live and breathe Taylor Swift's music, create new music in the same style, and still not be violating copyright.
The Stability AI case, and how Judge Orrick deals with it, will be interesting and uninteresting at the same time. It deals primarily with the fact that after specific prompting, an image-generation AI can generate something fairly close to existing copyrighted images. That doesn't say anything more about whether LLMs are inherently producers of [only or primarily] derivative works, just as the fact that a human can violate copyright doesn't say anything about whether humans primarily or exclusively output derivative works.
More likely, perhaps, is that everything will be so infused with LLM output that copyright ceases to be relevant, or forces copyright law to be rewritten from the ground up.
Copyright requirements, even prior to LLMs, weren't well-specified. There's no objective threshold for how close something has to be to a previous work before the new one violates copyright. It's whatever a judge thinks, refering to the 4-factor test but ultimately making subjective judgements about each of those prongs. It's all a house of cards, and LLMs may just be what topples it.
A lego sculpture is copyrighted. Lego blocks are not. The threshold between blocks and sculpture is not well-defined, but if an AI isn't prompted specifically to attempt to mimic an existing work, its output will be safely on the non-copyrighted side of things.
A derivative work is separately copyrightable, but redistribution needs permission from the original author too. Since that usually won't be granted or would be uneconomical, the derivative work can't usually be redistributed.
AI-produced material is inherently not copyrightable, but not because it's a derivative work.
Journals are an academic-career-advancement service. It therefore makes sense that they do not pay academics. You don't pay your customers.
That means they need to generate a secondary customer base elsewhere, who will pay. Those secondary customers happen to be the employers of the academics who are the primary customers. That socializes the cost of providing the service, since academics individually wouldn't be willing and able to pay.
Once journals have established a reputation, their policies and paywalls and fees are the result of trying to signal exclusivity and set an optimum market price.
Until the supply side of the research market largely agrees on a way to use open-access repositories like arXiv as a primary career-advancement signal, complaining about closed-access journals is tilting at windmills.
Changing the law to prevent journals from being able to copyright anything could potentially force the research industry to rapidly develop a new solution, but at the cost of short-term chaos and career instability for new academics.
First of all, would we restrict all internet access, or just access to certain known sites and VPNs, letting everything else through because it's too insignificant even if it technically might merit being blocked for kids? I don't think a global internet block for minors is a good idea.
On wired internet, restricting access for devices that aren't clearly tied to individual users is problematic. Imposing age verification overhead on anyone who runs a network is unacceptable and unworkable. Locking non-mobile devices to individual users, in order to have mandatory software that blocks or sends age signals to the ISP, is also unacceptable and unworkable.
For mobile devices, maybe. There's a privacy problem if it's required for sim cards to be paid using credit cards, but if we do that, or if that's already effectively the case, I think it's fair that anyone who has an active credit card should be permitted on the "adult" internet. For multi-line accounts, we could make it a crime for the account holder to misrepresent age of the user of a line, i.e. to claim they're an adult when they're really a minor. Not very different from minors and cigarettes. It's not universally illegal for a parent to supply them, but it is in some places, and it should be.
You can easily play or spectate a low-unit count game of BAR on any decent 2010+ quad core.
Such a computer won't allow you to play 8v8 that goes into the late-game stage. Sometimes not even 4v4 or 2v2 with players scaling to high unit counts. Some players try anyway. Ignoring player disconnections, half the drama of large-scale games is the one player who's lagging because they're on a potato computer. If the sim doesn't lag, the game will at least be down to single-digit fps.
That means you can't really play multiplayer comfortably, at least not beyond 2-4 players.
For that, you need a recent ryzen or intel. I'd estimate recent as post-covid.
I don't know what combination of things is important; there's larger cpu caches, faster sustained CPU frequencies (TDP and cooling matter there), hardware mitigations for speculative execution bugs, faster ram, resizeable BAR support... but in my experience going from a 6-core skylake-era cpu to a ryzen 9xxx, with the same gpu, made a massive difference. I saw no massive improvement going from a 4-core 2010-era cpu to a 6-core skylake-era cpu; I'd classify both as potatoes for BAR purposes.
Programming talks about parallelism or concurrency or threading. (single-threading, multi-threading)
Or synchronous and asynchronous.
The legal system talks about concurrent and consecutive.
Process descriptions might use "sequential" rather than consecutive or series.
"Linear" is another possibility, but it's overloaded since it's often used in reference to mathematics.
What can't happen is inter-generational transmission of particular subjective experiences that aren't paired with specific, unique metabolic, hormonal, and gene-expression signatures. Only biomolecular-mediated phenotypes, the most general and obvious of which would be things like stress or exercise or diet, make sense to be transmitted that way.
For instance, someone who's chronically afraid might transmit some kind of stress/fear modulating signals to offspring. Someone who's afraid of a specific thing, however, cannot transmit fear of that specific thing unless there's some incredible and unexplored cognition-to-biomolecular signalling mechanism that's entirely unexplored and undescribed. Therefore, I don't know why the article uses the term "lived experience", which is too broad a term to describe what the research suggests might be occurring.
I'm skeptical. Is there no more value to series like Gormenghast, Book of the New Sun, and The Second Apocalypse, beyond mere literary masochism, compared to LotR? Like them or not, LotR, as elaborate as its mythology is (if you include Silmarillion and some or all of the History of Middle Earth), is not at the same level.
What's interesting and not easily explainable if true, however, is the suspicion that the Black Dahlia murderer used a motel that at the time was called the Zodiac Motel. That forward-connection would've taken someone obsessed with solving the Black Dahlia murder, not just interested in the nature of the crime; assuming the theory about the Dahlia murder location is correct, the Zodiac killer would have had to solve the location of the Dahlia murder by himself, and then use it as an in-joke for a later series of unconnected murders.
> $ curl -i http://press.knowledge.dev
> HTTP/1.1 409 Conflict
[...cloudflare headers...]
> error code: 1001
google suggests that error 1001 is a cloudflare-side DNS configuration problem with the domain (which is CNAME'd to target.substack-custom-domains.com, which is cloudflare-hosted). CNAMEs to cloudflare seem to require special care.
Chargeback. Tell your credit card company the truth, you can't login to cancel substack payments, and let your credit card company deal with them.
If you used paypal, they already allow you to cancel recurring payments from paypal's website, without going through the payee at all.
Maybe substack has been lazy in implementing this, or maybe the guidance the were getting as the deadline approached was conflicting. They may have it fixed soon. They may even determine that payments associated with the account indicate over-16 and they don't need to lock you out at all. Or, getting hit with a lot of chargebacks will motivate them to have a separate login flow to cancel billing even if they can't let you read what you paid for. You can't be the only person frustrated at being locked out while they're still billing you.
> The fatigue limit or endurance limit is the stress level below which an infinite number of loading cycles can be applied to a material without causing fatigue failure.[1] Some metals such as ferrous alloys and titanium alloys have a distinct limit,[2] whereas others such as aluminium and copper do not and will eventually fail even from small stress amplitudes.
My experience with people who have LLM subscriptions of any kind is that they use them all the time and would immediately ask an LLM that kind of question, rather than asking on a web forum that's not even dedicated to math. So I think it's a fair presumption that someone asking that question doesn't have access to the best commercial models.
On the largely irrelevant question of what math LLMs can do, although Opus may do better, Sonnet can follow procedures sometimes but not consistently. It has blind spots and can't scale procedures; beyond certain numbers or dimensions or problem complexity, it just guesses (wrong). And those limits are quite low. If you want 2 simple examples:
4294967297*1331
Invert this matrix: m=[1 0 5 0 3 7; 2 3 0 3 3 2; 1 0 1 1 0 1; 3 5 3 5 1 2; 2 4 3 2 1 5; 1 0 5 2 1 5]
LLMs follow procedures, but whimsically. Better LLMs will be less whimsical, but they still won't be fully competent unless they digest questions into more formal terms and then interface with an engine like Wolfram.
We need merit-selected technical committees of non-representatives to advise politicians and tell them clearly, in as much detail as necessary, when they're wrong on something. If the politicians don't listen, the technical committees should be independent and able to make their case on the internet and social media.
Implementing that would be difficult. The metric for merit is a challenge, and is itself easily coopted by politics. For example, China's vaunted "political meritocracy" is ultimately controlled by party leaders in the CCP, so it's basically a meritocracy for the CCP-aligned, not a meritocracy for anyone else. If a government's goals contradict facts-on-the-ground, the government will find a way to skew an "independent" technical committee to suppress those facts.
I'm also referring to the faster models, not the slow and expensive deep thinking ones which I have little experience with. I don't see how reasoning would enable deep thinking models to meaningfully evaluate textbook pedagogy, either.
Math is a broad subject. This is something LLMs are actually reasonably good at: ask them for textbook recommendations, and get into a dialogue about which sub-areas of math you're interested in and what level you're currently at, whether you want pure math (more theorem-proof focused) or applied math (more practice solving concrete problems, e.g. finding lots of derivatives and integrals). Toss in names of books that have been recommended and ask where they fit in to the LLM's other recommendations.
LLMs don't understand the math, but they're trained on a lot of discussions and recommendations for math books, and have a reasonably good sense of what level different books are at.
Download multiple recommendations in each area and try them all out. Seeing how different authors start out approaching largely the same material will help you conceptualize it better than just relying on a single approach. There's no universal "right" book to learn from. I wouldn't buy non-free textbooks without trying them out first.
Youtube has a lot of math lecture series, which can help if you're stuck on a particular point, but they're not the same as doing problem sets yourself.