AlanYx
AlanYx on Hacker News
Thank you for pointing this out. Dahl is not really an Akkadian-focused scholar, though he teaches it; he's more well-known for his work on proto-Elamite. Still, probably more than capable to assist. I wonder if any Akkadian experts have weighed in on this translation?
Cuis is the easiest entrypoint into modern Smalltalk. All the others have so, so much stuff (great stuff, just a lot of it). Cuis takes the approach of paring things down to something minimal. You can understand everything from top to bottom fairly easily.
It's got a very interesting pixel layout, different even from previous tandem OLEDs. Hard to describe quickly in words, but shown in Figure 2 here:
https://www.apple.com/ca/macbook-pro/proled-xdr-display/pdf/... I imagine some of the C-shaped empty space is probably to accommodate the per-pixel emitter transistor.
A surprising amount of people use the back camera for document scanning.
One things Kimi is useful for is accessing/querying websites that have paywalls or try to prevent use by AI agents. It is aggressive and persistent for that, though not always successful.
The payphones aren't really all that anachronistic. Cue Phoebe Bridgers' 2020 song "Kyoto": "They still got payphones / It cost a dollar a minute".
That last point might change as you get deeper into the novel.
Still such a great novel; has aged very, very well.
North Korea does this too, actually (and like Israel, for both genders). It's probably one of the significant reasons why NK has such a comparatively effective offensive cybersecurity group, despite how unlikely that would seem given their overall industrial capacity.
NK likely also gets a bit of a boost because of the extended length of mandatory service. Males on technical teams have to serve for 13 years.
Russia has historically not had mandatory universal conscription.
Specifically Unit 8200, which really has no counterpart elsewhere in the world given Israel's mandatory universal conscription. Imagine if you could systematically screen every young adult in a country, identify those with the strongest math/quantitative skills or promising deep tech skills and divert them into one single security special ops org for several years. You'd get the concentration of skill that Unit 8200 has been producing.
Dentistry is an interesting field because it's the only major profession where you can still routinely get hired as a full professor without a PhD. (This used to be more common in other professions fifty years ago.)
As an outsider, perhaps this is one reason why there seems to be more of an applied and subjective judgment-based element to the profession, and significant divergence in professional norms/treatment choices internationally (some examples where norms differ quite substantially: value of silver diamine treatment, rates of general anesthesia use for pediatric treatment, attitude towards "immediate loading" in implant treatment).
Is this really a good solution for cooking though? The grid of holes for the speakers in the main column are going to get clogged with food spatters in no time, and they wouldn't be easy to clean. An iPad I can understand, since you can just wipe it off.
Anthropic did throw the UAE government under the bus in their "Detecting and countering misuse of AI: September 2026" report, specifically GTG-84002, which is framed in the report as a single misuse but bundles together a half dozen separate previously confidential projects from the UAE government, not all of which were unlawful/unethical (some were though).
Not trying to compare Anthropic to Meta, they're different beasts. But Anthropic is an unusual company in that it is willing to throw paying government customers under the bus if Anthropic unilaterally decides what those governments are doing is inappropriate.
The discourse around "gatekeeping" is so poisonous. I think a lot of non-mathematicians are looking at this situation as if this was a guild of medical doctors or some other profession with a regulatory monopoly trying to "gatekeep" access to math from a new upstart in order to preserve their own pricing power. That's not how the math community works, it welcomes all and there is no barrier to contribution.
Mathematicians do have some vested interest in keeping the profession from collapsing into an intellectual oligopoly, where one or two commercial players with early access to their own internal models continuously scoops everyone else and pollutes the field with externalities, and the profession itself collapses, only leaving AIs and hobbyists able to stand. At that point it'll be the AI firms who become rent-seekers. That's not really "gatekeeping" in any conventional sense of the term, it's protecting a healthy economy of ideas and the long-term development of mathematics.
Only a subset contain Lean formalizations. And even for that subset, there's the potential that the formalization is semantically off (that is, it's a formalization for a slightly different problem).
The reaction/fallout would have been substantially improved even if OpenAI had just made a commitment to not scoop external researchers using an internal model until X months after the model had been made available to the public.
That would have given grad students who've been grinding towards a PhD for years a fighting chance to see if they could leverage the model to push their work forward, rather than watching years of work potentially turn to dust via a tool they don't even have access to.
It wouldn't delay the progress of mathematics by any meaningful amount in the long run (an X month delay is nothing) for OpenAI to take this approach, and would help somewhat to preserve the health of mathematics as a field. Without it, the motivation for any young mathematician to devote years to a new problem must be sapped knowing there's an uneven playing field... an OpenAI team with access to colossal tools months before they'll ever be able to get access, willing to scoop anyone as soon as they can, perhaps without even taking the time to completely understand the proof.
I don't see any long-term benefit to OpenAI with their current strategy. This is an internal model; it's not available for sale at the moment. They've said they're not even going to bother claiming the Millenium Prize money for Navier-Stokes. It feels like kicking over hundreds of other people's chessboards just because they can.
Specifically, (n log n)^{1 - 10^{-13}}). There are likely no practical industrial problems of a size that would benefit from that specific reduction, but just breaking the nlogn barrier suggests that there may be more and better fruit here in the future.
This is really the critical thing: the fun is the incentive. (Or at least the dominant incentive in math, historically.) As economists like to say, the overarching lesson in economics is that incentives matter. Reduce the incentives and participation will decrease.
Perhaps that won't matter if we enter an era where AI participants are the main participants who matter for discovery-level mathematics. But it would likely be what economists would see as a market failure if only a small oligopoly of AI participants, closely held behind closed doors, is able to fill that intellectual role.
Certainly it'll result in a boom for hobby mathematics, and it'll be a hobby at a much more advanced level than before. Whether those hobbyists can continue to push the actual frontier, particularly if AI models operating along that frontier are not made accessible to hobbyists (either via corporate/AI lab gatekeeping, via pricing, or via significant time lags) is a different question. I'm a little more confident in a future where hobbyists push the frontier in applied mathematics than in pure mathematics.
There's probably a loose and deeply imperfect analogy with computing: via democratization hobbyists have made a big impact in applied operating systems development (Linux/OpenBSD) but have been less successful/impactful in OS research (whither Hurd...) or in cost-heavy fields like microprocessor design.
>but mathematics doesn't exist for their pleasure, it exists to provide tools to solve humanitie's problems.
The risk here is that this does do fundamental long-term damage to mathematics as a viable field.
Virtually no one is going to want to take on the risk of PhD-level math work, studying a narrow problem for four years or so to arrive at an impressive incremental result, when there's a sword of damocles hanging over their head every day that an internal system held by an oracle they don't have access to may scoop their results and turn those four years into dust.
To some extent, that sword of damocles always existed in a de minimus sense in the form of other mathematicians. But everyone was playing the same game, coming to the game with the same arsenal limited by human cognition.
If the game board becomes irrevocably tilted, new entrants have no incentive to play except as a hobby. But few hobbyists can devote years of work to understanding and pushing the frontier. It could well mean existential damage to mathematics as a field.
Whether that might undermine math's ability to solve humanity's problems in the long term is almost an economics problem, not unlike the question of whether and when the existence of monopolies ultimately restricts long-term economic growth. Much probably depends on whether intellectual monopolies or oligopolies are being created that will supplant the existing mathematics "economy".
He's a research fellow at a politico-economic thinktank, not academia. But it is disappointing given that he also has a PhD from Harvard.
Nortel's patents were among the first that were critical to modern MIMO OFDM (they really were on to the future in that sense, it's not hyperbole), but most never went to Qualcomm or Huawei. When Nortel went belly-up a consortium called Rockstar co-owned by Microsoft, RIM and a few others ended up buying them for a hefty price (more than $4 billion). It's possible some of them have made their way over to Qualcomm or Huawei as part of sales over the years I guess.
Chinese phone manufacturers that use Qualcomm hardware generally do respect the royalty system. Though they pay a lower total royalty because of a 2015 antitrust action in China, which forced Qualcomm to calculate royalties on 65% of the net selling price of devices sold for use in China, rather than 100% used in most of the rest of the world. (For those unfamiliar, Qualcomm's royalties are not a flat fee per device/modem, they're calculated as a percentage of the total selling price of the finished device, sometimes with a negotiated cap.)
China is playing the long game here because they expect domestically generated IP revenue to be significant in the future.
AFAIK, a lot of the Ericsson and Nokia patents are legacy. Companies still need to license them, but they're not targeted at the latest generation of 5G polar codes, MIMO OFDM implementations, etc. Not sure about Samsung.
Qualcomm does more than 5 billion a year in patent licensing revenue. It's a licensing behemoth.
It's a hard area for the government to navigate because IP is designed to confer monopoly power. As long as Qualcomm walks a careful line on licensing costs/behaviour, they probably think the risk of being the target of antitrust sanctions is limited or manageable.
Consumers will likely pay incrementally higher prices though.
They're not giving it away, rather they're essentially forming a patent oligopoly. Huawei and Qualcomm together hold the bulk of patents for 5G. It's of no value to them to try to litigate against each other. Here they're getting a cross-licensing deal that will solidify their patent licensing wall/revenues.
Is it potentially anticompetitive? Yes.
Tufte doesn't really move far beyond exploring examples he likes, and as a result, it's hard to take away any generalizable set of principles. Some of the few "rules" like this data-ink ratio are framed as generalizations but depend on idiosyncratic aesthetic judgments.
I think this is why every Tufte-inspired CSS framework or LaTeX style ends up just cargo-culting the style of his books: Bembo/Palatino/ETBook typography, italicized subheads, an asymmetric wide margin layout, margin notes replacing footnotes, illustrations/diagrams in the margins. (Like the linked website.) Few people are really confident after reading the books to stake out their own approach. It's not a bad aesthetic, but if the books were truly successful at their goal, varied application of the ideas would be as common as imitation.
Definitely. His book "Accidental Empires" (subtitled "How the Boys of Silicon Valley Make Their Millions, Battle Foreign Competition, and Still Can't Get a Date") is also an incredibly fun read, and a glimpse into a lost era. If anyone likes the true story of the guy sneaking into vintage Apple to develop Graphing Calculator out of pure passion, you'll love Accidental Empires.
(Just realized I've never read the 1996 update/revision. Adding it to the top of my list.)
It wasn't just the captive slaves and human sacrifice either (though that was a big deal), the Aztecs imposed crushing economic tribute burdens on subjugated city-states, and when payments fell short, they'd go in and raid. Tribute wasn't just gold and tradeable goods, it was also food, and the Aztecs didn't care if they drove a place into famine.
There were also rival indigenous states (Tlaxcala, etc.) that were never conquered by the Aztecs but had been trapped in continuous low-intensity war with them for years.
Though it is worth saying the Aztecs weren't universally despised. Some regional dynasties were allies. Some of those were also unpopular.
A lot depends on what clothes you're washing. Modern enzymes are most useful with modern synthetic material blends, especially underwear. If you've ever had that type of thing stay stinky after washing, that's what's missing.
If you're wearing mostly cotton, normal detergent is largely fine unless it's heavily soiled/stained.