gattsuru
23hr ago
It's a little rough because the actual facts for the actual conviction are genuinely messy.
Johnson's conviction for the robbery and homicide of Kenyatta Smith depended heavily on Ozzie Clark's testimony identifying him, and if you actually look at the transcript, that identification is genuinely pretty shaggy as testified. Charitably, Clark did genuinely have reason to fear retribution had he immediately pointed at a murderer, and at court received not-very-subtle intimidation in the court room, so him claiming to have no idea who the shooter was the day after the murder could plausibly just that. It's also a lot of impeachment material for a witness. The jury had the information, and the supposedly prejudicial hearsay was just a police officer saying the other accused guy pointed to Johnson, so I can't judge too critically by just reading transcripts. I can at least see it, though, where some of the others are just clearly guilty people.
Even the misleading statements during the concession aren't that misleading, at least by the standards of defense attorneys and activists. I'm pretty pessimistic on what that means, so we're fully in damning with faint praise space, but you don't have fabricated quotes or completely made up claims. Clark did genuinely say he was motivated to provide testimony now because of "civic duty"/"civil duty" after claiming something entirely different before, and did genuinely say he had "not visual" identification. But he also claimed during the trial he "I didn't need any problems by getting involved in all this" (aka feared retribution), and that he'd seen Johnson very shortly before the shooting, had known him for a long time, and had heard his voice, and none of those things made it into the concession. That's the sort of stuff that's a central case of what 'duty of candor to the court' means in a classroom, and also the sort of failure of candor that ends up polluting widespread pleadings.
But the actual behavior in the review office is hilariously bad. "Stiegler Schemes to Blame Mason" sounds like a partisan judge editorializing, until you read the section:
At this time, Stiegler “lobbied” Ernst and Napiorski. Early on June 5, Stiegler told Ernst that Mason “had purposefully inserted the false facts into the response,” and that “this was one hundred percent her fault, zero percent his fault.” Stiegler suggested that the DAO “file something with the Court preemptively before the hearing explaining that we had gone through Ms. Mason’s cases, that we found mistakes in other cases too, and that, therefore, this was all her fault.” Ernst responded that if there were errors in Mason’s other cases, this would only show a pattern of poor supervision by Stiegler. He nonetheless persisted:
[W]e have to get out ahead of this. Because if we get out ahead of it, then the Judge will view this as one rogue ADA—well, an ADA who went rogue basically. And whereas if we don’t, then he will think of this as this was all Matthew Stiegler’s fault. Stiegler made the same suggestion to Napiorski: “to look through old filings or old documents that Ms. Mason prepared and find more mistakes and to kind of paint her as a rogue actor.” Yet, Stiegler testified before me that Mason was an “experienced” ADA, “one of our strongest ADAs in the [U]nit.”
And then later:
Mr. Krasner’s actions are more troubling. He did not simply learn of the Stiegler proposal; he urged the Law Division supervisors—who serve at Mr. Krasner’s pleasure—to implement it and to present a false narrative to the Court. Mr. Krasner directed that the DAO stay involved in Johnson “to protect the office”—which Napiorski believed also meant protecting Mr. Krasner himself—and that the Four “not do any investigation”. “[Mr. Krasner] didn’t want people poking around in what occurred.” (Id. at 126:2 (Wildberger).) He thus sought to direct the very lawyers obligated by law to correct the Concession’s errors to do just the opposite. Even worse, when told that the Four believed they had to alert me, Mr. Krasner responded that “there would be consequences for Ms. Ernst if she alerted the Court to the conflict issue,” and that there would be consequences “if anyone did.”
This is three stooges shit.
Now, to be fair, this is one judge's summary of affidavits, where pretty much everyone involved has strong incentive to cover their ass and sell someone else up the river. But everyone there is a lawyer, so however you shake out the properties, somebodies lying. My gutcheck has Stiegler and Krasner at the worst side of the line, for what it's worth.
gattsuru
2d ago
a soft takeoff requires the model to think of novel, never-before-seen techniques to build a better new model, and the new model needs to be able to think of new techniques that the previous model couldn't. And even if we got a soft takeoff, it would give many chances in the future to pull the plug.
I don't think it's likely, but how are you modeling the risk of something like a super-DFlash or -GroupQueryAttention, or some training-focused equivalent? These took some insight to figure out, but I don't see why they're more clearly requiring deeper or less bruteforcable insight than the recent math proofs.
gattsuru
2d ago
Yeah, this was both incredibly predictable and heavily predicted, over a decade and a half ago; it's held up better than any of Yudkowsky's technical predictions, as little as it's surprising to find that the sun rises in the east. Tbf, I think the Amodei et al faction were explicitly arguing in favor of their enlightened and uncontested eternal reign, but to be more realistic it was pretty offputting a campaign a decade ago even when arguing to a bi furry who just happened to be a weak red triber.
gattsuru
2d ago
The Rittenhouse trial famously had news people running red lights while tailing yhe jurors.
gattsuru
3d ago
I'll caveat that it's not clear that a sell-off solves, rather than slows, AI risk; a competitor buying all this equipment at fire sales price might be less interested in building a machine god, but they'll still be interested in building a smarter system and have a lot of spare inference or training equipment to run.
Beyond that, it depends very heavily on what the end situation you expect.
The maximally-bullish case is some form of captured recursive self-improvement producing a massive and deep moat. Claude Fable 7.2 or Kimi 5 or (more likely) some internal specialized model produces a 5x efficiency boost, which makes throwing more processing power at the question economical, which unlocks another 5x efficiency boost, so on. At the more science fiction side of things, this could be new chips that combine FPGA-like re-programmability with ASIC efficiency; at the more plausible you've got software hacks, latency reduction, and conceptual refinements.
The good news from an X-risk perspective is that almost everything going this direction so far has been slow and in hardware, which put some limits on speed, since no matter how good an AI-designed chip or network layout is, logistics takes years. The bad news is that there have been some individual human-driven efforts already in software and model design (changes to KV architecture, MTP/DFlash) already, and it's the sort of space that I'd naively expect smart-enough LLMs to 'beat' humans by brute force. If it can pop off quickly, it will do so in months rather than years, and it will be a big surprise to almost everyone else.
That's not a massive moat, since eventually information (and models themselves) leak or a competitor open-sources them. But five or ten years of selling superintelligence at a tenth the cost of what your competitors are selling 'naive intern' can cover a hell of a lot of debt, as would being able to train smarter models for a hundredth of the price of your competitors. And at the really optimistic (from a business) or pessimistic (from an x-risk) cases, you stop being in a situation where 'revenue' or even 'competitors' makes sense as a question.
The more moderate bullish case is taking existing models and refinements to regulated fields, and getting a steep enough moat that the competitors can't step in easily. Higher education's the obvious option, if not likely huge and fast enough, between the external political pressures and underlying tensions in the business models for major colleges, but there's a lot of space in medicine and compliance that are heavily licensed in ways that could make it very hard for merely-good models to be used. Even some weird cases with general-purpose robotics could end up in a state where use is generally valuable, the liability risk of using sub-cutting edge models is extreme, and thus only the nerds can get business from the big companies.
Optimistically, this could come with a massive demand-side increase -- personalized instruction making everyone able to become experts in a field they find interesting, customized entertainment, productive hobbyist work. The middle case is Nothing Ever Changes despite it all, where we end up with gambling addicts and entertainment dollars redirecting at a 1:1 ratio, or some close approximation of it. Pessimistically, it could be the NSA wanting bulk data processing capabilities, and then 'selling the business' stops being an option: when state actors are a big enough portion of your financial model, your model stops being about finances.
The weakly-bearish case is just selling inference, well. The massive expenditures for training buildouts and heavy overpowered models eventually instead allow things like global prioritization and redirection based on load and spot energy costs, at a variety of different demand levels and latency limits.
((The actually-bearish case is a financial product one, where regardless of whether the hyperscalers are making profits, the book value of their assets drops catastrophically, either because of depreciation scaling or cost of servicing debts or financing existing products makes them sell out. But that's a much more complicated case than it sounds at first.))
gattsuru
5d ago
To be fair, the EA side does have numbers and did look at them hard. They can give numbers for malarial infection rates and deaths, both in before/after, difference-in-difference, and comparing high-malarial and low-malarial-risk environments to make sure they weren’t getting some spurious signal. There were even a couple times this lead to use of different insecticides chasing maximized numbers.
The bigger problem is how real the numbers they looked at are. The infection rates at least have some random sampling going on, but it’s a tiny fraction with some selection effects crawling back in. The bigger problem is fatality rates, which are derived from a mix of ‘verbal autopsy’ and modeled estimates from infection rates. But the verbal autopsies are known to be terrible, and the models use local funding of anti-malarial supplies as an input. Start backing them out and you end up with 10x to 20x variations that might be real or might be sampling on the dependent variable. Worse, almost all of the modeled effects (and even the difference-in-difference studies) give drastically higher results than the early RCTs, often 2-3x, and they themselves depended on comparing against people sleeping without nets at all, a scenario that basically doesn’t exist. That’s not impossible, but it’s reason to treat them with a massive grain of salt.
But on the gripping hand, the pessimistic numbers still involve at minimum tens of thousands of lives saved, and more likely hundreds of thousands. It breaks the economic argument, but not the raw effect.
The fishing nets thing is an annoying problem from an environmentalist perspective, but it’s ultimately a rounding error. There’s not much risk of fishery depletion from these nets, very little of the target areas rely on fishing for a big source of calories, and the chemicals aren’t that toxic to mammals. It’s a hundred-life problem, not a hundred-thousand-life problem.
gattsuru
5d ago
You've also got the difficult question of how well EA people can commit to it -- FTX sponsoring a concusionball stadium should have been one of those Murder-Ghandi moments -- but yeah. The systems here are hilariously corrupt, the tooling is corrupt, and even the numbers being used to extrapolate any analysis are huffing their own farts.
gattsuru
6d ago
I've run clockworkthought.com/blog and a number of other personal or project websites on NFS. They're the most trustworthy provider I can find from an ethos-of-free-speech perspective, but that's damning with faint praise, and I wouldn't put money on it, nevermind data.
(I also trust them to stay around longer than I trust Google Sites, which is the closest 'free' option. Google Sites is a lot more useful friendly for very simple document-style websites, though.)
The big selling point is that, for tiny websites or at low volume, they're dirt-cheap. For really optimized websites, you can end up paying less for hosting than you would for your domain name, but even at standard rates, sub-30 USD / year is pretty much the default.
The downside is that it's cheap, rather than inexpensive. You're not getting first-in-class performance, or user interfaces, or support staff. Even the built-in outbound email functionality is pretty limited. If you need a lot of storage (>10GB), plan on doing anything latency-sensitive, or need a lot of database functionality, they're not a great choice. There is a built-in control panel, and you can just use SFTP or SCP to upload files, but don't expect any WYSIWYG editor. Costs are based primarily on site storage count and don't have a real throttling capability, so if you allow user uploads, this could potentially be moderately expensive.
There aren't problems for my use case: I went with Grav as a content management system knowing that its design would be less responsive than NFS's hardware, and having to boot up a SCP client is second nature from my day job. Whether they'd be an issue for you is a bigger and probably harder question.
gattsuru
7d ago
Trivially, there's another side of the political aisle that's spent decades chasing conspiracy theories. Jet fuel can't melt steel beams, Diebold stole the 2004 election and Stacy Abrams is a competent governor who totally won, HIV was a Reaganite plot, Dan Rather was totally innocent and credible. This did not result in Gabby Giffords getting forgotten and unloved among the Left: indeed, it meant that even years after it was proven that the murderer was a complete nutjob, the central example of the mainstream media would still claim a Republican politician was really responsible, and never actually pay for it.
Just as trivially, we have a surfeit of other plausible and more likely explanations that the ground facts about Kirk's assassination don't seem to have drawn out a lot of their obvious consequences, as evidenced by the part where countless progressives and leftists who would not be caught dead (to be fair, a good choice!) listening to Carlson or Owens, who either have not commented about a major political assassination (hey, Trace!), commented only to say they don't care, or actively cheerlead the killing. It there any chance that the widespread support for violence on the progressive bench, and the broad supply of FUDD about Kirk's behavior and against ? For some strange and unforeseeable reason, you haven't considered a single one.
Hell, it's even just misleading on its own terms. Kirk had actual behavior that was bad enough, but in particular the description of Kirk's treatment of J6 is conflating observing a real thing (presence and prolonged concealment of informants, presence of a left-wing person cheering the violence) as something far broader than he actually did say.
gattsuru
7d ago
I wonder what other motivations Hanania might have.
gattsuru
7d ago
I made a bet on that for image generation, and bet wrong, so my confidence is very low, here. There are some technical reasons that it might be hard to train a model to recognize a good story (eg, it's possible for training to overfit on microscale solutions and then never pull any signal from the larger structure), but it's hard to come up with explanations that couldn't be applied to spaces LLMs have done well at, like math structures or short-form video.
I've actually drafted some lengthy write-ups of the different meanings of quality in these contexts. But they don't really seem to help the LLMs, and I'm not sure if that reflects a limit of the LLMs or of my writing. And their equivalents do genuinely seem to have been of mixed blessing in image generation spheres: learning about various artistic and photographic techniques helps get a specific output image you're imagining into creation, but the models themselves genuinely just get a lot out of positive: high quality, negative: bad art.
Random_Eddie on twitter did an approach that was pure prompting and moderately successful, although some slopisms bleed through (and doing a bunch of different writers in one conversation probably hurt). Tends to fall off pretty quickly if you want more than 3k-5k tokens of the same writer in the same context, though. Agentic approaches like Claude-Book 'work' better by doing things like perplexity analysis and gating, but I'm increasingly convinced they're a dead-end from a usability perspective even if they could write acceptably.
I've made a few LoRA with Unsloth, and while 'a couple hours' is more than a little generous, it is doable. I'll see about getting one from a recognizable and general-audience author.
That said, "style" is probably occluding a bit. You can get habits, formats, short-term pacing, and turns of phrase pretty easily just by motioning at the name, and sometimes too easily with LoRA. I've not been able to get a Zahn (or even Bujold or Butcher)-level plot setup just by asking for one, or finetuning, or throwing an agentic setup at it.
And none of them really solve the problem that the LLMs doesn't seem to know what makes a short story 'good', so if the problem is that prompting an LLM for a good story with no more detail, and then the LLM can't tell whether it's supposed to be writing fiction or nonfiction, that's going to be a harder problem.
gattsuru
8d ago
aka: Biden interpreted "shall" to mean "only when I want to, and I never want to", and TheAntipopulist will never, ever, ever, ever recognize it or grapple with it.
gattsuru
8d ago
Or, alternatively, they simply don’t like or play the genre well enough to engage with a game, à la the infamous Cuphead review.
gattsuru
8d ago
I'd caveat that the numbers game here looks really goofy. It only takes one in a thousand people matching FCfromSSC's perspectives to more than double the number of game developers in the United States. Worse, these new people can be a lot more productive in the sheer output sense even if the median one falls behind on the actual quality side.
I'll put a marker down: I'd expect Iron Pagoda gets at least one of the games released and in an SNES/GameBoy Color-level or better quality enjoyable playable demo by the end of the year this year, and probably a playable (if alpha) release by this time next year.
Fanfic genuinely has seriously twisted a lot of fiction writing incentives and economics, and that's about the most degenerate case available and the lowest quality.
In the short term, I'm hoping that the high-profile examples tend to require some underlying skill, if only because the AI tools will quite happily produce high-effort and lovingly detailed terrible ideas, and it takes skill to recognize it. But that's still going to make modern automated content farms look like child's play.
gattsuru
8d ago
Ironically, the necessary skills "make an X that's good" into a useful set of instructions might be 'alignment-complete' in the same sense of being a genie you can ask "I wish for you to do what I should wish for".
... or it might just be a matter of using the right prompting technique.
gattsuru
9d ago
This is something the 2024 bill would have ameliorated somewhat.
For anyone that doesn't want to reenact the reruns.
gattsuru
9d ago
One more recent matter that's killed them off, and not listed on the FanLore, is the pivot to ISBN'd book and anthology sales on a less formal schedule. Between the Kindle market, print-on-demand services, convention sales venues, and increased shipping costs, the conventional business model stopped looking anywhere near as compelling.
Which is a pity, because what's left did lose something from it.
gattsuru
9d ago
The economics is relatively 'easy', but I'd caution that the costs are higher than you'd expect. Printing is a scale service, but shipping mostly isn't, and the point where you're spending more to ship something than to print it comes around 50-200 units depending on what service, quality, and printing type you're going for. And that's domestic; if you have to ship international, you're spending more on postage than on per-unit production day one.
((This, coincidentally, is why merch and collections get pushed so hard; after production and shipping costs are included, these things end up being the highest per-unit profit, even if the sales are seldom massive in total revenue.))
The business model is hard. Subscriptions can cover a lot, but as Substack demonstrates, there's little relationship between the quality of a writer, the utility or correctness of their output, and how many people actually subscribe. Having good access or technical chops help get an audience, but there's a tension where these are resources that can be 'spent': access gets devalued if you're not critical enough and gets pulled if you are critical, expertise invites followers-on and there's limits to the extent of domain knowledge.
Traditionally, having the information first helped, but in this era that's a lost cause. You can't beat twitter to be the first to the scene, only be the first person to realize something was important.
There's also a bit of a conflict between sales model and content:
- Subscription works best with regular content drops and constant (and reliable!) production cycle, which typically pushes people to novelty or topical current-day events, which has the benefit where you have more consistent income, but also need to keep hitting that schedule, and both secular trends or a snafu can cost you a ton. That's workable for traditional news-and-reviews, cutting-edge research, or topical focuses.
- Bulk sales favor 'timeless' content and you can eventually make a surprising amount from sales of your back catalogue or 'collections', but the competition is harder (literally everyone who published in this field ever), maintaining that back catalogue can be expensive or literally messy, and maintaining customers is a lot trickier while your revenue goes feast or famine. Great for art or fiction.
- Sponsorship is the tricky option, where your product is a side effect of something else getting the real focus. That doesn't have to be conventional advertising: a lot of prints that make this work are loss leaders for businesses that need to show customers how to use their products, or coalitions showing why the entire class of product exists. It can also be direct advertising, with the caveat that unless your magazine is literally Architectural Digest or defense industry, you probably aren't getting any real money here. It works in some domains, and often better than 'traditional' sales or subscription for them - a lot of maker electronics stuff pivoted hard to it for a reason - but for a thousand-subscriber group, it's rarely going to be worth the time chasing the leads.
One very unintuitive thing is the sheer disconnect between the scope of your plausible sales audience and your plausible revenue. A periodical targeting hobbyist electronics seems like it should be able to print money on subscriptions alone, but there's a road paved with skulls: there's a million teachers who need your product and literally can't buy it for their use case, and your actual sales venue is people bored in a line at Microcenter on a shelf your small zine won't get on. The market cap, the 'success' stories and well-known cases, for scifi/fantasy review publishing, like Locus, have the sort of actual subscriber base that would disappoint a high school newspaper. You just can't do that market, period. On the flip side, there's been successful mags focused on (SFW!) niche-of-niche furry products that made great side gigs or whole one-person shops, because you can have ten thousand people show up at your table, wanting to spend money, over a weekend.
gattsuru
9d ago
Baldree's Legends and Lattes series.
Mixed feelings on it. It's very fanfic-tier, of the literally 'what if the adventurer retired and worked in a coffee shop' sense, which is what I was looking for, and in contrast to a lot of fanfic there's both a genuine grabber and a central plot arc instead of people just waffing at each other. But it's also painfully woke. I can deal with stories where I don't agree with the politics. It's annoying when it gets in the way of the rising tension, though.
Boiling your deuteragonist's backstory down to 'was discriminated against' might save us time, fair. When it's everybody's backstory, it's not really shorthand, anymore. When a threat hanging over the protagonist is defused as soon as you stop interacting with their human male flunkies and find out that she's an older woman, it's become self-parody.
Which is a pity, because there's a stronger story buried just a few steps deeper, and at points Baldree stumbles into it. What are the logistics of a new business, how does the Rules For Rulers concept apply at small locales and small gangs, what are the fantasy world ramifications of 'adventurer' being an actual job, what ramifications does retired adventurer bring, when they show up and get explored they're done well. Even the lesbian romance has tension to it, even if it's not my cup of tea. But then you get back to progress as its own byword and luck magic, and the tension just deflates again..
gattsuru
10d ago
The normal corruption is easier and thus a more common tone, but it's still present.
gattsuru
10d ago
Given your work, is it plausible that you are only going to get contracted by the sort of place that’s absolutely addicted to being Goodhart’d to start with?
gattsuru
11d ago
There's a big question of how you monetize this stuff without enshittifying it -- right now, HuggingFace's basically just selling storage and download, a space with historically not great margins, and the obvious market option of selling model inference runs into content moderation processing problems. Probably a commoditize your complement strategy.
But yeah, if you want a hand on open weights for a lot of AI-focused stuff, HuggingFace is the standard, right now, whether you're looking at LLMs, audio processing, or a lot of vision input work. ImageGen has gravitated to other areas, but even then a lot of people also upload to HF.
gattsuru
12d ago
I’d caveat that there have been some massive changes: translation is basically solved, ‘Rosie-the-robot’ style control is no longer science fiction but a creepy and dumb product, ai-assisted chip development and software engineering is a default option. Recursive self-improvement has been slow, rather than non-existent.
Some of the delay is just logistics. There’s probably over a hundred people worldwide following the AI cancer vaccine dog’s approach, but it’s going to be three or four years before we have clear and convincing academic papers even assuming it works and generalizes, just because that’s how medical trials work. AI driven assistance and funding for nuclear reactors might make building them in the US possible, but it isn’t going to make the NRC respond in less than six months. Silicon fab cycles are measured in years. Structural stuff just can’t be that fast.
Others are tooling. There’s a massive space where many small and medium businesses would benefit from custom code, for example, and AI can do it… but if your interface and sanity checks require a programmer or project manager anyway, it’s not really available yet even if the AI can do it. And Claude Code is not ready for prime time use by normies.
A lot of stuff is also just obscured when it does work. An AI-derived optimization algorithm for matrix multiplication just gets swallowed as a delta in efficiency from expected performance. An AI-built software tool just looks like a (verbose) software tool.
I typically cook for two to four people. I am not a good cook. Having a repertoire of recipes that you like and can produce consistently, while selecting purchase sizes carefully, and having a chest freezer for perishables, lets you cover a lot of gaps.
For these recipes:
Some other fun ones:
I would also not ignore meals that are shy of 'cooking' in the traditional sense. A block of soft mozzarella cheese, a loaf of bread, a tomato, and some pesto sauce makes an excellent sandwich that's much classier-feeling than the typical PB&J, and the only thing you need to be able to use is a butter knife and a toaster, and looks restaurant grade if you toast it in an oven or panini press with 'fancy' sourdough bread. Same for a ton of pastas and soups that are basically just heating it up and maybe adding water. Chili is hilariously easy, keeps well so you can have it for a few meals across a couple weeks, and can be spiced or mixed up to your preferences pretty easily -- cornbread is traditional, but long grain rice or spread thin on a naan works wonders, and if you really want to summon dark gods heavier mixes do genuinely work on pasta at the cost of your immortal soul.
You can go fancier and still keep it in a single pot and <6 servings, but you really don't have to.
That said, accept that some food waste is going to happen, and it's not worth optimizing out. A whole onion is about two dollars at unit count one, and 50 cents for a bag. A bachelor or couple will probably start an onion and have to throw out or compost half of it. That's fine, it's a rounding error, and if you try to optimize it out you're going to waste more time, energy, and money anyway.
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