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User ID: 232



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User ID: 232

I can't help but find the timing of this to be extremely suspicious. A few weeks after the western IC warns Russia of a terror attack, a few days after it happens, practically at the same time as the Russian propaganda machine starts firing on all cylinders that we (NSFL links ahead) "beat the evil terrorists black and blue, barbecued their nuts and fed them their own ears and they confessed to being hired by evil satanic ukronazis", anti-Russian propaganda outlets start spinning tales about how the GRU with their secret spy shit ray guns are unquestionably to blame for melting the brains of US bureaucrats for the last ten years (despite the well known fact that said bureaucrats have no brains to melt - cue rimshot). I don't think anyone taking part in this whole cold war 2: electric boogaloo embroglio is even remotely credible, and I think it takes a lot more than a news theory to move the needle on public sentiment around Russia.

This is too zany, too spy-thriller, for the average person to care. I kinda doubt it was meant for us, i.e. normal(-ish) people with typical culture war axes to grind. Maybe it's a distraction to keep people from thinking too hard about the Crocus attack, maybe it's an influence op perpetrated on the western IC to build consensus about Russian foreign meddling, maybe it's a freak coincidence. The only culture war implications I can draw from this are increasing levels of paranoia in the US IC about the Russian Menace, continued wagon-circling about Ukraine policy, etc. That isn't terribly interesting to me, particularly because it isn't clear the manufactured consent is remotely in need of fortification in the US IC, so I don't have much else to say about it.

I get it now, and sorry for missing your point initially - my big lesson from interacting on this forum is that I tend to respond to the thing I know how to talk about, instead of the thing actually under discussion. Working on it.

Maybe the political parties could have a more productive dialogue with different candidates - I don't think any campaign with Trump in the mix can host meaningful debates, especially after the disastrous 2016 Republican primaries; and I'm less than confident that Biden is still firing on all cylinders. There's surely still some debate left in the downballot races, but between gerrymandering and party infighting, this year is less about debating issues and more about who should even get to speak.

I've worried for a while that the private sector has been absorbing competence on both sides of the aisle, ever since tech took off in the late 80s and early 90s. I think the kind of people you'd want to see in political contests, who'd be willing and able to actively engage in debates about relevant current issues, are pursuing more lucrative and less risky careers making targeted advertising platforms or whatever. So even if we had different candidates today, I'm doubtful we'd get quality debates.

Do you think there's an opportunity for productive debate with the state of US politics in 2024? With Trump v Biden? Someone else (who?)? Any downballot races you could point to as examples of what you want?

Alibaba has potential trade consequences that go beyond social media apps, and would be a much harder sell. It could also significantly impact the viability of Amazon, Walmart, and other large businesses that mostly derive inventories from China.

WeChat and Weibo are, outside of a handful of Chinese nationals with friends and family in the mainland, effectively already banned from the west - by China itself. These apps are crippled and uncompetitive in their neutered western forms. The Chinese experience on both platforms is widely understood to be dramatically different.

In all of the cases above, no one is targeting the median American teenager with pro-CCP messaging and anti-western memes. TikTok is.

To your point about electronics in China: if it were feasible, we'd consider it. But I think you underestimate the sheer size and cost competitiveness of Chinese manufacturing. Between their massive volumes, government subsidies, decades of manufacturing expertise built up on other people's goods, and the utterly anemic and perpetually consolidating western semiconductor market, you're talking about a trillion dollar decades-long pivot that would plunge the US supply chain into prolonged chaos.

And frankly, I already know what Trump and Biden would say in any such debate. Trump has been making his case for decades, and you'd have to be sleeping under a rock for the last eight years to know exactly what he wants to do with respect to China. And Biden doesn't really have anything to say about China - his administration can and does take reasonable steps to protect government and military supply chains from foreign powers, but clearly they aren't too concerned about the nature of our remaining trade relationships. I don't know what we'd gain from this or frankly any debate between the two sides - I think people made up their minds on Trump v Biden years ago.

Without getting too specific, I'm in a critical part of the EV supply chain. That said, I'm offering personal speculation based on publicly available information and some napkin math - there's some other stuff that informs my opinion which I can't really talk about, but it doesn't take an insider to see which way the wind is blowing.

This is just wrong. GM hasn't sold a hybrid (outside of a wacky Corvette model) in five years. The Volt was wildly successful, but it uses a now-dated central traction inverter and electrified transaxle design, which isn't a great choice for a full EV compared to per-motor or per-axle in-wheel or in-board hub motors. They might as well be starting anew. Ford at least has modern hybrid models, but they too are all central traction inverters. Meanwhile, SiC traction inverter tech has gone from impractical experiment to just about the only game in town in the last five years, which has completely rewritten the rules on the size, weight, and power tradeoffs required for hub motors. For these US automakers, modern EV tech might as well have fallen out the back of an alien spaceship, and they're clearly blowing billions on R&D trying to play catch-up on problems their competitors have already spent a decade solving and optimizing - just go look at how the F-150 Lightning was priced.

On a different note, most of the last ten years of hybrid battery development has used NiMH for its high reliability and large total cycle count, and this is yet another thing the US domestic auto industry is going to have to discard as they transition to Li-Ion.

Look at what Tesla is doing for an idea of the scale of changes needed. There is a reason they call their cell assembly plant a "gigafactory": the goal for Giga Nevada was to produce more capacity in 2020 than the entire world produced in 2014 (and on paper, this was achieved, though actual utilization fell short by around 30% for a variety of reasons). These guys crunched the numbers a decade before anyone at Ford or GM made so much as a whisper about fully electric vehicles, and determined they needed to have tens of GWh of vertically-integrated domestic battery production to get cell costs remotely close to viable at a run rate of a few hundred thousand cars a year (an order of magnitude below Ford/GM EV fleet annual expectations). In ten years, starting from nothing, Tesla's up to around 40 GWh total annual production capacity across every plant (more if you factor in grid storage capacity, which is a separate but thoroughly understated can of worms), with another 100 GWh coming online in the next few years. Ford is basically all-in on some CATL LFP partnership, having secured at least 60 GWh for through 2025 (on paper) and several other long-term deals for later; personally I think this is going to go poorly for them, reminiscent of the Foxconn debacle a few years back, but I leave room to be pleasantly surprised. GM appears to be working with LG Chem for high-nickel cathodes but on a significantly delayed schedule from their original plans. In neither case is it clear where the precursor materials are being extracted or refined, but I'd bet dollars to donuts it's mostly China. Best I can tell is these guys each expect around 120-150 GWh of annual production capacity sometime in the next few years. For reference, CATL makes around 30% of global Li-Ion supply and today has about 250 GWh of annual production capacity. I remain deeply skeptical of the US automakers' ability to execute on such lofty goals, particularly if they keep pumping out overpriced stinkers and falling behind on innovation, when their combined expectations for the next few years are to go from practically nothing to double-digit percentages of the global lithium battery supply, and all while buying their precursor materials at no-doubt strategically inflated prices from their primary competitor nation.

I'd estimate this EV investment is something like $35B in capital costs between the two of them. China is selling low-cost EVs to every other low-cost market on Earth, so once the US GHG rules kick in, it's not like Ford/GM can really continue selling ICEs at scale any more - they will be drawing down most of their existing propulsion facilities, which is something like 20% of each of their balance sheets (it's more like 25%, but some ICEs for heavy industry applications will still be required - that capacity will stay mostly unaffected). Sure, it's not $50B down the drain, but $10B and most of your ICE expertise down the drain is nothing to take lightly, let alone on top of another $15-20B in industry-redefining novel (at least to them) technology investment. And the massive capital investment, vertically-integrated manufacturing, and on-shore in-house production of battery components is exactly the opposite direction from where Ford and GM have been headed for the last 40 years.

My point is, don't underestimate the complexity or the expense of the challenges ahead for US automakers.

As an aside: The global readily available lithium supply is sorely inadequate for something as ambitious as the entire US automotive market going full electric by 2030 anyway. The WEF is projecting sixfold increase in lithium demand over 2020 figures, and even with optimistic projections on political and environmental mining and refining operation approvals, we're still talking like 6-8 years for operations to go from "we think there's lithium here" to mining and refining it at any kind of scale. And again that's with everything going right, which it very frequently doesn't: market conditions can delay financing, detailed surveys of lithium deposits can determine midway through that the deposit is economically nonviable to refine, governments can and do regularly inject arbitrary and capricious environmental demands. In practice, it can take over a decade for mining and refining operations to come fully online. Plenty are in-work right now, but it's just nowhere near enough. This fuels a lot of my skepticism regarding the ambitious annual production capacities discussed above.

Meanwhile: China is the recipient of something like 90% of Australian lithium, and between Australia, Chile, and domestic mines, China is consuming something like two-thirds of all lithium extracted on Earth. They follow it up with another 60% of the world's lithium refining capacity. Their domestic battery manufacturing companies are functionally unrivaled - CATL is routinely years ahead of everyone else on the market in metrics like gravimetric energy density, cost per cell, total throughout... China is the 800-pound gorilla of the EV industry, and since most of their cost for EVs is tied up in the battery, as long as China can keep producing better, cheaper batteries than the rest of the world, they'll trivially outcompete an unserious, labor-depleted, heavily outsourced, geriatric American automotive industry. From where I stand, at least, it looks like it will take a radical transformation of all major industry players just to survive the next decade, and without significant assistance from USG in tipping global trade scales to secure strategically valuable lithium assets and construct refineries in friendly jurisdictions, I can't see the US being globally competitive in manufacturing anything that needs a Li-Ion battery in it 20 years from now.

Can you provide a source for this claim? I don't find it hard to believe, but it warrants a lot more context than a single-sentence drive-by.

This feels familiar to the gender wage gap discussions: one side alleges their fact demonstrates prejudice and burden, the other side alleges an assortment of methodological trickery and revealed preferences...

And on the gripping hand, every major company in the US has several outreach/scholarship/early acceptance pipelines explicitly for promising young women and virtually zero such aid explicitly for men across all of them combined. I don't think there's any question that trans advocacy and institutional support exists within companies for transgender individuals - if not at all major companies, certainly at least at "high-status" ones.

Supposing you're correct that a substantial achievement gap exists between trans and non-trans individuals, this makes it all the more appealing to portray oneself as trans for all the usual affirmative action reasons, with the added bonus that, unlike pretending to be a different ethnicity, your transgender portrayal is fundamentally unfalsifiable: there is (to date) no biological evaluation that can be conducted to verify "transness." If you're a smart, talented, conscientious youth in the US, but you have trouble standing out against your enormous pool of peers and you have no affirmative action points in your favor, and you discover that you can pretend to be unfalsifiably, invisibly, inconsequentially victimized by your own body in order to cash in on a sudden surplus of free pity points (almost as good as affirmative action points, definitely better than nothing)... Even if you have to dress up, run a few circles around a shrink once a week, and pretend to be mad when people use the "wrong" pronoun, it doesn't sound all that demanding compared to what it already takes to break into a high-status job without knowing the right people. To be clear, it's not One Neat Trick to get a job or anything, it's just something that might improve your odds.

I've been begging the question, so I'll hold myself to account: what about the majority of transgender who are underperforming? Are they all faking it to stand out too? I suspect not, and I'd suggest that there's probably some social contagion and autism spectrum comorbidity effects at play, but my thinking here is underdeveloped. I have several years worth of direct evidence at my employer suggesting there exists a performatively transgender grifter class that isn't completely inept; and I think there's at least an order of magnitude more transgender people I'll never encounter who couldn't make it past the phone screening - I don't think they could keep up the grift, much less benefit from it. But even without having a very articulate theory of what's going on with the underperforming majority, I think both you and nybbler can be right at the same time, and that you're talking about two (at least, maybe more) very different cohorts, unfortunately captured under the same label.

I suppose incoherent, contradictory, frequently erroneous rambling, cheap low-effort barbs that deliberately mischaracterize forum regulars with years of coherent, level-headed history, and stubborn commitment to jackassery against a backdrop of numerous mod warnings and small-time bans is representative of an unsettlingly vast portion of the general polity. For some reason, I'm having trouble attaching these characteristics to Reagan or Bush. I don't think you're intentionally aiming to paint this major faction of conservatism as being fundamentally incompatible with the forum rules, but holding up Hlynka as an exemplar of crotchety conservatism in a thread where we explain why we banned him for being crotchety isn't making a stellar case for why we need more of that around here.

I do want to see more posters who can see the world through a Hobbesian lens, without succumbing to cynicism, tribalism, or conspiratorial ad-libbing. I can also appreciate simplifying the story around race relations and wokeness, much as I suspect such a project is doomed to fail. In the not-too-distant future I've been meaning to post at length about why the kind of conservative I'd like to see here is a particularly hard bar to clear for our forum - this ban may be a good catalyst.

I agree. I don't think many voters are impressed by some kind of self-congratulatory back-patting exercise for solving a problem the administration itself is responsible for exacerbating for the last three years. I mentioned this in a different comment, but for consistency I'll repeat it here: the more I think about it, the less I think the Biden administration wants a narrative about progress, and the more I think they just want the border and illegal immigration out of the news. They're in a bad position, largely of their own making, and now any attempt to bring the numbers down just comes off as cynical optics manipulation.

Earlier I implied that the administration wants to create a narrative about progress, but the more I think about it, the more convinced I am that they just want the numbers to go down and have everyone forget about the border and illegal immigration for a while. They don't get credit from the left or the right for reducing illegal immigration numbers: the left complains about denying the poor, impoverished families of their American Dream; the right assumes any attempt by the Biden administration to reign in illegal immigration is bad faith optics manipulation. I think at this point they're trying to stop the bleeding. I wouldn't say Biden "fell into" some political trap, so much as the administration got spooked into action by numbers and headlines they couldn't ignore, and Republicans see that kind of panic as a glowing red weak point.

Now the administration is under attack from a bad angle, and they have to respond or risk losing control of the narrative. If they had no response, this comes off as a tacit admission that the administration's border security policy has failed. As previously mentioned, over-reacting is also dangerous, since it hands the enemy obvious ammunition: "Why is Biden fighting so hard to let illegal immigrants in?" Getting a judicial ruling that explicitly negates Abbott's directives casts Abbott as a lawbreaker, and emphasizing medical emergencies portrays him as cruel, all without compelling Abbott to do anything. It plays well with the base, if conversations with friends are any indicator... prevailing left-wing opinion of Abbott can be roughly summarized as "crooked, deranged lawfare man," and pulling out "the judge said you're obviously wrong and bad" fuels plenty of sneering. Out of a handful of bad options, I think this is probably the best one.

There's also the optics of corpses piling up on the shores of a headline-news border crossing to consider. I'm sure the rank and file have enough genuine empathy in them to be alarmed and upset when Texas declares they have no obligation to rescue the injured or the dying, but this is still a pretty abstract concept - it's easy to say "people will die" without fully internalizing it. Compare with news crews finding piles of bodies and asking why Joe Biden lets Texas get away with it. That's the start of an uncomfortable conversation, and it keeps the border in the news. Now CBP has cover to keep cutting through Texas obstructions and keep the body count low.

Licht was fired as CNN's president and CEO in June 2023, after an article in The Atlantic revealed that employees had become unhappy with him over actions taken during his tenure.

So, that went well. Whether Zaslaw is still pushing for neutrality or not is unclear to me, but I'll grant that there's grounds to believe CNN is no longer a sympathetic media outlet.

In any case, here's the New York Times and the Washington Post. A brief Google search turned up similar anxiety across NPR, NBC, CBS, the AP, ABC, Fox (of course)... Even MSNBC started running interference in early January, and much like one can infer the rough outline of an object from the shadow it casts, here too we can infer the immigration-shaped issue from the article's calculated absence of context. Setting aside sympathies, record-breaking illegal immigration figures were inarguably headline news in December, and that's not a good look for Biden.

I recently read a Todd Bensman post that dropped the last puzzle piece in place. The Biden administration's illegal immigration policy (or lack thereof) just spent November and December in the spotlight, with even traditionally sympathetic media outlets raising eyebrows at the magnitude of border crossings and highlighting uncomfortable results in opinion polls. A handful of diplomatic meetings between the US and Mexico took place in late December, and in the opening weeks of January the Mexican government suddenly found an urgent need to shut down La Bestia, a train route traveling from Guatemala to the US border (technically with a "layover" in a Mexico City freight yard), and the primary corridor of illegal immigration from Central America for the entire Biden administration. Migrants are now being bussed to Villahermosa with increasing frequency and urgency, hot on the heels of the US diplomatic visit. Longitudinal flights from Piedras Negras (across the border from Eagle Pass) restarted concurrent to the diplomatic meeting (PDF, see last two pages - by migrant advocacy group Witness to the Border, so it's only an estimate, but probably close to accurate, especially for obvious signals like restarting known longitudinal flights). The Matamoros/Brownsville migrant camps were bulldozed at the end of December. There's a lot more actions taken in the last few weeks, but the upshot is that border crossings are way down, shantytowns aren't on nightly TV any more, and record-setting border crossings are momentarily a thing of the past.

I saw threads for the last two weeks wondering about Abbott's possible motivations. I believe comments like this illustrate the reason. The Biden administration is taking measurable steps to halt the flow of illegal immigrants (up to you if it's a genuine change of heart or just cynical ratings management), and the results have been observable. By picking a fight with the federal government now, Abbott shifts the frame from "the Biden administration is making measurable progress reducing illegal immigration" to "the Biden administration is fighting to make illegal immigration easier," which at a soundbyte level is a win for Abbott. Any subsequent moves the Biden administration makes to reign him in just turn into more headlines for Abbott, adding up to a serious perception problem at election day against Donald "Build The Wall" Trump. Consequently, the Biden administration wants to avoid escalation, and now they have a ruling in-hand that undermines any object-level obstruction by Texas without actually compelling Texas to do anything different.


  • Green is direct from the AI
  • Red is flagged as a potential TOS violation for manual review - I think it could be both prompt and AI output
  • No highlighting is prompt

Sometimes the output halted in weird spots, and you could push it a little further with some extra input. So in some cases, you'll see obvious prompt continuation.

In practice, the highlighting had a lot of issues, and it frequently over- or under-represented the amount of AI-generated content. The original author might have explained somewhere on Twitter how much prompt continuation was needed vs how much was just GPT-3 having weird issues. Or maybe the whole thing is secretly fake and green highlighting was added in post. Given the widespread production of similar bottomless pit greentexts in the wake of the original, I think it's probably real output.

In some sense, being a cleaned-up prompt continuation stitch feels a little bit like bumper rails at the bowling alley. It's a lot easier to perform well when you get that much additional guidance. Arguably the whole punchline is human-written, which moves the goalposts for this accomplishment from writing a spectacular joke unaided to filling in the world's most obvious madlibs blank... But remember, it only feels obvious to you and me. Out of all the words in the English language, GPT-3 correctly predicted the funniest one. It has a literal sense of humor. And that's pretty scary.

Bottomless Pit Supervisor made me feel like the floor dropped out from under me. Like we were headed for something dangerous. A lot of people had that reaction to GPT-3.5 when it started actually looking dangerous, but this stupid greentext was so perfect that it gave me that cliff's edge vertigo nearly a year early on GPT3. Every time I hear about AI progress, I think back to this meme as the moment I knew we were screwed.

There's basically always been an operation consisting of thousands of people looming just over the horizon, for more than a decade prior. Getting a few thousand guys together to cross the border and wreak havoc isn't much of a challenge, particularly given the very small size of Gaza and the distributed storage and management of weaponry across individual Hamas members - sending a few kids on foot or on bikes to spread the word on impending assault destinations and times is very easy, everyone mostly brings weapons they already had been given weeks/months/years ago for just such an event, and if the groups and destinations are determined even a little in advance then there's practically nothing left to do but go. I wouldn't be surprised if operations of that scale could be called up in a few hours, even factoring in planning time. And as others in the thread have noted, even well-prepared defenders can get caught with their pants down if the enemy makes an unexpected-enough move, so most of the ground-level chaos was caused while the IDF was still figuring out what was even happening.

What raises eyebrows is the size of the stockpiles of weapons, particularly the thousands of rockets launched out of Gaza on the day of the assault. Stuff that blows up doesn't tend to last long in Gaza, and the IDF regularly conducts operations to clear out ammo warehouses. Either they've somehow systematically missed thousands of stockpiled rockets over several years, implying Hamas has been unusually effective at keeping them out of sight over a prolonged period with many changing leaders... or a whole ton of rockets arrived at once from some sponsor, and were smuggled in on very short order by unknown means. I'd bet money on the latter.

My point is, it's entirely possible that a single well-exploited mistake allowing rockets to be smuggled into Gaza by the thousands was the difference between havoc and status quo for Israel this week. Right now, I don't think we can realistically conclude much about the competence of Mossad or western intelligence from single catastrophes, other than "they aren't perfect"; though I expect in the coming weeks we'll see lots more narratives and fingerpointing as Israel tries to understand how this happened and how to prevent it in the future. I definitely don't think there's any need to reach for conspiracy to explain the magnitude of the event, either; it's a sufficient, but hardly necessary, explanation to yield this outcome, and right now there's enough grieving people seeking retribution against someone as an emotional relief valve that basically any publicly visible conspiracy investigation is unquestionably compromised by emotion.

My best guess is, Hamas and Iran pulled a single good trick on Israel, and this sort of disaster was always one bad day away.

Create a Precision Repeat Offender Program (PROP)

A bit on the nose, eh? I can't tell if this was meant as a verb (i.e. the single line in this proposal propping up the rest of the bloviation), or as a noun (theater object to facilitate a more realistic performance). What a masterstroke.

Others have already mentioned that prosecution in the US is conditioned on local politics, that retail employees basically have their hands tied in responding to theft, and that there is a cultural factor encouraging and normalizing shoplifting and theft in subsets of big-city populations from a young age. This is probably the bulk of it. I'll add an unverifiable but anecdotally-reinforced personal theory that might have some effect on low-repetition shoplifting adding to overall increases from 2020 to end of 2022: I suspect wearing masks during the pandemic years (and indeed long after them for some people) tipped the scales on the risk-reward calculus for a lot of people, because a lot of people (wrongly) think they might get caught by facial recognition.

The local Walmart has large, conspicuous cameras set up at the doorways, ostensibly for recording crimes to be used in subsequent investigation or prosecution. That such subsequent investigation is rarely conducted is beside the point - to the average person, it sounds risky to get their face caught on camera while they're doing crimes. The marginal shoplifter could always wear a mask, but when they're the only one hiding their face, wearing their hoodie over their head indoors, or generally acting weird around cameras, they tend to stick out - it's not a stretch to imagine that the marginal shoplifter who's concerned about getting caught by cameras might also be concerned about looking obviously super suspicious. But when everyone's wearing a mask, hiding your face from the cameras is a free side-effect of a different normalized behavior. This might have emboldened a lot of marginal shoplifters.

This sounds convoluted, and probably doesn't have a huge impact relative to the other mentioned explanations... but a couple of low-income friends have insinuated to me that the masking requirements made them a lot less worried about getting caught by facial recognition in their own personal escapades, so I don't think I can discard it outright.

~576MP streaming at 30FPS with a FOV of 120 degrees

This is not quite right. Eyes have a huge overall FOV, but the actual resolution of vision is a function of proximity to foveation angle, and there's only maybe a 5° cone of high-resolution visual acuity with the kind of detail being described. Just taking the proposed 120° cone and reducing it to 5° is more than a 99% reduction in equivalent megapixels required. And the falloff of visual acuity into peripheral vision is substantial. My napkin math with a second-order polynomial reduction in resolution as a function of horizontal viewing angle puts the actual requirements for megapixel-equivalent human-like visual "resolution" at maybe a tenth of the number derived by Clark. None of that is really helpful to understanding how to design a camera that beats the human eye at self-driving vision tasks though, because semiconductor process constraints make it extremely challenging to do anything other than homogenously spaced CCDs anyway.

On top of that, the "30FPS" discussion is mostly misguided, and I don't actually see that number anywhere in the text; I only see a suggestion that as the eye traverses the visual field, the traversal motion (Microsaccades? Deep FOV scan? No further clarity provided) fills in additional visual details. This sounds sort of like taking multiple rapid-fire images and post-processing them together into a higher-resolution version, something commercial cell phone cameras have done for a decade now. This part could also be an allusion to the brain backfilling off-focus visual details from memory. It's unclear what was meant.

especially if you expect to catch up with the 14 stop DR, which might not even be possible with current sensors.

This is already a solved problem, and has been for at least five years. Note that in five years, we've added 20dB dynamic range, 30dB scene dynamic range, bumped up the resolution by >6x (technically more like 4x at same framerate, but 60FPS was overkill anyway), and all that in a module cost that I can't explicitly disclose but I can guarantee you handily beats any LIDAR pricing outside of Wei Wang's Back Alley Shenzhen Specials. And it could still come down by a factor of 2 in the next few years, provided there's enough volume!

In any case, remember that the bet isn't beating the human eye at being a human eye, it's beating the human eye at being the cheap, ready-today vision apparatus for a vehicle. The whole exercise of comparing human eye performance to camera performance is, and has always been, an armchair philosopher debate. It turns out you don't need all the amazing features of the human visual system for the task of driving, this is sufficient but not necessary for a solution to the problem. You need a decent performance, volume-scalable, low-cost imaging apparatus strapped to a massive amount of decent performance, volume-scalable, low(ish)-cost post-processing hardware. It's a pretty safe bet that you can bring compute costs down over time, or increase your computational efficiency within the allocated budget over time. It's also a decent bet that the smartphone industry, with annual camera volumes in the hundreds of millions, is going to drive a lot of that camera manufacturing innovation you need, bringing the cost down to tens of dollars or better. Most of the image sensors are already integrating as much of the DSP on-die as possible, in a bid to free up the post-processing hardware to do more useful stuff, and that approach has a lot of room to grow in the wake of advanced packaging and multi-die assembly innovations in the last ten years. All the same major advances could eventually arrive for LIDAR, but it certainly didn't look that way in 2012, and even now in 2023 it still costs me a thousand bucks to kit out an automotive LIDAR because of all the highly specialized electromechanical structures and mounting hardware, money I could be using to buy a half-dozen high-quality camera modules per car...

As far as reaction time, real-time image classification fell to sub-frame processing time years ago, thanks in part to some crazy chonker GPUs available in the last few years. There's a dozen schemes for doing this on video, many in real-time. The real trouble now is chasing down the infinitely long tail of ways for any piece of the automotive vision sensing and processing pipeline to get confused, and weighing the software development and control loop time cost of straying from the computational happy path to deal with whatever they find.

This is also why I think Tesla's software just sucks. It's not the camera hardware that's the problem any more, and the camera hardware is still getting better. There's just no way not to suck when the competition is literally a trillion-dollar gigalith of the AI industry that optimized for avoiding bad PR and waited an extra four years to release a San Francisco-only taxi service. Maybe if Google was willing to stomach a hundred angry hit pieces every time a Waymo ran into a wall with the word "tunnel" spray-painted on it, we'd have three million Waymos worldwide to usher in a driverless future early. I doubt Amazon has any such inhibitions, so I guess we'll find out soon just how much LIDAR helps cover for bad software.

Your "doesn't get the job done" link doesn't seem to go anywhere... I had to clip out everything past the "mediaplayer" portion of the URL to get to the video, where a tesla slams into a test dummy. But it doesn't take much work to find counterexamples, and this wouldn't be the first time someone fabricated a safety hazard for attention.

I don't think LIDAR is as big of a differentiator as tech press or popular analysis makes it out to be. It's very expensive (though getting cheaper), pretty frail (though getting more durable), and suffers from a lot of the same issues as machine vision (bad in bad weather, only tells you that landmarks have moved rather than telling you anything you can do with this info, false positive object identification). And this is trite, but remains a valid objection: human vision is sufficient to drive a car, so why do we need an additional, complex, fragile sensor operating on human-imperceptible bandwidth to supplement cameras operating in the same bandwidth as human eyes?

Tesla's ideological stance on machine vision seems to be: if camera-based machine vision is insufficient to tackle the problem, we should improve camera-based machine vision until it can tackle the problem. This is probably the right long-term call. If they figure out how to get the kind of performance expected from a self-driving system out of camera-based machine vision, not only have they instantly shaved a thousand bucks of specialty hardware off their BOM, arguably they've developed something far more valuable that can be slapped on all variety of autonomous machines and robotics. If the fundamental limitations are in the camera, they can use their demand in automotive as leverage to encourage major camera sensor manufacturers to innovate on areas where they currently struggle (high dynamic range, ruggedness, volume manufacturability). Meanwhile, there's a whole bunch of non-Tesla people working independently on many of the hard problems in the software side of machine vision; some of the required innovations in software don't necessarily need to come from Tesla. And if it does need to come from Tesla, they've put enough cameras and vehicle computing out in the wild by now that they could plausibly collect a massive corpus of training data and fine-tune it better than pretty much any other company outside of China.

Google, meanwhile, had years of headstart on Tesla, a few hundred billion dollars of computers, at least one lab (possibly several) at the forefront of machine vision research, extremely deep pockets to buy out tens of billions of dollars of competitors and collaborators, limited vulnerability to competitive pressure or failure in their core revenue stream, and a side business mapping the Earth compelling them to create a super-accurate landmark database for unrelated business ventures. I think the reason Google's self-driving vehicles work better than Tesla's is because Google held themselves to ludicrously high standards, half of which were for reasons unrelated to self-driving, and the likes of which are probably unattainable for more than a handful of tech megacorps. That they use LIDAR is immaterial - they've been using it since well before the system costs made commercial sense.

As for the rest of Tesla's competitors... when BigAutoCorp presents their risk management case to the government body authorizing the sale and usage of self-driving technology, it sounds a lot more convincing to say "cost is no obstacle to safety" as you strap a few thousand bucks of LIDAR to every machine and spend another few dozen engineering salaries every year on LIDAR R&D. A decade of pushing costs down has brought LIDAR to within an order of magnitude of the required threshold for consumer acceptance. I'll note that comparatively, camera costs were never an obstacle to Tesla's target pricing or market penetration. Solving problems with better hardware is fun, but solving problems with better software is scalable.

That's not to say Tesla's software is better though. I can't tell if Tesla's standards are lower than their competitors, or if their market penetration is large enough that they have a longer tail of publicized self-driving disasters to draw from, or if there's a fundamental category of objects their current cameras or software can't properly detect. Speaking from experience, I've seen autopilot get very confused by early-terminating lane markers, gaps in double yellow for left turns, etc. I think their software just kinda sucks. It's probably tough to identify the performance differences in good software with no LIDAR and bad software with LIDAR; comparatively much easier to identify bad software with no LIDAR. And really easy to blame the lack of LIDAR when you're the only people on Earth foregoing it.

Phonological and morphological awareness do seem to be well-correlated with literacy outcomes both in alphabetic and non-alphabetic languages, and there's a lot of meta-analyses which show about the same low-moderate correlation in Chinese primary language learners as in English primary language learners. There's some studies that show cross-language transfer in English/Chinese bilingual households for phonological and morphological awareness, but no such transfer for orthographic awareness, which seems to suggest there's something fundamental about the cognitive process of organizing and mapping the set of graphemes and meaningful constructive subsequences in the written language to its equivalent phonetics and trivial phonetic expansions, which is independent of a language's orthographic characteristics.

In any case, I don't think there's any dispute that written Chinese has semi-consistent phonological and morphological structure. The majority of Chinese characters are horizontally structured phono-semantic compounds with a semantic left radical and a phonetic right radical (maybe 70-80%); around half are phonologically regular regardless of tone; and there's only a few hundred common semantic and phonetic radicals. There's clearly a massive encoding and decoding efficiency achieved through semi-consistent phonological mapping of the orthography.

It's really hard to find trustworthy or low-bias takes on this topic. There's a vivid, unsettled debate about how exactly the Chinese literacy rate improved (from <20% in the 1950s, to ~96% by the 2010s), and to what extent the introduction of simplification, pinyin, etc played a role. People get downright vicious in these discussions because they tend to get deeply involved in Chinese idpol culture wars. The debate has its own Wikipedia page. I don't place that much confidence in my understanding of how it all fits together, especially through the fog of culture war - this is a mind-bogglingly complex topic. My basic understanding is that opinions vary widely, from believing that simplification (and possibly pinyin, significantly more controversial) fundamentally enabled mass literacy, to believing it was purely a result of herculean educational investment and widespread literary access (and even that simplification/pinyin was reformist nonsense or foreign interference), with huge diversity of opinions on the relative weights of every effect within that spectrum. It seems fairly uncontroversial that China pre-1950s did not have widespread educational access, and that what access existed was often printed in traditional characters or unique regional characters that the masses could not feasibly learn without dedicated scholarly investment. The literacy rates are also undisputed. I don't think it has much relevance to the question of how Chinese children today learn to read, but it's nevertheless an interesting sideshow.

Speaking as someone in the chip industry, we most certainly do rely on China.

The Chinese market is massive, and was, until recently, growing at an eye-watering pace. I know of a few companies that took 20%+ off the balance sheets permanently when the Huawei sanctions hit a few years back. Even if the latest sanctions target advanced capabilities and leading-edge chips, these are still the centerpieces of designs with millions of units of volume (particularly in telecom, for 5G deployment and Chinese Android phones sold across the world), and less-advanced companies had many roles in these systems which are now jeopardized. Chinese electronics and electronics-adjacent industries, even those not relying on advanced chips or tools, are no doubt eyeing the latest round of sanctions with concern that their niche will be next. Semiconductor sales volume to China is going to slow down a lot for the next year or two, which is going to do damage to companies whose growth strategy was dependent on the continued growth of that market.

I'm less knowledgeable about the specifics on this part, but I also recall as little as a few years ago that the semiconductor packaging expertise cultivated in China is unrivaled, particularly its ability to scale. The more advanced devices nowadays bond the die to a PCB-like substrate material with extremely fine pitch routing on many layers of high-density film, to famousfanout the contact points on the die to reasonable pitch and to improve signal/power integrity. While in theory the manufacture of the substrate and the bonding of the die can be done anywhere, China offered an unrivaled combination of rapid turnaround, high volume, and excellent quality (provided you knew where to look). There's a lot more packaging techniques developed and scaled in China, I just picked this as an example I remember; with chiplet designs for processors and chip-stacking technologies for flash memory, packaging is getting more demanding by the day. There's no explicit sanctions on this packaging equipment as far as I can tell - packaging is something the fab can contract out to a third party, and I suspect the sanctions are targeted narrowly on fab companies. Will large US semiconductor companies still need to process their finished dice in China, presenting additional risks for export control? Will the US summon up another round of sanctions to decapitate the packaging industry as well? Perhaps the industry has quietly de-risked itself over the last few years, but I can't find evidence of this with trivial googling.

Anyway... we do rely on China, quite a lot, for both market size and post-fab manufacturing. Sanctions aren't doomsday, but definitely more than a haircut.

And that's before considering the possibility of TSMC catching some "errant" missiles in a hypothetical conflict (much less hypothetical than two weeks ago, to boot), knocking over more than half of worldwide advanced semiconductor production.

The report in source 2 of gp actually addresses this...

Research by the Office of Immigration Statistics replicates the Fazel-Zarandi et al. methodology and assesses the possibility that the size of the unauthorized population was in the range of 16.2–29.5 million on January 1, 2017 as Fazel-Zarandi et al. conclude, rather than 11.4 million as the DHS residual model estimates. One key finding is that the difference between FazelZarandi et al.’s results and DHS’s residual model is entirely driven by high estimated growth in Fazel-Zarandi et al.’s model during the 1990s—yet key data required for inflow-outflow modeling are not available for those years. These data limitations, along with a number of questionable modeling assumptions, give DHS no confidence in Fazel-Zarandi et al.’s findings about population growth in 1990-2000. A forthcoming DHS whitepaper includes a preliminary inflowoutflow analysis that is similar to the Fazel-Zarandi et al. method but updates certain assumptions and makes fuller use of DHS data for 2000 – 2018; the paper finds support for the DHS estimate of about 11.4 million people as of Jan. 1, 2018 (Rosenblum, Baker, and Meeks, forthcoming).

Can you help me understand how you arrived at the conclusion that visa overstays are the largest group of illegal immigrants in the US? I looked at the overstay reports and I see a somewhat consistent estimate of about 700k per year. 25% of 2M is 500k, but it only represents actual encounters, so I'd expect this number to be the sum of the encounters released and the non-encounters. If even 10% more illegal immigrants are crossing without an encounter, it seems to me that the rate of growth of non-visa overstay illegal immigrants is larger, especially as of the last few years. Is the argument that the total visa overstay population is still larger than the total illegal southern border crossing population? I didn't see estimates for either of those numbers in the overstay reports.