I actually agree with you in principle. I taught math and philosophy at a community college after getting my CS degree, before transitioning to corporate America as a sysadmin on steroids. You do have a point. It’s your classroom, and you’re right that none of us really knows what the future looks like. As Heinlein put it, “Stupidity is the only sin in nature. Judgment is swift; the punishment, harsh. And there is no appeal—you live and you learn, or you don’t live long.” You rightly grok that grounding students in clarity of thought and persuasive articulation is the right thing to do.

But I want to push back on a couple of your assertions. “Coding” as a universal future-proof skill always felt like a reach, and I’m not sure what stake a humanities professor has in it. More importantly, I don’t buy your framing around autonomous thinking. How autonomous is a carpenter who isn’t allowed to use a saw? How does banning tools make craftsmen better? A tool doesn’t abolish autonomy; it enables mastery. Denying students AI doesn’t prepare them for the future they’re walking into—reread Heinlein's quote--it just deprives them of learning how to collaborate with a force already shaping their world.

AI isn’t a replacement for human reasoning. At its best, it’s a collaborator—an amplifier of judgment, not a substitute for it. The hard part is managing that dynamic in the classroom—keeping the line between the student’s work and the LLM’s work bright and sharp. I agree with your sentiment: if that line blurs, it risks compromising the student’s growth and undermining academic integrity. The challenge is that you’re also in a position to model how to get it right. Preparing students for that reality seems just as important as teaching them to write a persuasive essay without any tech at all.

I remember when “online classes” were basically diploma mills farming credential seekers who figured an MS or MFA would boost their career options. Nobody who took education seriously considered them legitimate—the same way upper management quietly ignored “University of Phoenix” or “ITT Tech” listed on a résumé. If your education came from one of those places, you weren’t educated. You were just a credentialed cosplayer.

Covid changed that. The pandemic gave online education a shot in the arm (pun intended), and what started as a stopgap metastasized into something our cultural immune system has never learned to fight off. Suddenly, entire universities digitized their classrooms wholesale. And once the line between “school” and “screen” blurred, it stayed blurred.

Now Google, with its Chrome homework help button, has taken the next step—turning the browser itself into a cheat sheet. The tool may be paused for the moment, but the damage is done. Students are being trained to see the shortcut as normal, even sanctioned. What was once a diploma mill has become a distributed millstone, dragging down the very idea of intellectual integrity.

AI isn’t the culprit here. This rot began the moment we accepted that an “online class” could substitute for human presence, accountability, or the messy give-and-take of real learning. Covid forced the shift, and we are left with the consequences: an educational ecosystem where Big Tech sets the terms, and teachers scramble to defend whatever fragments of rigor remain.

The diploma mills at least had the decency to look tawdry. Chrome’s button arrived polished, market-tested, frictionless—and all the more corrosive for it.

Interesting article. The paper is pretty interesting, too. Pangram Text, is an AI detector that claims 99% accuracy spotting machine-generated text. Impressive benchmarks, clever tricks (mirror prompts, hard negative mining), and a lot of self-congratulation about finally solving the “who wrote this?” problem. But if you peel it back, what you see is the same old cat-and-mouse game with plagiarism we’ve been playing since middle school kids first discovered they could plagiarize an encyclopedia entry for a term paper -- with a little help from a thesaurus and Strunk and White's "Elements of Style."

Pangram trains itself to sniff out statistical fingerprints left behind by LLMs. But the very same process can run in reverse: an LLM (or a motivated human) can train against those signals and wash them out. Every detection method is also a recipe for camouflage.

Humans already have an intuitive “detector” for voice and tone. We know when something doesn’t sound right, and we edit until it does. That act of injecting our quirks, biases, and rhetorical jagged edges into our writing is exactly what breaks the smooth, distributional fingerprints Pangram is keying on. In other words, the best obfuscator is a human being human. History says this detection arms race among the LLMs ends in a stalemate. Spam filters, plagiarism checkers, CAPTCHAs — all followed the same arms race curve. Detectors get better, camouflagers get better, and eventually the false positives overwhelm the system, unfairly flagging everyone from non-native English speakers to creative writers. Pangram admits as much between the lines: they’re state-of-the-art “for now."

That’s the uncomfortable reality: detectors like Pangram can tell us whether some text smells statistically AI-ish, but they can’t arbitrate authorship in any meaningful sense. Watching Rodin with hammer and chisel in hand, you’d say, “Here’s a sculptor about to go to work.” But Rodin didn’t just see marble — he saw Dante’s caryatid crushed under her stone in The Gates of Hell. So who’s the author of that sculpture? Rodin, who cut the stone? Dante, who first gave form to the torment? Or you, the observer, who decides what it means?

Now swap the marble for some vectorized token chain residing on a contour in some Hilbert space composed of billions of vectorized token chains. The LLM produces a new token chain from a statistical guess at a trajectory through that Hilbert space. It is then edited, and reshaped by a human, and fed back into the LLM. Wash, rinse, and repeat. But where is the authorship? That lives in the messy middle — a collaboration between machine and human, with a bunch of textual prompts connecting them. The line isn’t just blurred. It’s gone.

The broad concern from this poll is clear: half of Americans say they’re more worried than excited about AI in daily life. But a key finding that truly crystallizes the issue is this:

76% of Americans say it’s extremely or very important to be able to tell if content was made by AI—yet a majority, 53%, admit they aren’t confident they could actually do it.

That disconnect is dismaying, because deception isn’t new. Politicians shape stump speeches into whatever “reality” sells. Propaganda, advertising, and courtroom rhetoric are all exercises in selective distortion. Starting with the ochre splashed on the walls of Lascaux and continuing through centuries of myth and image-making, human culture has always blurred the line between truth and narrative.

We happily suspend disbelief for cinema or literature, but we are appalled and recoil when the same fakery is spilled across our screens in our newsfeeds. The context has changed, yeah -- in the theater you willingly suspend your disbelief. But why are humans so willing to suspend it when it comes to their newsfeeds? Why is AI the bogeyman, here? AI doesn't change the fact that most humans lack critical reasoning skills, while some are exceptionally adept at exploiting that lack. AI hasn’t made us worse at spotting deception; it has simply made it obvious how bad we’ve always been. The real question isn’t whether we can perfectly separate “real” from “fake.” It’s whether we can re-calibrate our critical reasoning for a world where fakery is frictionless and narrative is weaponized.

AI isn’t the problem. It’s the mirror.

So let’s get this straight: a MAGA true-believer shoots and kills a MAGA kingmaker, and the MAGA-chaired House Oversight Committee’s big takeaway is call in the CEOs of Discord, Steam, Twitch, and Reddit? Comer calls Kirk a “patriot” and frames this as proof of “radicalization of online forums.” What’s missing in Comer's script is the part MAGA refuses to acknowledge: the shooter wasn’t some “Antifa super-soldier” conjured from MAGA fever dreams. The shooter was one of their own -- just read his social media.

Instead of grappling with how grievance-politics metastasize inside their movement, the MAGA nutbars running the Oversight Committee are doing what the MAGA nutbars above them are demanding: find a scapegoat, any scapegoat, and get the spotlight off of MAGA. Their choice? Silicon Valley. Drag in some gaming-focussed CEOs, grill them on their platform's “nefarious purposes,” and hope the ensuing headlines bury the fact that a hate-spewing MAGA mouthpiece was silenced by a hate-filled MAGA nutbar's rage. Let's be clear, here: Kirk spent a decade cultivating that rage. He reaped what he sowed.

Apple said they’d never cave,
Touchscreens weren’t their game,
walled gardens are their claim to fame,
But here we are all the same

Come on, come on, come on, come on —
And touch me, babe, can’t you see
That’s the feature they resisted endlessly!

Now OLED shines so bright,
M6 dreams at night,
Steve said “no” back in the day,
But now Tim says we can win that fight

Come on, come on, come on, come on —
Touch me, babe, can’t you see
The market is not afraid, what was that promise that Tim made?

Come on, come on, come on, now touch me babe!

With apologies to Jim Morrison and the boys... :)

Hmmm. Back in my cold warrior days, it was the Iron Curtain. This is starting to remind me of that. Back then, Moscow tried to wall off Western goods and information; today, Beijing is walling out Western GPUs — ironically not to restrict information, but to accelerate it on homegrown silicon.

CAC’s ban on Nvidia AI chips forces Alibaba, ByteDance, and others to buy Chinese accelerators (Biren, Moore Threads, Huawei Ascend). The short-term hit is performance; the long-term play is industrial policy — subsidies plus captive demand to build a self-sufficient AI stack. For Nvidia, AMD, and Intel, it’s a hard cutoff: export restrictions from Washington on one side, Chinese bans on the other.

The result is a bifurcated tech world. U.S. + allies double down on Nvidia, AMD, Intel, and hyperscaler silicon (Google TPUs, Amazon Trainium, Microsoft Athena, Meta’s in-house chips). China builds its own ecosystem behind their silicon curtain. Standards and frameworks are going to fracture (Huawei 5G, anybody?) Only this time, the wall isn’t made of barbed wire and checkpoints -- it’s wafers, fabs, and platform lock-in. That means redirection of focus to Europe, India, and the Middle East — where U.S. tech giants are already announcing multi-billion AI buildouts. Huang's direction here is pretty clear -- he all but told Wall Street don’t model China revenue. Given the Chinese market once drove 20–25% of Nvidia's revenue, Wall Street had better pay attention. :)

Domestically, I'm thinking Washington will harden its stance in a couple of ways. Xi basically just told Trump to take his "AI tariff" and shove it -- the 15 percent of H20 China sales Trump extorted from Nvidia just vanished. Xi won that round, bigly. Be interesting, though, to see how the more rational people in this benighted administration respond. I'm thinking more subsidies for TSMC Arizona and Intel Foundry. But I also see even more draconian export policing from the MAGA nutbars. Get out the popcorn; this only going to get stupider with Trump trying to call the shots in a game that he has no clue about.

Socrates...is that you? :) Well said.

You are most welcome. As my favorite sci-fi wordsmith Robert A. Heinlein pointed out, “Anyone who cannot cope with mathematics is not fully human. At best he is a tolerable subhuman who has learned to wear shoes, bathe, and not make messes in the house.”

Any help I can provide you in achieving sapiency is my pleasure to provide.

I’ve got bad news for you, too: it’s called non-linear scaling. The stresses and torques at 95 m don’t scale linearly, Fatigue, resonance, and aeroelastic behavior all get more brutal the longer the blade gets. Math has no mercy, and neither does fatigue stress and resonant frequencies. The GE engineers had to solve several trade-offs; basic physics constrained them to 68.7 m. The catch is that root bending stress grows with the square of blade length, while the natural bending frequency drops with the square. That means when you jump from ~70 m to ~95 m, you almost double the stress and cut the frequency in half — putting resonance right in the range of rotor harmonics and gust energy. Blades are deliberately tuned to keep those resonant frequencies out of harm’s way, and the longer they get, the harder that tuning fight becomes. So yeah, two-piece blades are real, but the leap from ~70 m joins to ~95 m joins isn’t just “add a few more bolts.” It’s a whole new problem set. When you've grokked the engineering math, come back and we'll continue this discussion, ok? I suggest you start your education with Euler-Bernoulli beam theory.

I do like the airship “what if” angle — blades are long and (relatively) light, so on paper it seems tailor-made for buoyant lift. I've already posted about it, elswhere in this thread.

The catch is handling. A 95m blade slung under an airship turns into a weather vane the size of a football field. Crosswinds, gusts, even wash from the stabilizers during takeoff/landing would make it a nightmare to keep stable. Then once you’re down, you’ve got the classic LTA problem: mooring a giant balloon in real-world wind -- and there is going to be a lot of that, especially if the destination is a wind farm. :) Honestly, wind is why airships never really solved heavy cargo despite the payload advantage.

So yeah — cool idea, and I like thinking about it too. But in practice the “free lift” just buys you a new set of headaches. Big ones. :)

Yeah, I had the same thought — the trick is that a 95–100m blade is less “dead weight” and more “giant sail.” Even if you scale a helo to sling 35 tonnes, you’re still fighting rotor wash, gusts, and control oscillations the whole way. Not saying it’s impossible — a “Skycrane on steroids” is a cool mental picture — just that the physics gremlins don’t go away, they just move around.

I’m genuinely impressed with the fixed-wing design they’re proposing to haul 95-meter blades. That’s not “strap it to the roof rack and hope for the best” engineering — it’s a clean-sheet aircraft designed to wrap itself around a renewable energy problem. Respect.

But my inner contrarian couldn’t resist: what if we dusted off lighter-than-air?

On paper, it almost makes sense. Those blades aren’t dense hunks of steel — they’re long, fragile aerofoils weighing maybe 35–40 tons apiece. That’s a volume problem, not a mass problem. Buoyant lift was born for that kind of cargo. Picture a modern cargo airship, two blades slung under its belly like chopsticks, floating from port to installation site.

Of course, reality is a cruel engineer:

Wind sensitivity: Giant balloon + giant blades = crosswind hell. Even with AI vectored thrusters, gusty weather would turn every flight into a white-knuckle simulator run.

Ground handling: Mooring a 200-meter airship with unwieldy cargo is not exactly “pull up to the gate.” It’s a dance involving tethers, winches, and crews large enough to look like a Graf Zeppelin re-enactment society.

Economics: Slow cruise speeds and weather holds are poison to project schedules. Every extra day those blades aren’t spinning is money lost.

Still, there’s something about it that scratches the “I like a challenge” itch. LTA wouldn’t be faster, cheaper, or easier than the fixed-wing plan — but it might be a different kind of elegant. Less brute force, more "float it gently like a leaf across the sky."

I’m not pitching this as a better solution. The fixed-wing aircraft is the real thing, and it’s an excellent solution to the problem of dragging a 100 meter long telephone pole around the country on highway infrastructure never meant to accommodate this cargo's geometry. But part of me likes the idea that LTA is still out there in the margins, waiting for some lunatic engineer to say: “Yeah, let’s try it.” As my friend Hunter used to say, when the going gets tough, the tough get weird. :)

No, you are not. The “I’m totally pro-X, but” preface is a tell. It’s rhetorical Kevlar for what follows, not an argument. My guess is you are a fossil-fuel shill, not a serious commenter. If you’re “all about wind,” you should know the logistics wall we’re hitting with 90–100m blades and why new transport concepts exist in the first place.

False premise, twice. First, nobody’s proposing to chainsaw national forests so an outsized cargo bird can cosplay a 747. These aircraft concepts are designed to use short, semi-prepared strips sited on already-open terrain (prairie, pasture, fallow fields, deserts) near the project—then reclaimed. Second, air delivery shrinks—not expands—the footprint compared to today’s miles of widened switchbacks, blasted hairpins, and tree-clearing for oversize trucking turn radii. One graded strip near the site plus a short last-mile haul beats carving a serpentine road corridor across counties to drag a 95m telephone pole around corners.

What’s “half-thought” is assuming the bottleneck is runway grass, not physics and geometry. The whole point is that ground transport is choking on bridge limits, curve radii, and slope constraints long before you even get to aerodynamics. Building a vehicle around the load (the blade) is literally the opposite of half-baked—that’s standard heavy-lift engineering.

Pick a lane. Either access is “surprisingly little impact,” in which case a temporary strip near the pads is a rounding error—or access isn’t little, because anyone who has escorted oversize loads knows those “back roads” become widened curves, shaved cutbanks, and permanent turnouts to swing a 95m blade without planting it in the trees. Air delivery reduces the number of places you have to permanently deform the landscape.

Seriously? Just imagine if drive-by slashdot trolls understood mechanical engineering. A 95-meter blade carries gigawatts of cyclic bending and torsion through continuous carbon and glass fibers. Cut those fibers for a bolted joint and you’ve destroyed the very thing that gives the blade its strength, forcing all that stress through a splice or sleeve — the weakest possible link. Even if you bury the joint inside a fairing or coating, the tips are moving at more than 300 kph -- any discontinuity in stiffness or surface finish risks tripping the boundary layer and shredding efficiency. Turbine blades also flex millions of times a year for decades, and a even a hidden joint would still create micro-slips and stress risers — a fatigue factory, not a long-life structure. Add to that the fact that blades are tuned so their natural resonances stay out of operational ranges; drop in a splice and you shift mass and stiffness where it matters most, leading to tower resonance, gearbox grenades, and very expensive noise. And even if you somehow engineered the perfect internal splice, you’d still need to prove to insurers and certifiers that it can survive twenty years of salt spray, UV, lightning, and cyclic loading — a test program that would cost more than building the custom transport aircraft in the first place.

This is why engineers designed the aircraft around the blades — not the other way around. Structural integrity and aerodynamic continuity are non-negotiable. “Just bolt it together” isn’t an idea; it’s cosplay engineering for people who think physics bows to their snark.