dahart

> This company had designed cars for about 120 years at that point but still seemed to commit easy mistakes…

Oh take a look at the recall list of any car company in the world and you will find they all make simple mistakes, constantly. Probably a consequence of price pressure at all times. While cars are lasting longer than they used to on average, I feel like it’s been getting worse in some ways with cars lately turning into computers and good car/engine companies lately turning into bad tech companies without that much tech experience who outsource important parts and do lousy integration. And yeah, building assemblies or modules with non-replaceable parts is becoming more common.

> I’m not sure why it matters whether we use an absolute scale. In another couple years, LLMs will trounce everybody on every topic.

Whether intelligence is innate or trained, and what the absolute scale is, matter tremendously for national education policy, not to mention food, pollution, finance and everything that contributes to outcomes. Your examples are mainly based on differences in training. The main difference between particle physics and fractions is school, not cortical thickness, right?

Personally I also care whether the narratives we share and the public conception of intelligence is true and accurate or not. There absolutely are cultural biases surrounding intelligence that affect society and affect how people treat each other. If intelligence is trained, then we know we can focus on training. If intelligence is largely genetic and not training (or SES or nutrition, etc.) then grouping kids by ability is more justified than otherwise. If the biological component of 2 standard deviations above the mean in intelligence is relatively small (like it is for many other physical traits) then the term “gifted” is exaggerating reality, in addition to any mis-attribution of the source of the difference that the word implies.

Is LLMs getting better a reason to stop learning or stop caring about education & education policy? LLMs only got where they are by humans showing them everything humans wrote, right? I don’t see how LLMs improving changes anything with respect to teaching humans or measuring human ability. One thing that LLMs or AI in general might help enable is teaching kids at their own pace. The whole reason we teach kids in groups by age is because it’s easy and scalable. If each kid had her/his own teacher, then making the timing of the curriculum adaptive becomes feasible. Maybe AI-supplemented teaching will open this door, though there are still valid reasons to keep kids interacting and learning along with other same-age kids.

> I don’t know what this means

A hypothesis or model that’s unfalsifiable broadly means it’s unscientific. You can read the Wikipedia section I liked to, and follow the citation if you want.

“John Horn and John McArdle have argued that the modern g theory, as espoused by, for example, Arthur Jensen, is unfalsifiable, because the existence of a common factor like g follows tautologically from positive correlations among tests. They contrasted the modern hierarchical theory of g with Spearman's original two-factor theory which was readily falsifiable (and indeed was falsified).”

Horn, John; McArdle, John (2007). "Understanding Human Intelligence". In Cudeck, Robert; MacCallum, Robert C. (eds.). Factor analysis at 100: historical developments and future directions. Mahwah, N.J: Lawrence Erlbaum Associates. ISBN 978-0-8058-6212-6.

Musical and artistic ability both have in fact been associated with intelligence by many people for thousands of years; many musicians and artists have been called “geniuses”. I don’t know what intuitive sense you’re referring to wrt music, but you’re certainly not speaking for us all.

> I get riled up when I hear opinions that many lead to support for abolishing gifted programs.

Ah I see! Thanks for explaining; this is a critically important piece for me to understand why you’re reacting so strongly. I don’t support abolishing accelerated programs, so relax; I think you’re making some assumptions and jumping to conclusions. I have heard here on HN from parents reporting there are public schools in California and elsewhere that have been doing away with accelerated academic programs, and many parents and kids are extremely frustrated.

Note the paper I linked to at the top supports you:

“Ability grouping, which is perhaps the next best-supported practice in gifted education, is likewise implemented relatively rarely. This failure of schools to use practices that are known to be effective is not the case in other areas of special education, where the use of evidence- or research-based best practices is often mandated in policy”

FWIW, I was segregated into a small accelerated program in the 5th grade, and dropped into a high school, which came with its own set of problems. They didn’t use the word “gifted”, though, and I’m glad.

My feeling on the why the word ‘gifted’ is bad is two parts: it incorrectly assigns ability only to nature, when we have plenty of evidence that intelligence has many environmental factors, and calling it ‘gifted’ might be dramatically overstating how much smarter the top 5% of kids are compared to the mean or the bottom 95%. I agree there’s some utility in classifying kids, or at least understanding their individual educational needs and letting them go at their own pace. Calling them “gifted” (like the article we’re commenting on explains) sends the wrong message, both in terms of accuracy and in terms of what parents and educators should do about it.

Kids who are classified as ‘gifted’ don’t necessarily perform well in school, the Wikipedia article on g points out. And intelligence factors change somewhat over time. It would obviously be bad to measure all 5 year olds only once and then put them on educational tracks that can’t ever change, to decide who’s “gifted” and who’s not and assume there is zero fluidity, right? But that’s the history of the word “gifted” - it was chosen by someone over a hundred years ago, and it was specifically chosen to underscore the idea that there is an innate and unchanging raw intellectual ability. We know better now, and we should pick terminology to match, right?

BTW might be worth discussing that kids who aren’t “gifted” benefit developmentally from social interaction with kids who are “gifted”. This does make education policy legitimately more difficult.

> it’s very possible that g helps with musical ability and painting ability too.

The development of g rests on that assumption, but the measured correlations vary, and the correlations are lower for music & painting than between, e.g., STEM subjects.

Also interesting - the cross-subject correlations g measures actually decrease as intelligence increases. The smarter someone is (as measured by psychometric tests), the more likely they are to be “smart” in a single subject and not all subjects. This is an interesting self-contradiction in the whole theory.

> It makes perfect sense to me that socio-economics would correlate.

Yeah, I totally agree. But, it’s very important to know that the people like Spearman and others who developed IQ and g and other concepts of intelligence in the 1920s were specifically looking for the innate biological component of intelligence that explains “gifted” ability in the absence of nurture and environmental factors. That’s where this use of “gifted” came from - it’s pre-supposing that intelligence was not heavily influenced by the wealth of your parents, and they didn’t know how important nutrition and pollution were at the time. This is why I think using “gifted” is problematic. From that paper I linked to: “Reframing ‘gifts’ as ‘talents’ underscores both the domain-specific nature of these abilities and that their extent should be viewed as dynamic rather than static or preordained.”

One question that occurs to me - who are these gifts bestowed by? There are two obvious answers: nature and God. I think nature is historically what is meant by ‘gifted’ in the context of education, but I’ll speculate there’s at least a little bit of historical religious influence on the choice of that word. Given that we know that SES, nutrition, environment, education, parenting and many other factors have real measurable influences on both intelligence and outcomes for people, the nature & God explanations are somewhat lacking, right?

The concept of g is not without plenty of critique, like IQ its origins are from eugenicists, that it doesn’t track known biology, and that it’s unfalsifiable. The concept of g is that there’s a correlation in performance across multiple subjects, the evidence does not show the correlation is 1.0 - the average correlation is more like 0.6. g is particularly bad at explaining musical talent. https://en.wikipedia.org/wiki/G_factor_(psychometrics)#Criti...

I’ve never read something arguing that intelligence doesn’t exist (and I certainly wouldn’t buy such an argument). I just don’t think intelligence is one dimensional, thus rankings can be misleading or sometimes damaging when used to determine the educational curriculum of a child.

My issues with intelligence tests are that they only rank, they do not measure absolute intelligence, and they assume (against the evidence) that intelligence is 1-dimensionsonal and rankable. The ranking part means that terminology like “gifted” is making a huge assumption and priming people to think about intelligence incorrectly. IQ of 130 (“gifted”) is, by definition, 2 standard deviations above the mean. An adult male that’s 2 standard deviations above the norm in height is 6 foot 2. A whopping 5 inches taller than the mean of 5’9”. The 6’2” man is a little taller than the average guy, not a lot taller — even though they are taller than 95% of men. There’s no reason to believe that the distribution of intelligence, especially the hereditary/biological component of intelligence, is any different.

Okay it’s fair to question calling ‘effort’ part of intelligence; what I meant is that nurture/environment and experience and motivation are a large part of what gets measured with any and all psychometric tests. And we do know that practicing for IQ tests can raise scores somewhat.

FWIW, I wasn’t arguing against the idea of intelligence being heritable or having a biological component. Intelligence is heritable, but also there are large environmental and nurture components as well. Using the word “highly” might be technically accurate but somewhat misleading, the heritability of IQ for example averages around 50% across many studies (https://en.wikipedia.org/wiki/Heritability_of_IQ).

I was just pointing out that the way we measure intelligence does not measure intelligence itself directly, it only ranks people. We don’t know how much smarter someone who’s IQ 150 is than someone who’s IQ 100, we only know how many people are smarter than either score. Calling someone with a high IQ profoundly gifted is not actually supported by the ranking metric we’re using.

High intelligence does exist, I completely agree. What “high” actually means is debatable. But why is being amazing at art or music different from having high intelligence? Not sure I agree, and I think that statement is suspicious and deserves some justification. I think a lot of people would consider Bach and Mozart intelligent.

The actual reference to different brain structures in the Wikipedia article also mentions the positive correlation between socioeconomic status of children and their measured intelligence. That’s enough to question what’s actually being measured, and whether a correlation between cortical thickness and IQ really does represent a correlation between cortical thickness and intelligence, or something else.

> When adults consistently praise a child’s intelligence rather than their process or effort, mistakes stop feeling like normal setbacks and start feeling existential.

Isn’t this a good reason to stop using the term “gifted”? Isn’t it now widely acknowledged that effort (among other things like creativity and self-conception) actually is part of intelligence?

“Gifted” children are historically identified and classified via IQ tests (typically with the threshold IQ >= 130 - though the definition of what ‘gifted’ should mean is being debated), and using “gifted” for smart kids emerged and was popularized in the 1920’s when IQ tests were being developed by people who basically believed in eugenics, in the heritability of intelligence, and they wanted to identify the kids with the smart genes. [1] Using language like ‘profoundly gifted’ and ‘genius’ for high IQ has always been (mis)leading since IQ is a ranking, not an absolute measure of intelligence.

I just searched and found an interesting recent paper arguing that ‘gifted’ is problematic and attached to science that is no longer valid, and should be improved or replaced. [2]

[1] https://en.wikipedia.org/wiki/Intellectual_giftedness#Overvi...

[2] https://pubmed.ncbi.nlm.nih.gov/36278606/

Some people certainly have been diving into nuclear & green for decades, and we now have far more wind, solar, and hydro power than we did several decades ago. Nuclear has been flat for only 2 decades and is about to start growing.

“We” certainly have had control the whole time, “we” have been consciously creating greenhouse gas emitting machines while knowing the consequences. It is the economics. The delay in environmental consequences combined with the immediate financial benefits of easy power & transportation made the choice too tempting for some.

The kind of control you’re talking about is self-control. We’ve always had the option to stop our bad behavior, and we chose not to. And we still have the option to exercise self-control with AI. The question is whether that option might disappear soon. Can AI get good enough that we will actually lose the choice to regulate ourselves?

> while the chains of thought chatbots produce look like deliberation, research has demonstrated that the bots often concoct them after the fact, reaching an answer by one route but reporting another.

Doesn’t research show humans often do this too? There’s a pretty famous paper from the 70s about that [1], and lots of subsequent evidence. We also have choice blindness [2], we confabulate reasons [3], and we even change our choices (sometimes negatively) after trying to introspect [4].

[1] https://www.researchgate.net/publication/229060046_Telling_m...

[2] https://pubmed.ncbi.nlm.nih.gov/16210542/

[3] https://pmc.ncbi.nlm.nih.gov/articles/PMC5986841/

[4] https://pubmed.ncbi.nlm.nih.gov/2016668/

Things are being massively changed by AI. That’s what this article is about, the article you seem intent on poo-pooing. I only asked you a question about your stance, it was not an attack. My question was aimed at trying to uncover why you’ve cast insults toward teachers multiple times, and implicitly the one who authored this article. The only ad-hominems were yours, and they started with your first comment.

What heavy assumptions are you referring to? If you mean assuming that kids probably won’t skip university and instead will be self-motivated enough to use AI non-stop for several years in order to teach themselves enough to get a job as a biologist or a ballet dancer or a civil engineer, and if you mean assuming that companies and organizations probably won’t suddenly start accepting self-AI-taught candidates as being the same as having a degree… if these are the assumptions you’re referring to, then you’re right - I am assuming those things and I believe them. No matter how AI changes things, it’s a pretty heavy assumption you’ve made to think kids will self-motivate an education just because information is available, especially given that was always possible and still chosen so rarely that it effectively doesn’t exist. And it’s a pretty heavy assumption to think that universities and organizations will change together in a way that can vette the merit of prospective candidates any time in foreseeable future. AI will change a lot of things, but you’re underestimating our social structures and what things like the accreditation system do for the workforce and the economy. You can argue it’s got problems, but assuming like you did that AI can replace it anytime soon is a very heavy assumption.

If the pencil comment and suggestion to take away computers wasn’t literal, then you’re right, I have no idea what you meant. Feel free to explain. If you can’t, then I’d agree, there’s no further purpose.

I disagree that’s the problem, and I don’t think your claim is true. Degrees are still extremely valuable, and income stats alone prove it conclusively. I don’t find your suggestion very interesting, not because colleges are gatekeeping, but for the reason already stated: because most people do not and cannot teach themselves and curate their own educations at a university level, and because even if they did, which they don’t, it still wouldn’t help them get jobs or advanced degrees in today’s workforce. It might be an interesting suggestion if that happened with any statistical significance, but it doesn’t, and isn’t a realistic path for education for society.

Figuring out how to teach kids is exactly what this article is doing. How do you propose to teach kids, when they refuse to put in the work, and reach for AI for everything? Your suggestion to make them use pencils seems naïve/ignorant/obtuse; this article is written by a computer science teacher. You can’t force people to use only pencils for homework (as the article points out), and it would be ridiculous to use pencils for writing computer programs in 2026. That suggestion is a non-starter. FWIW, the impression I’m getting is not that you have any helpful suggestions for education, but that you don’t have experience teaching and don’t understand what’s happening in schools right now.

Who is protecting jobs programs under the guise of something nobler? This seems like a straw man unrelated to your previous comment. I’m getting the feeling you’re anti-education for some reason, maybe have some bone to pick with the university system, is that accurate? Asking kids to teach themselves or forcing them to use pencils are not going to be successful ways to improve education.

Looking at the first several examples, shorter (one, two, three-) letter words are not stretched to the full ‘fixed’ width. It’s the whitespace around them that is fixed. The only example in the first three screenshots of splitting a word into tokes is ‘vibes’ which turns into ‘vib’ and ‘es’. I’m skeptical of the -ing and -tion words being single tokens as shown.

The BASIC print+goto loop might have been my first ever program too (in the 80s) but one thing for sure for me: it was definitely not “Hello, World”. I and others filled the screen with any number of silly things, random words, jokes and juvenile phrases, whatever, but for some reason, “Hello, World!” was a C thing, and I remember seeing it for the first time in a C class in high school, and then much more often in college.

I have memories of ‘poke’ as well. On the Atari 800 you could poke memory to change the keystroke repeat rate and delay before repeat started, so obviously we would turn down the delay to zero and turn up the repeat to max (it was maybe 60 characters per second), so anyone trying to type couldn’t hit the keys quickly enough to avoid repeating. You’d have to power-cycle the machine to fix it, so it was hilarious to 11 year old me.

Similar to his description of ‘poke’, but different mechanism - using debug.com on an IBM PC jr to edit the Ultimate III save files, and give myself maximum money and lives.

Good times!

Cute idea, but is this fixed width words, and not fixed width tokens? Isn’t an ‘ing’ ending normal a separate token from the root? Isn’t ‘strawberry’ two tokens?

Why is that interesting? How often does that happen? Has it happened even once? Seems like fantasy; this has been possible for a long time, and despite it being possible, it almost never actually happens. Before AI, kids willing to orchestrate their own education could use the internet to become experts in anything. Before the internet kids could use libraries and books to become experts in anything. But how many take the time and effort to match a 4 year degree? Statistically, approximately zero.

One major problem: how do you get a job for which a degree is required, if you teach yourself via books/internet/AI? How do you get into graduate schools for which a degree is required? How do you envision advanced degrees working without funding or labs or mentors?

All of education is undergoing dramatic seismic shifts because of AI right now. Attempting to insult teachers for talking about it doesn’t reflect on teachers, it reflects on you.

Who’s insisting that? Where does 25 come from? 4 year degree attainment is just under 40% in the U.S., and most of them finish by 22 or 23.

People are choosing to go to university. It might have something to do with having better job options and statistically higher pay…

Where do you find 2006? My googling says NT 6 was released in early 2007, so I meant that on Jan 1 2007, Win 5 was still current. https://simple.wikipedia.org/wiki/Windows_NT_6.x

It wouldn’t make a huge difference to me if 6 was released either 6 months earlier or 6 months later. In 2007, NT4 was only 1 major version behind for most people; adoption takes time. The broad timing of major versions being 4-5 years apart didn’t change until Windows 11, and we don’t know if that’s an outlier yet, but we do know that Microsoft has been changing the Windows release strategy, with more frequent updates. https://endoflife.date/windows

There might be a seed of truth there, but FWIW, I’m not very convinced by that. CPU speed development has slowed down a bit for sure, but software development is going faster than ever. GitHub and NPM and Python 3 and Rust all didn’t exist in 2007. CUDA was first released that year. LLMs weren’t being used. At the start of 2007, the latest Windows version was Windows 5, one more than Windows 4. Almost same as today. There isn’t a Windows 12 yet, while Windows 6 was released in 2007. So the pace of major Windows versions might be slightly slower. OTOH, the OS is much bigger than it used to be and it gets more frequent updates and point releases now than it did in 2007.

Well, that’s in the guidelines. https://news.ycombinator.com/newsguidelines.html

> A certain nuclear power plant had a Windows NT 4.0 machine running as late as 2007.

To put this in perspective, NT 4 was released in 1996, 11 years before 2007. That’s roughly the same as someone running Windows 10 today, which a lot of people still do. The Pentium 1 was only 14 years old at most. These parts of the system shouldn’t be surprising.

The AmigaOS and software from the 80s are of course the older more interesting bits, but for critical infrastructure and safety, shouldn’t we expect and design for our hardware and software to last a long time, and not try to keep up with tech fads every decade? I feel like the main problem isn’t hardware or software that’s old, but that there wasn’t a longevity plan.

It’s always been an interesting question how to write software that will last a hundred years. Maybe with AI this is the first time in history that planning to port & upgrade to new hardware every 5-10 years seems totally reasonable.

> I think they should have used an LLM

The article reads to me as largely LLM generated. I checked several sections with Pangram and it appears to agree that it’s either entirely AI generated, or at least 100% AI assisted.

I’m fine with the idea of AI assistance, but I agree the quality is low and this needed a bit more editing. I have my own list of gripes that include not defining terms that are used, text for tables and figures being repeated in the body and the captions, contradictions and non-sequiturs, and just AI’s real watermark of getting lost in details, using clever terminology, having a hard time being concise, and being unable to use plain and clear language.

I think they goofed on the conclusion: “These results do not argue against watermarking for provenance. They show that provenance and behavioral stability are separate properties.”

The article’s entire point is that stability depends on provenance techniques, therefore the results purport to show they are not separate properties. Oops.

Also, it’s not AI’s fault that URLs in the references section aren’t clickable. Come on.

Oh I see I’ve misunderstood. Your analogy is restricting the scenario to no interaction with LLMs. In that case, there are still some reasons LLM writing might be prefereable for students: for non-native speakers, and for math teachers new to match developing a new curriculum (sucks, I guess, but it certainly happens), just to name a couple.

One question to ask is why is your contrived LLM scenario any different than a math teacher using a textbook, or district/state worksheets? Math teachers typically do not write the course text or exercises, and never have. Very few math teachers do their own writing.

Irrelevant? How so? And why did you present two different options if you thought it was irrelevant? I thought you were trying to make a point about human interaction. From my POV, your options 2 and 3 are much closer together than 1 & 2, so if you’re not suggesting that human interaction is preferable to LLM interaction, then what’s your justification for claiming any option is better than any other? I still completely disagree with your clarified point, and suspect many many other people do too, and are demonstrating that preference by using chatGPT for their classes instead of using either the teacher or Google. It’s a simple fact that interacting with an LLM can be preferable to interacting with some teachers some of the time, and LLMs currently often make interacting with the internet more pleasant and more efficient. Your ‘almost always’ still sounds to me like one person’s opinion that is not shared by all.

> with its twisted mix of Australian, Cockney and Kings English

This is a great way of summarizing a lot of the TV we’re getting in the US that have British characters, and it’s annoying once you notice it.

See how the accent changes in Lie to Me between season 1 and season 3:

S1: https://youtu.be/bWyhsqh_e9s

S3: https://youtu.be/oPqOET_xCKw

Oh it very much depends, your opinion there is certainly not always true and not shared by everyone; you only know where you stand right now with any certainty.

It depends on the teacher. I’ve had good and bad math classes, and LLMs today are quite a bit better than the bad ones. The worst human teacher in my memory didn’t offer interactions. He walked in, turned his back to the class, wrote equations on the board for 45 minutes, and then left. The best math teachers, the ones better than LLMs, are the ones who share the joy and sense of discovery and history of math, and not just the mechanics. But there aren’t that many teachers of that sort.

Learning by using the internet without LLMs is rarely very good, but more often than not in my experience sucks much worse than using LLMs. If you include using public LLMs in internet usage, then it’s not very different from just using LLMs that search the internet. I have heard that a huge swath of today’s high school and college kids are reaching for chatGPT before Google (which is incidentally OpenAI’s goal), and that many of them would rather talk to chatGPT than talk to a teacher. I’m going to refrain from making any claims, but I believe there are a lot of people who disagree with your ranking of the options.

Foreign language learning is one case where I love using LLMs, because it’s not typically an option otherwise. You can practice non-stop and have conversations with someone fluent in a language who will be infinitely patient with your mistakes. This is true of math and other subjects too; using LLMs to practice, so that the human teacher isn’t the bottleneck, to supplement and reinforce the human interactions, is usually better than using the internet without LLMs. The other reason many people prefer talking to LLMs is the lack of judgement. If you aren’t getting it and ask the teacher one too many basic questions, they treat you differently. Sometimes it’s necessary and helpful, and sometimes it’s harmful and takes a long time to change. LLMs don’t do that, they just explain and explain. That lack of judgement is a big reason many people prefer LLM interaction to human interaction.

I’d guess the concern is performance, not what initializer value is used. And performance is a valid concern that is discussed in the proposal, and a reason there’s an escape hatch. Still, it might cause some confusion.

They were saying the problematic philosophy started in C++ 20, not the variable initialization rule.

Yes the reason is obvious, but it’s neither simple nor black and white. One huge problem is that this can cause serious performance regressions, and you have to change your code to opt out, e.g. add “[[indeterminate]]”. There are many, many cases in high performance computing where the intended & desired behavior is don’t touch my variables until I fill them.

This is changing C++ core principles, there’s a new designation for the state of a variable: erroneous. It’s also subtle and weird, because you can still have well-defined behavior even with erroneous state. It does seem like this might be an experiment though, I don’t think this is the end of the story. (It seems they’re already talking some redesign of this idea.)

Three of those four prompts are opt-in and configurable and aren’t the site’s fault, no? I disable the browser and OS password managers because I use 1Password… why do you have the Chrome and OS password managers enabled if you’re using 1Password? Or if there’s some reason you need them all available, at least rather than dismissing the prompts, why not add an entry to disabling prompting for a specific site in the 2 managers you don’t want to see again? All three support that.

There’s not much evidence these are being used, only that they are dependencies for something else; that’s why the download numbers are so high.

I wouldn’t say it’s broken, I’d say there are tradeoffs, and devs have known this and discussed it since the start of npm or any package manager. You automatically get some bloat when you use other people’s software. That’s the downside. The upside is you don’t have to write the code yourself and you can create things more quickly by not solving problems that others have already solved.

It’s worth noting that AI has some of the same tradeoffs. The quality of what you get is still proportional to your prompting & reviewing effort, and spending low amounts of effort often results in similar amount of bloat.

Ah, now having the best model be expensive to use, and thinking the cash burn of both companies is insane and unsustainable I completely agree with. This, I think is likely the biggest reason they’re asking for government intervention and regulation: to help them weather the coming investment/cash plateau, not because the models are nearing any asymptotic limits. To be fair, there is an argument to be made that the improvement in models is tied to the cash burn; if they can’t train bigger models or acquire more data or research more effective harnesses, then the improvement of their models might slow down - while GLM or other models continue to improve.

I’ve never thought LLMs were on the AGI path, but I have to admit it’s surprising how far it’s come with no end in sight yet. There is something important to be said about how ‘intelligence’ is embedded in language, and it suggests that intelligence isn’t exactly what we thought it was. The language component of intelligence also goes a long way to explaining technology’s progress in human civilization; how language and the printing press and mail and radio/tv and the internet have each ushered in accelerations in the pace of progress. Biologically and evolutionarily speaking, it’s unlikely that humans have become any smarter in the last two thousand years, but technology (among other things) has exploded.