The Wikipedia article on duct tape tells us about the history, in which the name for cotton duck came from Dutch doek meaning "cloth", and  "duck tape" was originally a tape with "a rubber-based adhesive applied to a durable duck cloth backing", later perhaps reinterpreted as a tape used to seal heating and cooling ducts. That article's section on duct tape in popular culture hints at connections with stereotypically male roles like "handyman", but the gender association remains implicit.

Not so for the cover of Louann Brizendine's 2010 book The Male Brain:

In contrast, The Female Brain is a tangled curly telephone cord in the U.S.:

And an overstuffed purse in the U.K.:

I was originally puzzled by the  duct tape brain, but readers set me straight — see "What's the Male Brain made of?" (3/25/2010).

It is the thesis of this book that society can only be understood through a study of the messages and the communication facilities which belong to it; and that in the future development of these messages and communication facilities, messages between man and machines, between machines and man, and between machine and machine, are destined to play an ever-increasing part.

And those messages will be an "ever-increasing part" of an ever-growing whole, alas — just ask anyone who has recently spent time with WorkDay and its ilk .

Weiner 's predicted "new industrial revolution" has a lot in common with current worries about AI:

Thus the new industrial revolution is a two-edged sword. It may be used for the benefit of humanity, but only if humanity survives long enough to enter a period in which such a benefit is possible. It may also be used to destroy humanity, and if it is not used intelligently it can go very far in that direction.

However, he underestimates the needed development time:

The introduction of the new devices and the dates at which they are to be expected are, of course, largely economic matters, on which I am not an expert. Short of any violent political changes or another great war, I should give a rough estimate that it will take the new tools ten to twenty years to come into their own. 

Thus by 1960 or 1970, he argues,

It is perfectly clear that this will produce an unemployment situation, in comparison with which the present recession and even the depression of the thirties will seem a pleasant joke. This depression will ruin many industries — possibly even the industries which have taken advantage of the new potentialities. 

The 60s and 70s had their problems, but not those problems. So who knows, maybe message-overload will continue to be our experience of AI doom?

Mouseover title: "Meanwhile the Engineers are just lighting themselves on fire to see what happens."

The aftercomic:

In fact, there's a wide range of reactions from each group — and likewise from Linguists, although some possibilities are oddly missing…

See also "Intellectual Automation" (3/7/2011); "AI Panics" (11/27/2016); "'The real threat of AI'" (6/26/2017); etc.

Men vsyd to ete togyders in open place, leest syngularite schuld brede lechery.

A mathematical singularity, as Wikipedia tells us,"is a point at which a given mathematical object is not defined, or a point where the mathematical object ceases to be well-behaved in some particular way, such as by lacking differentiability or analyticity", with an obvious example being what happens to the reciprocal function 1/x at the point x=0. I'm not sure when that usage began, but it's easy to find references back to the 19th century, e.g. Charlotte Angas Scott, "On the higher singularities of plane curves", American Journal of Mathematics 1892.

Most uses of the term these days involve a metaphorical extension of the mathematical concept to the idea of a technological singularity, which Wikipedia describes as "a hypothetical event in which technological growth accelerates beyond human control, producing unpredictable changes in human civilization."

The first documented use of this metaphor is attributed to John von Neumann in a 1958 posthumous tribute by Stanislaw Ulam:

Quite aware that the criteria of value in mathematical work are, to some extent, purely aesthetic, he once expressed an apprehension that the values put on abstract scientific achievement in our present civilization might diminish: "The interests of humanity may change, the present curiosities in science may cease, and entirely different things may occupy the human mind in the future." One conversation centered on the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.

Then in the early 1960s, I.J. Good presented "Speculations Concerning the First Ultraintelligent Machine". Good doesn't use the term singularity, but he clearly expresses (a version of) the idea. From his Introduction:

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an 'intelligence explosion', and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.

And from his Conclusion:

It is more probable than not that, within the twentieth century, an ultraintelligent machine will be built and that it will be the last invention that man need make, since it will lead to an "intelligence explosion." This will transform society in an unimaginable way. The first ultraintelligent machine will need to be ultraparallel, and is likely to be achieved with the help of a very large artificial neural net. […] The machine will have a multimillion dollar computer and information-retrieval system under its direct control. The design of the machine will be partly suggested by analogy with several aspects of the human brain and intellect. In particular, the machine will have high linguistic ability and will be able to operate with the meanings of propositions, because to do so will lead to a necessary economy, just as it does in man.

The whole article is well worth reading carefully, and it's a scandal that the only available (and somewhat corrupted) version is on the Wayback Machine. For more on I.J. Good, see my 2009 post "Good is dead", which sketches his contributions (with Alan Turing) to the world's first Language Model, as part of the Enigma decryption effort more than 80 years ago.

The next step (that I know of) was taken by Vernor Vinge, in a 1983 op-ed in Omni Magazine (I've typed out the contents because the original, black type on a dark grey background, is hard to read):

A favorite game of futurists is to plot technological performance – computer speed, say – against time. Such trend curves climb ever more steeply. Extrapolated 30 or 40 years, they are so high and steep that even the most naive futurist discounts their accuracy. Some who talk about that era predict a leveling off of progress. After all, saturation effects are observed in other growth processes.

There is an important reason why this process won’t level off. We are at the point of accelerating the evolution of intelligence itself. The exact means of accomplishing this phenomenon cannot yet be predicted – and is not important. Whether our work is case in silicon or DNA will have little effect on the ultimate results. The evolution of human intelligence took millions of years. We will devise an equivalent advance in a fraction of that time. We will soon create intelligences greater than our own.

When this happens, human history will have reached a kind of singularity, an intellectual transition as impenetrable as the knotted space-time at the center of a black hole, and the world will pass far beyond our understanding. This singularity, I believe, already haunts a number of science-fiction writers. It makes realistic extrapolations to an interstellar future impossible. To write a story set more than a century hence, one needs a nuclear war in between – to retard progress enough so that the world remains intelligible.

In a 1993 article "Technological Singularity", still (for now) available on the web, Vinge elevates singularity into the title. He quotes Ulam/von Neumann and Good, and concludes by speculating about "the Best We Can Ask For". The whole thing is worth reading.

It's striking how accurately some recent developments were foreseen by von Neumann and Good and Vinge  30-70 years ago — but what strikes me most about the current situation is how much of it was not predicted. None of those seers told us about Data Center politics; AI hallucinations; the socio-political and cybersecurity effects of AI bots and agentic AI; the economics of a possible AI bubble; and so on.

Maybe this is just temporary turbulence as a smoothly-flowing post-singularity future is forming, whether utopian or dystopian or both. But from where I sit, the foreseeable future of (things called) "AI" looks even more chaotic, which is one more reason to doubt that the concept of a singularity is really helpful.

A different metaphor is implied by Richard Dooling's 2009 book Rapture for the Geeks , as well as a 2012 work the rapture of the nerds by Cory Doctorow and Charles Stross.  Both allude to the (religious) Rapture, which is conceived in many different ways by different individuals and groups, but is generally seen as an abrupt event that's positioned in the middle of other variously defined and described times, and affects different groups of people in very different ways.

See also "Another meme collision", 7/8/2024.

AI is replacing human hiring managers in job interviews—and candidates are pushing back. Despite being unemployed, professionals told Fortune they’re refusing to take calls with bots, calling it an “added indignity” and a red flag for company culture. Still, stretched-thin HR teams say it’s the only way to handle thousands of applicants.

Evaluations of these interview bots don't seem to have improved over the past year — see e.g. "Dystopian and dehumanising: that’s what it felt like when I was interviewed by an AI assistant", The Guardian 10/12/2026, and many similar reactions.

There are lots of other reasons for interacting with a chatbot, like it or not, and one of the things that often bothers people about those interactions is what's come to be called glazing, which means "to hype and compliment someone in a way that is over-the-top and cringey."

Over the past few weeks, Graham Dot Zip has created several amusing (fake?) interviews that feature glazing responses from job-interview chatbots, prompted by nonsensical inputs:

I doubt that current job-interview chatbots are so dedicated to sycophancy. And I'm pretty sure that none of them could recognize Graham's  responses so accurately, or follow him so cooperatively into nonsensical improv. But the idea of taking a chatbot on a ride into wonderland is hilarious enough that I wish it were true.

For more about what such interactions might really be like, take a look at this video (from Indeed) on preparing for AI job interviews, or this one that shows some clips from interviews with bots from Humanly and others.

… in which models occupy dual roles: each authors math problems under adversarial prompting and solves problems authored by every other participant. A generation pipeline produces and filters the problems, and a psychometric model jointly estimates solver abilities and problem difficulties, from which author quality is derived. Experiments across 19 frontier models reveal that authoring and solving capabilities are partially decoupled, and that dual-role evaluation exposes capability separations invisible in single-role benchmarks. As newer models enter the arena, they produce problems that defeat previously dominant solvers, so the benchmark’s difficulty co-evolves with participant strength rather than saturating at a fixed ceiling. [Abstract taken from today's lecture.]

There's an evolving MathDuels leaderboard here.

It would be interesting to try the same thing with the sorts of problems featured in the International Linguistics Olympiad ("IOL"),  or the North American Computational Linguistics Open Competition ("NACLO").

My prediction is that at the start, current "frontier models" will generally do a bad job at solving such problems, and a worse job at posing them. But over time, they should improve, probably reaching the point of becoming useful research assistants, and perhaps even (in some sense) independent researchers?

A sample slide from Mayur's lecture today:

We can start with very, for which Wiktonary gives the etymology

From Middle English verray, from Old French verai (“true”), from Early Medieval Latin vērāgus, from Classical Latin vērāx, derived from vērus, from Proto-Italic *wēros, from Proto-Indo-European *weh₁ros.

According to the OED, the purely intensive adverbial use of very developed in the 16th-17th centuries.

The page on real from Merriam-Webster's Concise Dictionary of English Usage starts like this:

The adverb real, which is used only as an intensifier, developed from a use of the adjective to modify compound noun phrases like good turn. By the 18th century the real was apprehended as an intensifier modifying good alone, and its independent use grew from then. It was a development that took place, apparently, outside of mainstream British English; the OED identifies it as chiefly Scottish and American, and we have some slight Irish evidence. It has been from the start primarily a spoken use.

We covered the regional use of wicked as an intensifier back in 2014.

And scary as an intensifer in "scary smart" seems to have started around the turn of the century, as Google ngrams shows us.

A typical example:

[link] He made it to Wall Street because he’s scary smart — and you want him on your team — but he’s so socially awkward it’s painful.

And another one, in Doonesbury:

The same period seems to have seen the development of "crazy good":

And similarly, "sneaky good":

The phrase "silky smooth" seems to have been developing over a longer period:

But this kind of adverbialization is not something that you can (felicitously) apply wherever you like: *bewildering(ly) odd, *total(ly) flat, *strange(ly) lacking, etc.

Benjamin Franklin was an American polymath active as a physicist, philosopher, statesman and inventor.

The article goes on to list (some of) his other achievements, including his role as a writer, and as the founder of institutions such as the American Philosophical Society and what became the University of Pennsylvania. It omits many other things, including his contributions as an orthoepist and phonetician.

Franklin did none of this because he was trained to do it or hired to do it, but because he was curious about the world around him, and followed up in unexpected and consequential ways on chance encounters both common and rare.

Victor Mair was also active throughout his life in many different intellectual and cultural and physical areas. For regular readers of this blog, I don’t need to make a list — but I learned several new things about his history at yesterday's memorial service. 

And Victor’s diverse activities were Franklin-esque. Like Franklin, he was involved in the world around him; curious about both ordinary and unique aspects of his experiences; and able to turn that curiosity into insights, discoveries, communications, and organizational support.

This pattern is less common among today’s academics than perhaps it should be, but Victor’s example shows us what’s possible.

Because Grace Wu was not able to attend, she sent me a tribute to read on her behalf, which I've reprinted below.

I have always been deeply grateful to Professor Mair and to his extraordinary contributions to Taiwanese language education. In fact, Penn’s Taiwanese language program, which began in 1993, would not have existed without his advocacy. More than 30 years ago, at a time when there were not yet any Taiwanese language courses being offered even in Taiwan, he had the vision to establish Taiwanese at Penn.  I often think about what a remarkable idea and commitment that was.

Over the years, Professor Mair also wrote extensively about Taiwanese in Language Log. For example, on 6/16/2018, in a post with the title “Mother tongue is like mother’s milk”, he mentions the Taiwanese dictionary that my father helped compile.

And on 10/16/2009, in “National Language vs. Mother Tongue”, he led with a photo that I sent him, and discussed the campaign to replace topolects with Putonghua.

But the essay I love most is “How to Forget Your Mother Tongue and Remember Your National Language”.

There is one passage that has always been especially meaningful to me:

“The simplest way to make speakers of a language feel that their tongue is inadequate is to stigmatize it as sù 俗 (‘vulgar’), lǐyǔ 俚語 (‘slang’), tǔhuà 土話 (‘earthy speech’), and so on. Once such evaluations are accepted by the speakers of a given language themselves, the psychological impact is tremendous. Subjected to such indoctrination, they lose confidence in their mother tongue and may become acutely embarrassed when outsiders hear them speaking it.”

This idea was a real revelation to me. Having grown up under a Mandarin-centered language system, I had never fully understood how deeply the stigmatization of Taiwanese during the martial-law era had affected our attitudes toward our own language.

Professor Mair helped me understand this history and, more importantly, helped me feel proud of my own language. His work also taught me to be more respectful of my students’ accents and to approach dialects and language varieties with greater openness, empathy, and understanding.

I will always be grateful for Professor Mair’s lifelong dedication to East Asian scholarship and Taiwanese language education, and for the profound humanistic spirit with which he approached language, culture, and the people who speak them. His intellectual work touched many lives, including mine, and his influence will continue through generations of students and teachers.

Above is Grace Wu's tribute to Victor Mair, composed for his 10/10/2026 Memorial Service.

There's another one here, and the slogan alone also appears in text form.

The relevant linguistic history starts in the 16th century, when William Tyndale chose the phrase filthy lucre to render Greek αἰσχροῦ κέρδους in his bible's translation of Titus 1:7 and 1:11, and similar phrases in Timothy 3 and Peter 5.

The OED lists filthy as an adjective, from c1400, giving sense 2 the gloss "figurative. Morally foul or corrupt; obscene, disgusting, immoral, offensive." So that was a reasonable but not obvious choice for translating Titus's Greek αἰσχρός, which Wiktionary glosses as "causing shame; dishonoring; reproachful; disgraceful".

The phrase "filthy lucre" took off from there. The authors of the King James version retained it for Titus, Timothy, and Peter, and other authors have often used it up to the present, to refer to money in negatively-evaluated contexts.

The next step, three or four centuries later, was "filthy rich". The OED lists filthy as an adverb, glossed as "colloquial. Extremely, enormously, esp. offensively or disgustingly so. Only with reference to drunkenness or (esp.) wealth, usually in filthy rich."

The OED's earliest citations are

1827 We saw two individuals staggering through the middle of the street most filthy drunk.
1905 It may be just as well..not to wonder who those filthy rich people are speeding by in the ski-doodle cart.

The gradation between "rich" and "comfortable" is discussed here and there on line, for example on quora.com. In that context, the coinage "filthy comfortable" elevates a comfortable level of wealth from its lesser status to something almost offensively great, or at least worthy of envious gossip about easy acceptance of small expenses like optional guac. "Filthy comfortable" is something that anyone can aspire to be, even if most people are not there yet.

Schwab's ads nounify the phrase in the slogan "Find your filthy comfortable", thus personalizing the condition without more elaborate verbiage like "Find your way to becoming filthy comfortable".

But yesterday, Bob Ladd pointed out to me that Science magazine committed a similar error in the references to a paper dated 9/25/2026 (Morvai, Boglárka, Kinga G. Tóth, Marianna Boros, Dorottya S. Rácz, Ivaylo Iotchev, Kitti Szabó, and Attila Andics. "Neural evidence that dogs segment the speech they hear with a humanlike consonant bias." Science (2026).

The paper's second reference was to John McCarthy's 1979 PhD thesis, Formal problems in Semitic phonology and morphology — and "Semitic phonology and morphology" is rendered as "semantic phonology and morphology".

Bob's email:

I was going to add a somewhat off-topic comment to your latest post, but I thought you might be interested in this as a separate LLog item.

There's a recent article in Science about how dogs listening to Saffran-style nonsense syllable sequences can pick out recurrent patterns based on detecting regularities in transition probabilities, and that they show the same bias as human subjects do in favour of detecting CONSONANT regularities rather than VOWEL regularities.  (I was led to this article by a news story in New Scientist which which kind of garbled the details of the experimental stimuli, so that I went to the original article to figure out what the researchers had actually done.)

The opening sentence of the Science paper begins "Across many languages, consonants are more useful for word identification than vowels…" and goes on to cite work by the likes of Anne Cutler and Jacques Mehler that explored psycholinguistic aspects of this asymmetry.  The Science study aimed to see if dogs exhibit the same bias as humans for attending to consonants in speech segmentation, and it reports that they do.  Conceivably this would be worth a LLog post for the interest of all those readers who used to annoy Geoff Pullum.

However, what's relevant for "pneumatic, pneumonic, whatever" is that one of the sources for the statement in the paper's opening sentence about consonants and vowels is a reference to John McCarthy's PhD thesis, which is cited as “Formal problems in semantic phonology and morphology.”

The Science paper and its human background deserve a full post, which I hope that Bob will provide for us.

The conceptual gap between that paper and its coverage in the New Scientist should also be mentioned, perhaps with glance at the rest of the (extensive) coverage in popular media (BioTechniques, Neuroscience News, Discover, WaPo, El Pais, Newser, Science Alert, the Times, Earth.com, the Independent, etc. etc.).

There's also the obvious observation that the neuroscience of talking to dogs is one of the most clickbait-y possible current topics, maybe minus only the neurological verification that cats are more aloof, and that some AI agents are developing neurologically optimized vocalizations to steal the loyalty of our pets.

Governments can also use their enormous purchasing power to demand more from A.I. companies and to build more A.I. with them. In return for providing government funding, South Korea is securing contracts with multiple tech and telecom companies to give A.I. access to all of its 51 million citizens.

Giving AI access to everyone! That sounds like a good idea, right?

But wait a minute, what's the syntax here? Is access to AI being given to all of the citizens? Or is AI being given access to all of the citizens?

Why not both? For the details, see Jiyoung Sohn, "South Korea’s ‘AI for All’ Push Gives Free Access to Every Citizen", WSJ 8/28/2026:

South Korea plans to give its entire population free access to generative AI services, the first major state-led offering treating the technology akin to a public utility.

The program seeks to connect more South Koreans to homegrown AI chatbots with the goal of advancing the country’s push for AI sovereignty. By giving premium-level AI services free to its citizens, South Korean officials hope to avoid an overreliance on models from the U.S. and China.

[h/t Jonathan Smith]

Update —