by Derek Neal

In the first round of this year’s NBA playoffs, Austin Reaves, an undrafted and little-known guard who plays for the Los Angeles Lakers, held the ball outside the three-point line. With under two minutes remaining, the score stood at 118-112 in the Lakers’ favor against the Memphis Grizzlies. Lebron James waited for the ball to his right. Instead of deferring to the star player, Reaves ignored James, drove into the lane, and hit a floating shot for his fifth field goal of the fourth quarter. He then turned around and yelled, “I’m him!”. The initial reaction one might have to this statement—“I’m him”—is a question: who are you? The phrase sounds strange to our ears. Who could you be but yourself? And if you are someone else, shouldn’t we know who this other person is? Who is the referent of the pronoun “him”? Perhaps because of its cryptic nature, “I’m him” is an evocative statement, and it has quickly spread throughout sports and gaming culture. In a 2022 episode of “The Shop,” Lebron James himself declared “I’m him.” On YouTube, there are numerous compilations with titles such as “NFL ‘I’m Him’ Moments.” If you search the phrase on Twitter, people use it in relation to sports, music, video games, and themselves. But what does it mean, and where did it come from?

An internet search turns up a few articles explaining the history of this statement. Apparently, a rapper named Kevin Gates was the first to popularize the phrase when he titled his 2019 album, I’m Him. In this instance, “Him” acted as an acronym for “His Imperial Majesty.” We could then understand people saying, “I’m Him” to be saying something along the lines of “I’m the king.” This expression would function much like another sports saying, “the GOAT,” meaning “the greatest of all time.” But I think there is more to it than this. Since Gates used the term, no other examples have used “him” as an acronym. Read more »

by William Benzon

I’m stumped. I’ve hit a wall. More than one most likely.

I don’t know how to think about artificial intelligence. Well, that’s a rather broad statement. After all, I’ve done quite a bit of thinking about it. Six of my most recent articles here at 3QD about been about it, and who know how many blog posts, working papers, and formal academic papers going back for decades. I’ve thought a lot about it. And yet I’ve hit a wall.

First I should say that it’s only relatively recently that I’ve given a great deal of focal attention to artificial intelligence as such. What I’ve been interested in all these years has been the human mind, which I’ve often approached from a computational point of view, as I explained in From “Kubla Khan” through GPT and beyond. In pursuing that interest I read widely in the cognitive sciences, including A.I. My objective was always to understand the human mind and never to create an artificial human being.

It’s the prospect creating of an artificial human being that has me stumped. Of course, an artificial intelligence isn’t necessarily an artificial human being. Computer systems that plays chess or Jeopardy at a championship level are artificial intelligences, but they certainly aren’t artificial human beings. ChatGPT or any of recent large language models (LLMs) are artificial intelligences, but they aren’t artificial human beings.

But the capability of these recent systems, certainly the LLMs, but other systems as well, are so startling that, it seems to me, that they have changed the valence, for lack of a better word, of inquiry into the computational view of the human mind. What do I mean by that, by valence? My dictionary links the term with chemistry and with linguistics. In both contexts the term is about capacity for combination, the ability of one element to join with others in forming chemical compounds, the ability of a word to combine with others in a sentence. Something like that. Read more »

Aqui Thami. Resisters, 2018.

Poster.

More here, and here.

by Brooks Riley

by Rafaël Newman

My father’s mother—Annie Newman, my grandmother or Bubbi—was born Hannah Dubin in a shtetl in what is now Ukraine a few years before the Great War. One of her earliest recollections—in addition to the image of her own grandmother hiding in a baby carriage to escape marauding Cossacks—was of being able to see troop movements from the roof of her house, presumably during the Russian Imperial Army’s advance against Austria-Hungary, an engagement that occurred in Galicia, farther to the west, in 1914. Much later, in the aftermath of the nuclear accident in Chernobyl in 1986, when that obscure place was suddenly on everyone’s lips, she began recalling that her village, which she called Priut, in a region she referred to by its Russian name as Екатеринославская губернія, or Yekaterinoslavskaya guberniya—the Yekaterinoslav Governorate, a province of the Russian Empire—was not far from that site, which had now become infamous for a catastrophic meltdown. Read more »

My wife walking in the woods near Franzensfeste, South Tyrol.

by Bill Murray

In the typical American city where we live, the average commute time is 78 minutes a day and 97.5% of these poll respondents agree traffic congestion is a serious problem. The last place you might expect to find people who commiserate is an island forty miles long and thirty wide, 420 miles east of Madagascar in the Indian ocean. But here we are.

We came to poke around some of the more outre bits of Overseas France, La France d’outre–mer. Welcome to the French département of Réunion Island, eighteen hundred miles from Johannesburg and 3275 crow-fly miles south of India in the southern Indian Ocean. It doesn’t sound very French, but it is, resolutely, and likes it that way.

It’s about a four hour flight out here from Johannesburg, the only continental African connection. You leave late at night, think you can sleep a little bit but these aren’t long haul planes, so you do your best in a tilt-back seat. They do a quaint thing, they still run a food cart down the aisle handing out newspapers, like in the old days.

Time zones work to smooth out flight schedules, not sleeping schemes, so as you arrive, if you squint while you’re still way up in the air you can just discern that dawn, somewhere over the Andamans and Nicobars, is screaming around the planet, about to catch you.

And now that we’re here, we can’t get out of town. People are just crazy, crazy busy, but where is it they’re so busy getting off to? Réunion’s economic engine is sugarcane and its main exports are sugar, rum and molasses. Read more »

by Ali Minai

But nature is a stranger yet:
The ones that cite her most
Have never passed her haunted house,
Nor simplified her ghost.

—Emily Dickinson, “What Mystery Pervades a Well”

The first article of this 2-part series laid out the idea of emergence in complex systems, discussed how the appearance of abilities such as the generation of grammatical, syntactically correct, and meaningful text can reasonably be seen as an example of emergence, but also why these emergent abilities are just a shadow – or ghost – of the deeper language generation process in humans. This second part gets more deeply into the last point, making a detailed argument for why the linguistic abilities of LLMs should be seen as limited, and what would be needed to extend them.

The Meaning of Meaning

Perhaps the most critical difference between an LLM’s model of language and that of a human is in the way meanings are understood in the two. The task on which LLMs are trained provides no explicit information about meanings, and depends only on knowing the structural relationships between words in text. However, the fact that LLMs almost always use words in meaningful ways indicates that they have an implicit model of meanings too. What is the nature of that? The answer lies almost certainly in a linguistic idea called the distributional hypothesis of meaning, which says that the meaning of a word can be inferred from the statistics of its use in the context of other words. As described above, LLMs based on transformers are pre-disposed to the statistical learning of structural relationships in text, and their representations of meaning must be derived implicitly from this because of the tight linkage between word usage and meaning per the distributional hypothesis. Given enough data, the statistics can become very accurate – hence the meaningful output of GPT-4 et al. But such meanings – though accurate for purposes to usage – are abstractions. In contrast, the meanings in the human mind are grounded in experience. GPT-4 might understand the meaning of the word “burn” as something associated with the words, “fire”, “heat”, “flame”, “smoke”, “pain”, etc., but a person understands it in terms of the sensation of feeling heat and getting burned. Similarly, GPT-4 may use the words “near” and “far” correctly, but it has no experience of an object being near enough to touch or too far away to recognize. Concrete meanings in the human mind are thus grounded in the fact of the human animal being embodied – a physical system with sensations and the capability of action that leads to physical consequences. The LLM is “all talk” – just simulating concrete meanings as ungrounded symbols. Of course, not all concepts in human language are concrete enough to be defined in direct experiential terms, and there is ongoing debate about how the mind grounds abstract meanings. However, it seems plausible that they are grounded in the substrate of more concrete meanings, and thus indirectly in experience as well (see reference [1] for a recent overview, reference [2] for my views in detail). It is in this sense above all that LLM models are ghosts in the machine. Read more »

by Tim Sommers

I’m not really interested in magic. But I am interested in crime. So, recently while reading a discussion of close-in magic by neuroscientists I perked up when they got to the question of how criminals, and others of questionable character (like magicians), steal wristwatches right off their victims’ wrist without being detected. (Still relevant? Wrist watch wearing, admittedly, is way down from its peak in the 1950s, but a third of adult males still wear one every day – and then there’s smartwatches, step counters, etc.)

Apparently, there’s a skill and a trick involved in stealing a watch. The skill is to learn to undo the clasp using just your middle and pointer fingers, while simultaneously shaking hands with someone. Sure, that’s quite a skill to master, but I was more curious about how you then yank a watch off someone’s wrist without them noticing – particularly a watch with a “deployant clasp” that doesn’t open all the way. (See image above.)

Here’s what you do. You just clap the person on the shoulder at the same moment you yank off the watch. Apparently, this works. It’s all about distraction. Magicians have a fancy word for distraction. They call it “misdirection.” Personally, I find this irritating. I’ll stick with distraction.

Here’s another example of distraction from a magician. Before the start of a magic show I was dragged to, the audience was encouraged to come on stage and examine this large container to make sure it was real, solid, and had no trap door or hidden egress. Right before the show started the container was turned around by assistants, then closed. When the show opened, the container was turned back around, opened, and the magician stepped out to thunderous applause.

The crazy part is how the trick works. Having the audience check it out ahead of time was just a distraction. When they turned the container around, before they closed the door, the magician strolled casually out of the wings and climbed inside in full-view of the audience. I saw it clearly because I knew it was going to happen (because I had read a book the magician had written). But shouldn’t everyone have seen it? (Don’t even get me started on the “Invisible Gorilla.”)

Which brings me to my old roommate Nick. Read more »

by Steven Gimbel and Gwydion Suilebhan

Whether you love, hate, or tolerate Tesla may say something about the era you grew up in.

Every generation, when it reaches a certain age, makes two proclamations: Saturday Night Live used to be funnier, and “kids these days” are lazy and stupid.

Neither claim is true, of course, but they feel true. We members of Generation X insist SNL isn’t as good as it was, but that’s because they aren’t making jokes for us any more. Their audience now consists largely of Millennials, who have a unique sense of humor shaped by the age in which they were raised. That younger audience isn’t either lazy or stupid, either. Millennials work hard, but in different ways, and they know different things than we do as well.

Still, there are meaningful differences between Gen Xers and Millennials, and one of those differences has become particularly stark of late: our tolerance for moral ambiguity.

As Gen Xers, we grew up in a world in which our favorite sports heroes were discovered taking steroids, and we had to figure out how to keep rooting for them anyway. A world in which bona fide heroes like Senators John Glenn and John McCain could get caught up in a major political scandal and still get re-elected. A world in which our own idealistic (and idealized) Baby Boomer parents entered their peak earning years and started voting for tax cuts instead of justice. We learned to distrust everything and everyone: even those we loved.

We also learned to hold multiple conflicting opinions at the same time. We need more people of color on the Supreme Court AND Clarence Thomas harassed Anita Hill AND the accusations against him played into racist tropes about Black men. Bill Clinton abused his power in having a tryst with Monica Lewinksy AND we shouldn’t portray Lewinsky as a powerless pawn unable to make her own choices AND Clinton’s politics were generally favorable to women AND he was prosecuted by other White men who were equally (or more greatly) compromised.

Life taught us to doubt the existence of pure “good” and “bad.” We came of age in a morally ambiguous world. Millennials, by contrast, came of age in a morally bankrupt world. Read more »

by Brooks Riley