Language Log

I Used to Know How to Write in Japanese:
Somehow, though, I can still read it
Marco Giancotti, Aether Mug (August 14, 2025)

During the last thirty to forty years, two of the most popular dictionaries for mastering sinographs were those of James Heisig and Rick Harbaugh.  I was dubious about the efficacy of both and wished that my students wouldn't use them, but language learners flocked to these extremely popular dictionaries, thinking that they offered a magic trick for remembering the characters.

The latter relied on fallacious etymological "trees" and was written by an economist, and the former was based on brute memorization enhanced by magician's tricks and was written by a philosopher of religion.  Both placed characters on a pedestal of visuality / iconicity without integrating them with spoken language.

I have already done a mini-review of Harbaugh's Chinese Characters and Culture: A Genealogy and Dictionary (New Haven: Yale Far Eastern Publications, 1998) on pp. 25-26 here:  Reviews XI, Sino-Platonic Papers, 145 (August, 2004).  The remainder of this post will consist of extracts of Giancotti's essay and the view of a distinguished Japanologist-linguist on Heisig's lexicographical methods.

Forty-five or so years ago, my Chinese and émigré friends who knew Chinese language and were familiar with Chinese society and culture used to josh each other about these terms:

fūrén 夫人 ("madam; Mrs.")

wàifū 外夫 ("outside husband", but sounds like "wife")

nèirén 內人 (lit., "inside person", i.e. my "[house]wife")

The first term is an established lexical item, and the second two are jocular or ad hoc, plus there are other regional and local expressions formed in a similar fashion, as well as some japonismes.

All of these terms were formed from the following four morphosyllables:

fū 夫 ("man; male adult; husband")

rén 人 ("man; person; people")

wài 外 ("outside")

nèi 內 ("inside")

The following sentence in this Bloomberg story

I’m of the mindset that no car payment is better than a new car payment – hence why my 2017 Volvo will likely stick around for a few more years – but I’ve been enticed more about the electric vehicles on the market.

…could lead the reader down a garden path of wondering why a new car payment is the best car payment.

In an update to "Morpho-phonologically AI", I wrote

Ironically, since this puzzle was vocalically inspired by the term "AI" , I'm guessing that current AI systems are not very good at solving (or creating) puzzles like this. I'll give it a try later today.

But it seems that I was wrong.

"OpenAI Brings Back Fan-Favorite GPT-4o After a Massive User Revolt", Gizmodo 8/10/2025:

After a disastrous 72 hours that saw its most loyal users in open revolt, OpenAI is making a major U-turn.

In a series of posts on X (formerly Twitter) Sunday, CEO Sam Altman announced that the company is bringing back its beloved older AI models, including GPT-4o, and dramatically increasing usage limits for paying subscribers, a clear peace offering to a furious customer base.

Avram Pitch, "Meet President Willian H. Brusen from the great state of Onegon", The Register 8/8/2025:

OpenAI's GPT-5, unveiled on Thursday, is supposed to be the company's flagship model, offering better reasoning and more accurate responses than previous-gen products. But when we asked it to draw maps and timelines, it responded with answers from an alternate dimension.

AI Is Helping Historians With Their Latin
A new tool fills in missing portions of ancient inscriptions from the Roman Empire

By Nidhi Subbaraman Aug. 6, 2025

In recent years, we have encountered many cases of AI assisting (or not) in the decipherment of ancient manuscripts in diverse languages.  See several cases listed in the "Selected readings".  Now it's Latin's turn to benefit from the ministrations of artificial intelligence.

People across the Roman Empire wrote poetry, kept business accounts and described their conquests and ambitions in inscriptions on pots, plaques and walls.

The surviving text gives historians a rare glimpse of life in those times—but most of the objects are broken or worn.

“It’s like trying to solve a gigantic jigsaw puzzle, only there is tens of thousands more pieces to that puzzle, and about 90% of them are missing,” said Thea Sommerschield, a historian at the University of Nottingham.

Now, artificial intelligence is filling in the blanks.

An AI tool designed by Sommerschield and other European scientists can predict the missing text of partially degraded Latin inscriptions made hundreds of years ago and help historians estimate their date and place of origin.

From here (at least that's where I saw it):

The last couple of months have seen some interesting publications about AI systems that are small by modern standards.

From Yann LeCun's presentation at the AI, Science and Society event in Paris last February:

The most interesting LLM research that I've seen recently is from Alex Cloud and others at Anthropic and Truthful AI, "Subliminal Learning: Language models transmit behavioral traits via hidden signals in data", 7/20/2025:

ABSTRACT: We study subliminal learning, a surprising phenomenon where language models transmit behavioral traits via semantically unrelated data. In our main experiments, a "teacher" model with some trait T (such as liking owls or being misaligned) generates a dataset consisting solely of number sequences. Remarkably, a "student" model trained on this dataset learns T. This occurs even when the data is filtered to remove references to T. We observe the same effect when training on code or reasoning traces generated by the same teacher model. However, we do not observe the effect when the teacher and student have different base models. To help explain our findings, we prove a theoretical result showing that subliminal learning occurs in all neural networks under certain conditions, and demonstrate subliminal learning in a simple MLP classifier. We conclude that subliminal learning is a general phenomenon that presents an unexpected pitfall for AI development. Distillation could propagate unintended traits, even when developers try to prevent this via data filtering.

The PR campaign for the Unitree GI Robot now comes in at least three local variants: the "Uncle Bot" in China,  "Jake the Rizzbot" in Austin, and a gay version of Jake in Los Angeles.

Joel Becker et al., "Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity", METR 7/10/2025:

Despite widespread adoption, the impact of AI tools on software development in the wild remains understudied. We conduct a randomized controlled trial (RCT) to understand how AI tools at the February–June 2025 frontier affect the productivity of experienced open-source developers. 16 developers with moderate AI experience complete 246 tasks in mature projects on which they have an average of 5 years of prior experience. Each task is randomly assigned to allow or disallow usage of early-2025 AI tools. When AI tools are allowed, developers primarily use Cursor Pro, a popular code editor, and Claude 3.5/3.7 Sonnet. Before starting tasks, developers forecast that allowing AI will reduce completion time by 24%. After completing the study, developers estimate that allowing AI reduced completion time by 20%. Surprisingly, we find that allowing AI actually increases completion time by 19%—AI tooling slowed developers down. This slowdown also contradicts predictions from experts in economics (39% shorter) and ML (38% shorter). To understand this result, we collect and evaluate evidence for 20 properties of our setting that a priori could contribute to the observed slowdown effect—for example, the size and quality standards of projects, or prior developer experience with AI tooling. Although the influence of experimental artifacts cannot be entirely ruled out, the robustness of the slowdown effect across our analyses suggests it is unlikely to primarily be a function of our experimental design.