I’m sorry to say it, but TeX is no longer superior to my work. L'imprimerie de Kary is way better now :(
“I Write The Songs” by Barry Manilow is sort of music that drives my father mad, but boy do I love it.
So EB Garamond stands for Egenolff-Berner-Garamond
The arabesque is a form of artistic decoration consisting of “surface decorations based on rhythmic linear patterns of scrolling and interlacing foliage, tendrils” or plain lines, often combined with other elements.
Thomas Maitland Cleland (August 18, 1880 – November 9, 1964) was an American book designer, painter, illustrator, and type designer.
What if I told you that every Mac since 2022 ships a pair of daemons whose only purpose in life is to build a graph about you and the people around you: who you are, who you know, how those people are related to you and to each other, how you communicate with them, where you go, with whom, what you do and when. This graph is built on device by cross-referencing pretty much everything on the machine: Contacts, Calendar, Photos, Messages, Mail, location, Screen Time and a long tail of behavioral signals. And, more importantly, it is held as a queryable store that LLMs retrieve from (allegedly). Would you believe me?
The two daemons keep their work in ~/Library/IntelligencePlatform, a directory of SQLite databases (fifty-one databases) stored in plaintext but located in a zone protected by TCC Full Disk Access.
Likely, the most interesting is graph.db. It is a triple store written in a vocabulary of 181 entity classes and 278 predicates: every row is a subject, a predicate and an object. The subject is an entity (a person, an app, an event); the object is either a plain value (a name, a handle, a date) or another entity, which is where the graph gets its edges. The predicate is the interesting part: it says what kind of relationship the system believes holds between the two.
In tables of their own, sit who appears with whom in your photos; the communication log (who, when, which app, which direction; no content), which also pulls from your other devices; location and movement; and a long tail of device signals (screen locked, Wi-Fi, Bluetooth, charging, ambient light, and a stream named ContextualUnderstanding.PhysicalSocial whose record format lists people by name, phone and email, each with a start and an end time; it reads like a log of who was physically around you, though we never saw it filled in).
A pair of XGBoost classifiers decides who is family from 144 mostly behavioral features, two embedding models are one of ten signals the system uses to decide when two records are the same person, twelve analyzers in Photos score partner, parent, child, coworker and friend from who appears in your pictures with you, on which trips and holidays, and Apple’s on-device LLM reads your messages to put a name and a relationship on a face (if Apple Intelligence is active). Whatever the method, every row lands in the graph with a confidence attached, a number between 0 and 1.
Well, if you want your partner not to discover some contacts you might have deleted and their “closeness” to you, better to drop some rows from expired_stable_graph too (unfortunately, you have to do it manually). But I am sure you have nothing to hide (just joking).
The most important point, though, is that this is not only about you (the person using the Mac). The people around you are in it too: your family, your friends, “anyone” you have talked to through your device. None of them was asked, and the store links them to you and, through the events and groups they share, to each other. A relationship is intelligence one level above the rows it was inferred from. For instance, by correlating across my own store, I (well, an LLM working for me) could easily work out the following:
That there is a child in the household, and roughly how old. The family-member types and a family circle give the household. The scorecard’s child and son/daughter columns give the child’s place in it. Beside it sits an age, copied from Family Sharing; and dates of birth in the store can carry the system’s own word imputed, though what the system means by it is not clear to us.
Which daycare the child goes to, and both of the numbers that reach it. Copied off contact cards. Note what is not there: the calendar has no school-run event, so the store holds the institution and its lines but not the hour the child is dropped off. That is still enough to call a parent from a number their phone already trusts.
Where the family will be, on which days, between which hours. One calendar event, a place, two stored time slots and a title that names the family (so the guest list is in the string even where the attendee rows are empty).
Which of the family will be there. The scorecard names the ones scored as family, a household entity holds them together, and a Family Sharing circle says which of them are in the same family group.
And, in the same file, what is installed on the machine, down to the password manager.
The reality is that the amount of information in this store is really something else: every time we dig into what the daemons infer, and how, a few new lines of investigation open up. Whatever you would rather no one knew about you or your family may well be in there somewhere, and we think you have the right to know whether it is. What you get instead: no documentation, no way to inspect the store and no general way to correct an inference that is wrong.
Georg [
When it came to writing his master thesis, he was looking for a font to set the thesis in. He started the EB Garamond project after unsuccessfully searching for an open source Garamond font that provided advanced typographic features as well as Greek and phonetic characters.
After finishing his studies in romance languages, Georg completed a post graduate programme in library and information science during which he had the opportunity to study various printed works from the 16th to 19th century in the course of an internship at the department for rare and old books at the Austrian National Library. Currently, Georg is a systems librarian at the WU Vienna University of Economics and Business.
A fleuron (/ˈflʊərɒn, -ən, ˈflɜːrɒn, -ən/), also known as a printers’ flower, is a typographical symbol, or glyph, used either as a punctuation mark or as an ornament for typographic compositions. Fleurons are stylized forms of flowers or leaves; the term derives from the Old French: floron (‘flower’). Robert Bringhurst in The Elements of Typographic Style calls the forms “horticultural dingbats”. A commonly encountered fleuron is the ❦, the floral heart or hedera (ivy leaf), also known as an aldus leaf after Italian Renaissance printer Aldus Manutius.
