Friday, 14th March 2025
[...] in 2013, I did not understand that the things I said had meaning. I hate talking about this because it makes me seem more important than I am, but it’s also important to acknowledge. I saw myself at the time as just Steve, some random guy. If I say something on the internet, it’s like I’m talking to a friend in real life, my words are just random words and I’m human and whatever. It is what it is.
But at that time in my life, that wasn’t actually the case. I was on the Rails team, I was speaking at conferences, and people were reading my blog and tweets. I was an “influencer,” for better or worse. But I hadn’t really internalized that change in my life yet. And so I didn’t really understand that if I criticized something, it was something thousands of people would see.
— Steve Klabnik, Choosing Languages
Merklemap runs a 16TB PostgreSQL. Interesting thread on Hacker News where Pierre Barre describes the database architecture behind Merklemap, a certificate transparency search engine.
I run a 100 billion+ rows Postgres database [0], that is around 16TB, it's pretty painless!
There are a few tricks that make it run well (PostgreSQL compiled with a non-standard block size, ZFS, careful VACUUM planning). But nothing too out of the ordinary.
ATM, I insert about 150,000 rows a second, run 40,000 transactions a second, and read 4 million rows a second.
[...]
It's self-hosted on bare metal, with standby replication, normal settings, nothing "weird" there.
6 NVMe drives in raidz-1, 1024GB of memory, a 96 core AMD EPYC cpu.
[...]
About 28K euros of hardware per replica [one-time cost] IIRC + [ongoing] colo costs.
Something Is Rotten in the State of Cupertino. John Gruber's blazing takedown of Apple's failure to ship many of the key Apple Intelligence features they've been actively promoting for the past twelve months.
The fiasco here is not that Apple is late on AI. It's also not that they had to announce an embarrassing delay on promised features last week. Those are problems, not fiascos, and problems happen. They're inevitable. [...] The fiasco is that Apple pitched a story that wasn't true, one that some people within the company surely understood wasn't true, and they set a course based on that.
John divides the Apple Intelligence features into the ones that were demonstrated to members of the press (including himself) at various events over the past year compared to things like "personalized Siri" that were only ever shown as concept videos. The ones that were demonstrated have all shipped. The concept video features are indeterminably delayed.
How ProPublica Uses AI Responsibly in Its Investigations. Charles Ornstein describes how ProPublic used an LLM to help analyze data for their recent story A Study of Mint Plants. A Device to Stop Bleeding. This Is the Scientific Research Ted Cruz Calls “Woke.” by Agnel Philip and Lisa Song.
They ran ~3,400 grant descriptions through a prompt that included the following:
As an investigative journalist, I am looking for the following information
--
woke_description: A short description (at maximum a paragraph) on why this grant is being singled out for promoting "woke" ideology, Diversity, Equity, and Inclusion (DEI) or advanced neo-Marxist class warfare propaganda. Leave this blank if it's unclear.
why_flagged: Look at the "STATUS", "SOCIAL JUSTICE CATEGORY", "RACE CATEGORY", "GENDER CATEGORY" and "ENVIRONMENTAL JUSTICE CATEGORY" fields. If it's filled out, it means that the author of this document believed the grant was promoting DEI ideology in that way. Analyze the "AWARD DESCRIPTIONS" field and see if you can figure out why the author may have flagged it in this way. Write it in a way that is thorough and easy to understand with only one description per type and award.
citation_for_flag: Extract a very concise text quoting the passage of "AWARDS DESCRIPTIONS" that backs up the "why_flagged" data.
This was only the first step in the analysis of the data:
Of course, members of our staff reviewed and confirmed every detail before we published our story, and we called all the named people and agencies seeking comment, which remains a must-do even in the world of AI.
I think journalists are particularly well positioned to take advantage of LLMs in this way, because a big part of journalism is about deriving the truth from multiple unreliable sources of information. Journalists are deeply familiar with fact-checking, which is a critical skill if you're going to report with the assistance of these powerful but unreliable models.
Agnel Philip:
The tech holds a ton of promise in lead generation and pointing us in the right direction. But in my experience, it still needs a lot of human supervision and vetting. If used correctly, it can both really speed up the process of understanding large sets of information, and if you’re creative with your prompts and critically read the output, it can help uncover things that you may not have thought of.
Apple’s Siri Chief Calls AI Delays Ugly and Embarrassing, Promises Fixes (via) Mark Gurman reports on some leaked details from internal Apple meetings concerning the delays in shipping personalized Siri. This note in particular stood out to me:
Walker said the decision to delay the features was made because of quality issues and that the company has found the technology only works properly up to two-thirds to 80% of the time. He said the group “can make more progress to get those percentages up, so that users get something they can really count on.” [...]
But Apple wants to maintain a high bar and only deliver the features when they’re polished, he said. “These are not quite ready to go to the general public, even though our competitors might have launched them in this state or worse.”
I imagine it's a lot harder to get reliable results out of small, local LLMs that run on an iPhone. Features that fail 1/3 to 1/5 of the time are unacceptable for a consumer product like this.
TIL: Styling an HTML dialog modal to take the full height of the viewport.
I spent some time today trying to figure out how to have a modal <dialog> element present as a full height side panel that animates in from the side. The full height bit was hard, until Natalie helped me figure out that browsers apply a default max-height: calc(100% - 6px - 2em); rule which needs to be over-ridden.
Also included: some spelunking through the HTML spec to figure out where that calc() expression was first introduced. The answer was November 2020.