While recovering from the flu I’ve decided to review my Reddit subscriptions. I’ve been spending more time there recently because of niche communities like /r/Tiki, and removing subscriptions is about all the mental work I can handle right now with this stabbing headache.

Communities I used to love that didn’t make the cut:

• /r/castiron – Used to be a great place to source and identify cast iron 10 years ago, but now is full of people making the same stupid jokes. Also full of misinformation.
• /r/kombucha – I used to make a lot of kombucha, but I’ve mostly stopped because I’m the only one who likes it in our house. It seems like every post is a blurry image of a scoby with a dot on it and the caption, “Is this mold?”
• /r/HelloInternet – The podcast clearly is never coming back. Farewell my old friend.
• /r/DataIsBeautiful – I joined this for inspiration when I was learning data visualization and messing around with D3.js. I’m not into that as much anymore, but also the visualizations are becoming more complicated than they need to be. The more complicated ones get the upvotes, the actual nice simple ones that I prefer get left in the dust.

I also removed some of the default communities that I hadn’t gotten around to removing yet. Nice to clean up that timeline a bit.

Protip: For any free Substack, the feed is at [newslettername].substack.com/feed

I’m going through and unsubscribing from their emails and instead subscribing to their RSS feeds. I haven’t yet found a way to get a feed for paid newsletters, so I still route those from email to RSS with Feedbin.

The process was pretty quick. I went to https://substack.com/library, opened up the console, did a document.querySelectorAll() for the anchor tag for each publication (my selector will be different than yours so I didn’t include it–yay React!), then extracted the URLs and appended /feed with some quick regex in VSCode. I popped that list into https://opml-gen.ovh/, then imported the OPML into NetNewsWire.

TIL that the default feed cache when you are using fetch_feed() in WordPress is 12 hours and you can override it with a hook: wp_feed_cache_transient_lifetime

Hmm, this posted to Twitter by going through Bridgy. I know I use a micropub token to push to Bridgy, but since I don’t see anything in Twitter’s docs about micropub, I assume Bridgy uses the standard API for third party clients.

Twitter’s API for third party clients seems to be down, and it is unclear whether that is a bug or a policy decision. Writing this to test and see if micropub tokens are down, too.

Charlie’s symptoms match RSV and it is no joke. This poor kid has been very sick since Monday and wants to be held 24/7 (normally when he is awake he is very busy and does not want to be held). He seems miserable, but with none of the warning signs of needing to go to the doctor.

He’s been sick a lot in the last 6 months, but nothing like this.

I’m thankful that Amanda and I both have flexible jobs and can trade off days holding him so the other can work. Lots of feverish working during his naps, too.

Map of tiki bars!

Far more interesting than most data visualizations is the follow-up article about how they collected, normalized, and analyzed the data, the tools they used, and how they used them.

Emily Weil recommends checking out this resource before diving in to The Book of Shaders.

“SO2 (sulphur dioxide) is a very reactive molecule that binds with different types of wine compounds (aldehydes, phenols, etc.) that play a role in forming a wine’s aroma. In that sense minimizing the usage of sulfites is a reasonable practice in winemaking. The efficiency of it however, depends very much on the wine’s pH due to the higher activity of the molecular form of sulfites. From the sensorial point of view, sulfites mask some of the effects of the oxidation because of how they bind quickly with aldehydes, as well as partially preventing oxidation because their redox potential. Another quite important aspect is related to the prevention of bacterial growth and yeast development.

When a wine has no sulfites added and passes through malolactic conversion, byproducts can occur after the transformation of all the malic acid as a consequence of existing residual bacteria. The result is considerable amounts of biogenic amines (histamine, cadaverine, putrescine, etc.) There are some people that are quite allergic to histamines for example which can result in adverse health effects.

What this means is that besides the known disadvantages of too much SO2 in wine, it’s also the case that with no sulfites at all, similar health problems may occur to those susceptible in addition to potential spoilage of the wine, especially in high pH wines.

Sometimes the reason a toddler is crying changes mid-cry, so if the normal consolation method isn’t working for the reason you thought they were crying, go back to square one.

Today Charlie is sick and had a fever. We assumed the fever was bothering him (maybe a headache too?) and started cooling his head down and gave him Tylenol. That soothed him somewhat. After about 30 minutes of on and off crying, he wouldn’t let me cool his head with a washcloth anymore. Turns out he was hungry after his fever let up and offering him a snack and some water did the trick (after him not wanting to eat for most of the day).

This is a clever way to make patterned ice, and I happen to have these cookie stamps!

I took a photo last year of an apple tree trained in this way on Old Post Rd S in Croton-on-Hudson, but didn’t know what to call it. Turns out it is called Espalier.

I’d like to try to train a tree in this way.

I’m trying to up my POSSE game, but it isn’t so easy to publish short posts to my site when I’m not at my desktop.

I’ve tried three micropub clients on iOS and none of them worked for me.

• iAWriter returns a 400 invalid request error
• The Drafts.app Micropub action gives me a 200 success code, but never ends up on my site 🤔
• Micro.blog app will only allow me to publish to the Posts post type, but I want to publish to my Notes post type

The only thing that worked reliably was Quill, via the web.

Some ideas of things I can build to make the experience better:

1. A Shortcuts action to publish to a Micropub endpoint. Here is what ChatGPT had to say about that:

This shortcut could work in two ways: Tap the shortcut and get a field to enter your note, then send it. Or select an image from your camera roll and post it via a shortcut share action.

2. A new Drafts.app micropub action with more options.

3. An Obsidian extension to publish via micropub.

Fondue night was a hit last night, but a consequence I hadn’t considered is that Charlie may refuse to eat anything for the next couple of days if he can’t poke it with a fondue fork first 🫕 🤷‍♂️

The core thing to remember with coffee is that freshly roasted beans matter more than anything else. No fancy equipment can overcome not having fresh beans.

14 years with a WordPress.com account. I’m pretty sure I initially signed up to use Akismet, and I had no idea I’d end up working there years later!

Most search models in use these days are based on lexical similarity, or how many important words overlap. A more accurate model is based on semantic similarity, or how much abstract meaning overlaps.

Semantic similarity is based upon transformer models, a type of deep learning model, that creates an embedding to represent each document’s semantic meaning.

Lexical similarity is great if you know the exact keywords you are searching for, but brittle if you do not. Take two examples:

1. Obama speaks to the media in Illinois.
2. The President greets the press in Chicago.

For anyone familiar with US politics, the first example essentially says the same thing as the second – in other words, they are semantically (conceptually) similar. However, the important words in the two examples don’t match up. So the lexical similarity won’t return the same results.

A semantic similarity approach matches up the words Obama and President, media and press, Illinois and Chicago, and speaks and greets.

I hadn’t considered that those models measure similarity between two words, but not between two sets of words, called documents in the parlance:

As it turns out, current state-of-the-art language models are good at measuring the similarity between two words, but not great at measuring the similarity between two documents. We had to perform a considerable amount of R&D work to develop a transformer model that could create document embeddings—we hope to go into the gory details of this work in future technical posts.

One essential trick was to use word mover distance to create labels for pairs of documents in an unsupervised manner—so that our model could learn how to map a document’s word embeddings into a single document embedding. But, for now, the example above gives you the high-level idea behind our approach.