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I’ve been doing Dry January this year. One thing I missed was something for apéro hour, a beverage to mark the start of the evening. Something complex and maybe bitter, not like a drink you’d have with lunch. I found some good options. Ghia sodas are my favorite. Ghia is an NA apéritif based on grape juice but with enough bitterness (gentian) and sourness (yuzu) to be interesting. You can buy a bottle and mix it with soda yourself but I like the little cans with extra flavoring. The Ginger and the Sumac & Chili are both great. Another thing I like are low-sugar fancy soda pops. Not diet drinks, they still have a little sugar, but typically 50 calories a can. De La Calle Tepache is my favorite. Fermented pineapple is delicious and they have some fun flavors. Culture Pop is also good. A friend gave me the Zero book, a drinks cookbook from the fancy restaurant Alinea. This book is a little aspirational but the recipes are doable, it’s just a lot of labor. Very fancy high end drink mixing, really beautiful flavor ideas. The only thing I made was their gin substitute (mostly junipers extracted in glycerin) and it was too sweet for me. Need to find the right use for it, a martini definitely ain’t it. An easier homemade drink is this Nonalcoholic Dirty Lemon Tonic. It’s basically a lemonade heavily flavored with salted preserved lemons, then mixed with tonic. I love the complexity and freshness of this drink and enjoy it on its own merits. Finally, non-alcoholic beer has gotten a lot better in the last few years thanks to manufacturing innovations. I’ve been enjoying NA Black Butte Porter, Stella Artois 0.0, Heineken 0.0. They basically all taste just like their alcoholic uncles, no compromise. One thing to note about non-alcoholic substitutes is they are not cheap. They’ve become a big high end business. Expect to pay the same for an NA drink as one with alcohol even though they aren’t taxed nearly as much.
The Trump administration has made aggressive threats against immigrants in the US. It’s not clear what’s coming, my biggest fear is a violent display of fascism. (Don’t call them camps!) But even if it’s a polite legal process it will be chaotic and disruptive to many neighbors. Back in 2018 I donated reactively to the Trump administration’s cruelty to immigrant families. This time I’m trying to get ahead of it. The need for the money is now, no matter what happens it is going to be a bad few years for immigrants in the US. To that end I asked on Metafilter about charities to donate to. I got back a remarkable reply listing 18 charities that all have some California focus. I donated to most of them. I want to highlight two groups in particular. One is RAICES. They work in Texas, not California, but they are well organized and effective. The other is KIND. They have a simple mission. They try to ensure every unaccompanied minor has legal representation in immigration court (something not guaranteed.) The other groups on the list are all also deserving of consideration.
LLMs are good search helpers. Here’s three search tools I use every day. All of these use an AI to synthesize answers but also provide an essential feature: specific web search results for you to verify and further research. I use these for conversational inquiries in addition to more traditional keyword searches. Phind is an excellent free LLM + search engine. The AI writes an answer to your query but is very careful to provide footnotes to a web-search-like list of links on the right. I use this mostly for directed search queries, things like “what’s an inexpensive TV streaming device?” where I might have used keyword search too. The Llama-70b LLM that powers the free version is quite good, sometimes I have general conversations with it or ask it to generate code. Bing CoPilot has a very similar output result to Phind. I find it a little less useful and the search result links are less prominent. But it’s a good second opinion. Bing has been a very good search engine for 10+ years, I’m grateful to Microsoft for continuing to invest in it. CoPilot results are sometimes volunteered on the main Bing page but you often have to click to get to the ChatGPT 4 Turbo enhanced pages. Kagi is what I use as my general search engine, my Google replacement. It mostly gives traditional keyword search results but sometimes it will volunteer a “Quick Answer” where Claude 3 Haiku synthesizes an answer with references. You can also request one. I think Phind and CoPilot do a better job but I appreciate when Kagi intercepts a keyword search I did and just gives me the right answer. Google has tried various versions of LLM-enhancement in search, I think the current version is called AI Overviews. It’s not bad but it’s also not as good as the others. Not mentioned here: ChatGPT or Claude. Those are general purpose LLMs but they don’t really give search results or specific references. In the old days they’d make up URLs if you asked but that’s improving.
8BitDo makes good game controllers. A wide variety of styles from retro to mainstream, with some unusual shapes. And wide compatibility with various systems: PC, Macs, Switch, Android. They’re well built, work right, and quite inexpensive. A far cry from the MadCatz-style junk we used to get. The new hotness is the Ultimate 2C, an Xbox-style wireless controller for the very low price of $30. But it works great, doesn’t feel cheap at all. The fancier mainstream choice is the Ultimate 2.4g at $50 which includes a charging stand and extra reprogrammability. But what’s really interesting to me are the odd layouts, often small or retro. The SN30 Pro is particularly interesting as a portable controller. SNES-styling but a full XBox style modern controller with two analog sticks, easy to throw in a suitcase. There’s a lot of fiddly details for this class of device. Controller type (XInput, DInput, switch, etc), wireless interface (Bluetooth or proprietary), etc. 8BitDo makes good choices and implementations for all that stuff I’ve tested. They seem to work well with Steam. They’re a popular brand so well tested. It helps that PC game controllers have mostly standardized around the Xbox layout and XInput. Steam can patch over any rough spots for older games.
PreSonus makes good computer speakers. They’re marketed as “reference monitors” but at $100 for a small set I have my doubts about their referenceness. Fortunately I have a tin ear and they sound just fine for my computer playing YouTube videos, compressed music, games. Wirecutter agrees. The specific ones I have are these 3.5" Bluetooth speakers for $150. Inputs are RCA line-in, balanced, and Bluetooth, also an Aux-In and Headphone jacks on the front. Decent amplifier, plenty loud for an office. There’s 100Hz and 10kHz equalization knobs and a Bluetooth pairing button in the back. The “Gen 2” version includes an optional standby mode for power savings which seems to work fine. The cabinet is MDF and while it’s light it doesn’t have that hollow sound of cheap plastic. The website only promises 80 Hz so these are not the speakers for bass thumping. Fifteen years ago I recommended the M-Audio speakers. IIRC their quality went downhill, maybe they went to plastic enclosures? I also had some Creative Mackie speakers but they have a manufacturing problem that causes them to fail after a few years. We’ll see how long these PreSonus ones last. I’m self-conscious how this post looks like a spammy marketing affiliate page written by an AI. It’s not! I just like the product.
More in programming
Last year I wrote about inlining just the fast path of Lemire’s algorithm for nearly-divisionless unbiased bounded random numbers. The idea was to reduce code bloat by eliminating lots of copies of the random number generator in the rarely-executed slow paths. However a simple split prevented the compiler from being able to optimize cases like pcg32_rand(1 << n), so a lot of the blog post was toying around with ways to mitigate this problem. On Monday while procrastinating a different blog post, I realised that it’s possible to do better: there’s a more general optimization which gives us the 1 << n special case for free. nearly divisionless Lemire’s algorithm has about 4 neat tricks: use multiplication instead of division to reduce the output of a random number generator modulo some limit eliminate the bias in (1) by (counterintuitively) looking at the lower digits fun modular arithmetic to calculate the reject threshold for (2) arrange the reject tests to avoid the slow division in (3) in most cases The nearly-divisionless logic in (4) leads to two copies of the random number generator, in the fast path and the slow path. Generally speaking, compilers don’t try do deduplicate code that was written by the programmer, so they can’t simplify the nearly-divisionless algorithm very much when the limit is constant. constantly divisionless Two points occurred to me: when the limit is constant, the reject threshold (3) can be calculated at compile time when the division is free, there’s no need to avoid it using (4) These observations suggested that when the limit is constant, the function for random numbers less than a limit should be written: static inline uint32_t pcg32_rand_const(pcg32_t *rng, uint32_t limit) { uint32_t reject = -limit % limit; uint64_t sample; do sample = (uint64_t)pcg32_random(rng) * (uint64_t)limit); while ((uint32_t)(sample) < reject); return ((uint32_t)(sample >> 32)); } This has only one call to pcg32_random(), saving space as I wanted, and the compiler is able to eliminate the loop automatically when the limit is a power of two. The loop is smaller than a call to an out-of-line slow path function, so it’s better all round than the code I wrote last year. algorithm selection As before it’s possible to automatically choose the constantly-divisionless or nearly-divisionless algorithms depending on whether the limit is a compile-time constant or run-time variable, using arcane C tricks or GNU C __builtin_constant_p(). I have been idly wondering how to do something similar in other languages. Rust isn’t very keen on automatic specialization, but it has a reasonable alternative. The thing to avoid is passing a runtime variable to the constantly-divisionless algorithm, because then it becomes never-divisionless. Rust has a much richer notion of compile-time constants than C, so it’s possible to write a method like the follwing, which can’t be misused: pub fn upto<const LIMIT: u32>(&mut self) -> u32 { let reject = LIMIT.wrapping_neg().wrapping_rem(LIMIT); loop { let (lo, hi) = self.get_u32().embiggening_mul(LIMIT); if lo < reject { continue; } else { return hi; } } } assert!(rng.upto::<42>() < 42); (embiggening_mul is my stable replacement for the unstable widening_mul API.) This is a nugatory optimization, but there are more interesting cases where it makes sense to choose a different implementation for constant or variable arguments – that it, the constant case isn’t simply a constant-folded or partially-evaluated version of the variable case. Regular expressions might be lex-style or pcre-style, for example. It’s a curious question of language design whether it should be possible to write a library that provides a uniform API that automatically chooses constant or variable implementations, or whether the user of the library must make the choice explicit. Maybe I should learn some Zig to see how its comptime works.
I developed seasonal allergies relatively late in life. From my late twenties onward, I spent many miserable days in the throes of sneezing, headache, and runny eyes. I tried everything the doctors recommended for relief. About a million different types of medicine, several bouts of allergy vaccinations, and endless testing. But never once did an allergy doctor ask the basic question: What kind of air are you breathing? Turns out that's everything when you're allergic to pollen, grass, and dust mites! The air. That's what's carrying all this particulate matter, so if your idea of proper ventilation is merely to open a window, you're inviting in your nasal assailants. No wonder my symptoms kept escalating. For me, the answer was simply to stop breathing air full of everything I'm allergic to while working, sleeping, and generally just being inside. And the way to do that was to clean the air of all those allergens with air purifiers running HEPA-grade filters. That's it. That was the answer! After learning this, I outfitted everywhere we live with these machines of purifying wonder: One in the home office, one in the living area, one in the bedroom. All monitored for efficiency using Awair air sensors. Aiming to have the PM2.5 measure read a fat zero whenever possible. In America, I've used the Alen BreatheSmart series. They're great. And in Europe, I've used the Philips ones. Also good. It's been over a decade like this now. It's exceptionally rare that I have one of those bad allergy days now. It can still happen, of course — if I spend an entire day outside, breathing in allergens in vast quantities. But as with almost everything, the dose makes the poison. The difference between breathing in some allergens, some of the time, is entirely different from breathing all of it, all of the time. I think about this often when I see a doctor for something. Here was this entire profession of allergy specialists, and I saw at least a handful of them while I was trying to find a medical solution. None of them even thought about dealing with the environment. The cause of the allergy. Their entire field of view was restricted to dealing with mitigation rather than prevention. Not every problem, medical or otherwise, has a simple solution. But many problems do, and you have to be careful not to be so smart that you can't see it.
A few months ago I wrote about what it means to stay gold — to hold on to the best parts of ourselves, our communities, and the American Dream itself. But staying gold isn’t passive. It takes work. It takes action. It takes hard conversations that ask
