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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,...
2 months ago

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More from Nelson's Weblog

Angkor Wat resources

I took an amazing trip to SE Asia last month, including Angkor Wat. I had a hard time finding good reading or other resources to learn from before I went, in part because Amazon is awash in AI garbage. Here’s some books and podcasts I found useful about the Khmer empire in general and Angkor in particular: Ancient Angkor by Michael Freeman and Claude Jacques. The closest thing to a coffee-table book to preview what you will see. The practical information is outdated but the pictures and descriptions are good. Empire Podcast #185: The God Kings of Angkor Wat by William Dalrymple and Anita Anand. An entertaining and fully detailed account of the Khmer empire. It’s basically an excerpt from Dalrymple’s new book The Golden Road: How Ancient India Transformed the World. Fall of Civilizations Podcast #5: The Khmer Empire by Paul Cooper. Another history, not quite as magically well told as Dalrymple but full of good information. Angkor and the Khmer Civilization by Michael D. Coe. A highly recommended history of the Khmer region. Honestly I found this very dry and too detailed, but I did learn from it. Lonely Planet Pocket Guide: Siem Reap & the Temples of Angkor. We didn’t use this much but it seemed like a useful practical guide. OTOH it dates to 2018 so things have changed. My other advice for visiting Siem Reap and Angkor is: go. It is amazing. Plan for at least two full days of touristing there. Hire a private guide and driver if you can, it is absolutely worth it. (Email me for a recommendation.)

a week ago 13 votes
Legal aid charities for immigrants (2024)

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.

4 months ago 55 votes
AI enhanced search

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.

6 months ago 92 votes
8BitDo Game Controllers

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.

7 months ago 93 votes

More in programming

1995 Was the Most Important Year for the Web

The world changed a lot in 1995. And for the web, it was a transformational year. The post 1995 Was the Most Important Year for the Web appeared first on The History of the Web.

15 hours ago 3 votes
Solving a "Layton Puzzle" with Prolog

I have a lot in the works for the this month's Logic for Programmers release. Among other things, I'm completely rewriting the chapter on Logic Programming Languages. I originally showcased the paradigm with puzzle solvers, like eight queens or four-coloring. Lots of other demos do this too! It takes creativity and insight for humans to solve them, so a program doing it feels magical. But I'm trying to write a book about practical techniques and I want everything I talk about to be useful. So in v0.9 I'll be replacing these examples with a couple of new programs that might get people thinking that Prolog could help them in their day-to-day work. On the other hand, for a newsletter, showcasing a puzzle solver is pretty cool. And recently I stumbled into this post by my friend Pablo Meier, where he solves a videogame puzzle with Prolog:1 Summary for the text-only readers: We have a test with 10 true/false questions (denoted a/b) and four student attempts. Given the scores of the first three students, we have to figure out the fourth student's score. bbababbabb = 7 baaababaaa = 5 baaabbbaba = 3 bbaaabbaaa = ??? You can see Pablo's solution here, and try it in SWI-prolog here. Pretty cool! But after way too long studying Prolog just to write this dang book chapter, I wanted to see if I could do it more elegantly than him. Code and puzzle spoilers to follow. (Normally here's where I'd link to a gentler introduction I wrote but I think this is my first time writing about Prolog online? Uh here's a Picat intro instead) The Program You can try this all online at SWISH or just jump to my final version here. :- use_module(library(dif)). % Sound inequality :- use_module(library(clpfd)). % Finite domain constraints First some imports. dif lets us write dif(A, B), which is true if A and B are not equal. clpfd lets us write A #= B + 1 to say "A is 1 more than B".2 We'll say both the student submission and the key will be lists, where each value is a or b. In Prolog, lowercase identifiers are atoms (like symbols in other languages) and identifiers that start with a capital are variables. Prolog finds values for variables that match equations (unification). The pattern matching is real real good. % ?- means query ?- L = [a,B,c], [Y|X] = [1,2|L], B + 1 #= 7. B = 6, L = [a, 6, c], X = [2, a, 6, c], Y = 1 Next, we define score/33 recursively. % The student's test score % score(student answers, answer key, score) score([], [], 0). score([A|As], [A|Ks], N) :- N #= M + 1, score(As, Ks, M). score([A|As], [K|Ks], N) :- dif(A, K), score(As, Ks, N). First key is the student's answers, second is the answer key, third is the final score. The base case is the empty test, which has score 0. Otherwise, we take the head values of each list and compare them. If they're the same, we add one to the score, otherwise we keep the same score. Notice we couldn't write if x then y else z, we instead used pattern matching to effectively express (x && y) || (!x && z). Prolog does have a conditional operator, but it prevents backtracking so what's the point??? A quick break about bidirectionality One of the coolest things about Prolog: all purely logical predicates are bidirectional. We can use score to check if our expected score is correct: ?- score([a, b, b], [b, b, b], 2). true But we can also give it answers and a key and ask it for the score: ?- score([a, b, b], [b, b, b], X). X = 2 Or we could give it a key and a score and ask "what test answers would have this score?" ?- score(X, [b, b, b], 2). X = [b, b, _A], dif(_A,b) X = [b, _A, b], dif(_A,b) X = [_A, b, b], dif(_A,b) The different value is written _A because we never told Prolog that the array can only contain a and b. We'll fix this later. Okay back to the program Now that we have a way of computing scores, we want to find a possible answer key that matches all of our observations, ie gives everybody the correct scores. key(Key) :- % Figure it out score([b, b, a, b, a, b, b, a, b, b], Key, 7), score([b, a, a, a, b, a, b, a, a, a], Key, 5), score([b, a, a, a, b, b, b, a, b, a], Key, 3). So far we haven't explicitly said that the Key length matches the student answer lengths. This is implicitly verified by score (both lists need to be empty at the same time) but it's a good idea to explicitly add length(Key, 10) as a clause of key/1. We should also explicitly say that every element of Key is either a or b.4 Now we could write a second predicate saying Key had the right 'type': keytype([]). keytype([K|Ks]) :- member(K, [a, b]), keytype(Ks). But "generating lists that match a constraint" is a thing that comes up often enough that we don't want to write a separate predicate for each constraint! So after some digging, I found a more elegant solution: maplist. Let L=[l1, l2]. Then maplist(p, L) is equivalent to the clause p(l1), p(l2). It also accepts partial predicates: maplist(p(x), L) is equivalent to p(x, l1), p(x, l2). So we could write5 contains(L, X) :- member(X, L). key(Key) :- length(Key, 10), maplist(contains([a,b]), L), % the score stuff Now, let's query for the Key: ?- key(Key) Key = [a, b, a, b, a, a, b, a, a, b] Key = [b, b, a, b, a, a, a, a, a, b] Key = [b, b, a, b, a, a, b, b, a, b] Key = [b, b, b, b, a, a, b, a, a, b] So there are actually four different keys that all explain our data. Does this mean the puzzle is broken and has multiple different answers? Nope The puzzle wasn't to find out what the answer key was, the point was to find the fourth student's score. And if we query for it, we see all four solutions give him the same score: ?- key(Key), score([b, b, a, a, a, b, b, a, a, a], Key, X). X = 6 X = 6 X = 6 X = 6 Huh! I really like it when puzzles look like they're broken, but every "alternate" solution still gives the same puzzle answer. Total program length: 15 lines of code, compared to the original's 80 lines. Suck it, Pablo. (Incidentally, you can get all of the answer at once by writing findall(X, (key(Key), score($answer-array, Key, X)), L).) I still don't like puzzles for teaching The actual examples I'm using in the book are "analyzing a version control commit graph" and "planning a sequence of infrastructure changes", which are somewhat more likely to occur at work than needing to solve a puzzle. You'll see them in the next release! I found it because he wrote Gamer Games for Lite Gamers as a response to my Gamer Games for Non-Gamers. ↩ These are better versions of the core Prolog expressions \+ (A = B) and A is B + 1, because they can defer unification. ↩ Prolog-descendants have a convention of writing the arity of the function after its name, so score/3 means "score has three parameters". I think they do this because you can overload predicates with multiple different arities. Also Joe Armstrong used Prolog for prototyping, so Erlang and Elixir follow the same convention. ↩ It still gets the right answers without this type restriction, but I had no idea it did until I checked for myself. Probably better not to rely on this! ↩ We could make this even more compact by using a lambda function. First import module yall, then write maplist([X]>>member(X, [a,b]), Key). But (1) it's not a shorter program because you replace the extra definition with an extra module import, and (2) yall is SWI-Prolog specific and not an ISO-standard prolog module. Using contains is more portable. ↩

7 hours ago 2 votes
Market Ending Moves

Startup CEOs should ask themselves what crazy ideas can turn into a move that just ends a market's competitive dynamic

7 hours ago 2 votes
Why we won't hire a junior with five years of experience

We just opened a search for a new junior programmer at 37signals. It's been years since we last hired a junior, but the real reason the listing is turning heads is because we're open about the yearly salary: $145,849*. That's high enough that programmers with lots of experience are asking whether they could apply, even if they aren't technically "junior". The answer is no. The reason we're willing to pay a junior more than most is because we're looking for a junior who's better than most. Not better in "what do they already know", but in "how far could they go". We're hiring for peak promise — and such promise only remains until it's revealed. Maybe it sounds a little harsh, but a programmer who's been working professionally for five years has likely already revealed their potential. What you're going to get is roughly what you see. That doesn't mean that people can't get better after that, but it means that the trajectory by which they improve has already been plotted. Whereas a programmer who's either straight out of school or fresh off their first internship or short-stint job is essentially all potential. So you draw their line on the basis of just a few early dots, but the line can be steep. It's not that different from something like the NFL scouting combine. Teams fight to find the promise of The Next All-Star. These rookies won't have the experience that someone who's already played in the league for years would have, but they have the potential to be the best. Someone who's already played for several seasons will have shown what they have and be weighed accordingly. This is not easy to do! Plenty of rookies, in sports and programming, may show some early potential, then fail to elevate their game to where the buyer is betting it could be. But that's the chance you take to land someone extraordinary. So if you know a junior programmer with less than three years of industry experience who is sparkling with potential, do let them know of our listing. And if you know someone awesome who's already a senior programmer, we also have an opening for them. *It's a funnily precise number because it's pulled directly from the Radford salary database, which we query for the top 10% of San Francisco salaries for junior programmers.

16 hours ago 2 votes
A Data Engineering Perspective of LLMs

Data engineering is a field I would categorize as a subspecialty of software engineering. It shares the same concerns as software engineering—scalability, maintainability, and other “-ilities”—but its primary focus is on data. It’s a unique discipline because data is inherently messy, and as a result, no standard enterprise framework has emerged to dominate the space—and […]

2 hours ago 1 votes