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I found inspiration for this pitcher's glaze design in the night sky. Whenever I feel lost, I know I can always look up and be under the same night sky, no matter where I am. Whenever I feel alone, I know I can always look up and feel connected to humanity, everyone else looking up at the same sky. Whenever I feel all is lost, the vast darkness in the night sky reminds me there are so many possibilities out there that I haven't even thought of yet. My studio practice is on a partial pause for an unknown amount of time right now; every piece I make is stuck in the greenware stage as I continue to save up to buy kilns and build out the glaze and kiln area. In some moments, this pause feels like a rare opportunity to take time to make more experimental and labor intensive pieces, but in other moments, I am overwhelmed by the feeling that pieces without a completion timeline on the horizon are just not worth doing. It's easy to bask in fleeting bursts of inspiration; it's harder to push through the periods where nothing feels worth doing. It's especially when the waves of anxiety about the unknown future of my studio practice and the waves of anxiety about the direction of the US government and the future of my country come at me at the same time. I try to ground myself, to keep myself from spiraling. I name things I can see, smell, hear. At night, I look to the dark sky. When I can, I reread Rebecca Solnit's Hope in the Dark: Hope locates itself in the premises that we don't know what will happen and that in the spaciousness of uncertainty is room to act. When you recognize uncertainty, you recognize that you may be able to influence the outcomes–you alone or you in concert with a few dozen or several million others. Hope is an embrace of the unknown and the unknowable, an alternative to the certainty of both optimists and pessimists. Optimists think it will all be fine without our involvement; pessimists take the opposite position; both excuse themselves from acting. It's the belief that what we do matters even though how and when it may matter, who and what it may impact, are not things we can know beforehand. We may not, in fact, know them afterward either, but they matter all the same, and history is full of people whose influence was most powerful after they were gone. May we all find hope in the dark and choose to act.
When I was glazing this v60-style cone, I was thinking of rising sea levels, eroding beaches, and melting ice caps. Trying to tackle large challenges like climate change is overwhelming in the best of times, and these are not the best of times. There are many things we can personally do to reduce our carbon footprints and fight climate change, but If we want to have any chance to succeed, we need to join together and organize. If you're new to organizing, connect with local groups already doing the work you're interested in, and don't forget to look for groups pushing for change outside of just the national stage. Creating more dense walkable, transit-oriented communities is one of our strongest tools for a sustainable, climate friendly future. Generally, the bulk this work in the US happens at the state and local levels. In addition to the climate benefits, it's essential work to keep communities together and fight displacement. I personally spend a lot of my spare time organizing locally around this issue to help ensure NYC and New York State stay places everyone can thrive. I focus especially on pro-housing policies and improving transportation options and reliability so climate-friendly, less car-dependent lifestyles - and New York's relative safety - can be for everyone.
Clay shrinks as it dries and even more as it's fired, so it's useful to have a way to estimate the final size of in-progress work - especially if you're making multiples or trying to fit pieces together. One way to do this is with shrinkage rulers. I figured I'd design my own shrinkage rulers and provide a way for folks to make them themselves since ceramic tool costs can add up. To make your shrinkage rulers: Download either the colorful printable shrinkage rulers or black and white printable shrinkage rulers. Print at 100% size. (These files are both 400 dpi.) Verify that the 0% shrinkage standard ruler at the top matches the size of an existing regular ruler you have. This quick calibration step will make sure nothing out of scale during printing! Cut out your rulers. Optionally, laminate or cover in packing tape to help them last longer. To use your shrinkage rulers: If you're using commercial clay, look up how much your clay is estimated to shrink. If you're using a blend of clays or custom clays, you'll have to calculate how much your clay shrinks. An easy way to do this is measure the length of a wet piece right after you form them and again after it's been through its glaze firing. You can then calculate the estimated shrinkage rate: Pick the shrinkage ruler that corresponds to your clay's shrinkage rate. If you're between shrinkage rates, you can estimate with a nearby size. Remember that shrinkage rates are estimates, and a piece's actual shrinkage depends on many variables, including how wet your clay is and how close it is to it's original composition (this can change with repeated recycling). Measure your wet piece with the shrinkage ruler! The length shown is the expected length your piece's dimension will be when fired. The fine print: Reminder that shrinkage rulers only give estimated lengths! You're welcome to print these shrinkage rulers for yourself or your business. You may use the printed shrinkage rulers privately, even in commercial applications (I hope they help your ceramic art and business!), provided you do not redistribute or resell the shrinkage rulers themselves in any form, digital or physical. Footnotes If you're working on a jar or something else that needs to fit together tightly, it's better not to rely on shrinkage rulers to get a perfect fit. In my experiences, you ideally want to make the vessel and the lid as close in time as possible and have them dry together and fire together through as many phases as possible.↩
I'm continuing my clay body reviews series with two very heavily grogged "sculpture" clays I've used. Note that I currently practice in a community studio that glaze fires to cone 6 in oxidation, so my observations reflect that. Standard 420 Sculpture: Cone 6: average shrinkage 8.0%, absorption 1.5% Light straw when fired to cone 6: more yellow/beige than most white stonewares so the color is something to consider in your final vision (or engobe in something else) So much grog that it’s best described as working with wet sand, non-derogatory I've made complicated open coil-based structures with this clay that have been formed across many studio sessions over a couple days, and they've survived without cracking! Wet clay attaches readily to leather hard and even slightly dry clay. Wrapping my works in dry cleaning bags until done and dry before bisque was enough - I was worried I'd have to make a damp box, but not with this clay! The grog is white and grey, and it comes in a variety of sizes, including some that is visually rather large. The grog really shows if you sand to smooth the surface. I typically dislike how this looks - the result ends up looking more like concrete than clay. If you use this for functional ware or anything you move around a lot, you'll certainly want to sand the bottom since the groggy surface is extra rough to protect tables and counters. Burnishing alone doesn't usually make this clay smooth. Can be thrown when very soft, but your hands will feel scratched if you're not used to it! Angled slab joins join readily, and support coils press in quickly and easily. Some members of my studio prefer to make plates with this clay because the high level of grog significantly reduces warping. I personally prefer to make plates with clays with far less grog that I dry very slowly. High palpable grog content means a weaker object, and I prefer more strength in objects that are handled frequently. Can be marbled with 798, but needs to dry slowly. Standard 420's straw color shows in the unglazed section of this planter's drip tray, and there's also some flashing from the glaze near the edges. I sanded the base of this piece so the slightly rough surface of Standard 420 wouldn't scratch tables, and you can see the contrast between the sanded bottom (outside) layer where the varied grogs are revealed and the rougher surfaces of the other layers where they are still covered by clay particles. This handbuilt planter was made of Standard 798 over multiple studio sessions. The sculptural coil structures attached readily with my regular slip and score process, and it dried evenly enough to not crack with my regular process of drying under a single plastic dry-cleaning bag. This coiled wall art piece was made out of equal parts Standard 112 and Standard 420 wedged fully together. There's still ample grog in this hybrid clay body to work the same as the Standard 798 planter's coiled structure. Standard 798 Black Sculpture: Cone 6: average shrinkage 10%, absorption 1.0% Dark brown when wet, fires to a gorgeous black at cone 6 when unglazed. Clear glazes will make this clay look brown, so you need to use a black like Coyote Black or Amaco Obsidian to preserve the black color if you want to glaze it. So much grog that it’s best described as working with wet sand, non-derogatory. The grog is white, and provides a lovely contrast when on the surface or sanded to be revealed. Like 420, you'll probably want to sand the bottom of anything you'll pick up and put down more than once. Very similar working qualities to 420 - a true joy for handbuilding! Can be marbled with 420, but needs to dry slowly.
More in programming
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.
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. ↩
Startup CEOs should ask themselves what crazy ideas can turn into a move that just ends a market's competitive dynamic
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.
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 […]
