22 January 2018

错过的时间怎么买

Been re-listening to all my Jay Chou songs these couple of days. Was reminded by manga (so happy that I retain enough chinese to understand the raws) and a conversation with friends about the celebrities that we found good looking. I've also finally listened to his new album, which isn't much to my taste except this song (it sounds like a soundtrack song because it is):


男:假装我们还在一块 我真的演不出来
        还是不习惯你不在 这身份转变太快

女:画面里不需要旁白 却谁都看的出来
        是我情绪涌了上来 想哭却一遍空白
男:雪地里相爱 他们说零下已结晶的誓言不会坏
合:但爱的状态 却不会永远都冰封 而透明的存在
        轻轻飘落下来 许下的梦融化的太快 或许我们都不该醒来
女:你还是住在我的回忆里不出来
男:让我们微笑离开让故事留下来
合:放手后爱依然在 雪融了就应该花开
        缘若尽了就不该再重来
女:你依旧住在我的回忆里不出来
男:我离开将你的手交给下个最爱
合:纠缠与固执等待 反而是另一种伤害
        彼此紧握的手松开 去拥抱更多未来
男:错过的时间怎么买 谁都付 不出来
女:或许我们学会释怀 让过去安静下来

合:雪地里相爱 他们说零下已结晶的誓言不会坏
        但爱的状态 却不会永远都冰封 而透明的存在
        轻轻飘落下来 许下的梦融化的太快 或许我们都不该醒来
女:你还是 住在我的回忆里不出来
男:让我们微笑离开让故事留下来
合:放手后爱依然在 雪融了就应该花开
        缘若尽了就不该再重来
女:你依旧住在我的回忆里不出来
男:我离开将你的手交给下个最爱
合:纠缠与固执等待 反而是 另一种伤害
       彼此紧握的手松开 去拥抱更多未来

It's so hard picking a favourite line for the post title, the runner up is "让过去安静下来" but also all the lines where they both sing. 

Now excuse me while I go watch Now You See Me, which I just found out stars Jay Chou. And that there's a sequel, featuring his song! 

21 January 2018

pecan

Milk braised sweet potato with chickpea version of texas caviar 

Browned (maillard reaction) dairy is yummy, I'd very much like to try toasted cream. Will also try the same recipe with potatoes and thyme instead, and also with single cream instead of milk for more yummy milk solids.

18 January 2018

ABDC

Hurray new cookbooks!

In other, very extremely, sad news, batoto is closing down. It was many glorious years of reading manga on there, thanks for having been there. I'd be panicking more if not for:

  • I follow a lot of webcomics on Line
  • Already bookmarked several escalation groups
  • It's probably a good opportunity to downsize my manga consumption
:(

...

I caught up to all the translated chapters of Knight Run, which is not that many considering the main episodes start from now on (?!), and this is the high praise that I shall give: it's a cross between Ares in how it depicts war (oh it's been so many years) and The Brothers Karamazov in how it depicts humanity. While browsing my archives to find the links, I came across my post on Yongbi and thought what I wrote there applies to KR too.
It rounds out ToG and CiTT as my favourite webcomics. It's similar to CiTT in how much foreshadowing and clues there are in each chapter. It's literally the only webcomic that I've read with its wiki page open in the adjacent tab, searching as I go. 

17 January 2018

press

Decided to cook something more involved than soup to get over a slump:

masala eggs wrapped in flatbread with shredded cabbage

It was delicious, I wish I had the stomach room to eat another one.

The eggs will definitely be a staple, along with green onion fried eggs and tomatoes and eggs. It takes a bit longer than the Chinese eggs since I'm super slow at cutting vegetables into neat little dices. The bread tasted sweet despite not having any sugar in the recipe, which I credit to the fancy jersey milk that I used. It's insane how a bottle of that is 70p whereas a comparable bottle of whole milk (not sure what type of cow) in Toronto is $4. I was apprehensive at the bread's success since I only have volume measurements, and I did have to add a lot more flour than the recipe stated to arrive at a not too sticky dough, but in the end breads are pretty forgiving. I found that putting a lid on the pan to trap some steam produced a better texture.

And I do feel better after dedicating the morning to cooking. Also made poached pears with cinnamon (flavour pairing discovered via The Flavour Thesaurus) which was delicious as well. I'm so on board with fruit soups after my friend highly recommended cooking apples in the winter to avoid eating cold fruits.

16 January 2018

The Signal and the Noise

First book read of 2018! Blocking out half to an hour before sleeping to read has been working well.

David recommended this book to me as an introduction to Bayesian thinking / probability. More generally, Bayesian thinking helps to correct, or at least bring into awareness, many cognitive biases and therefore help us be less wrong. I found the book to have clear explanations and quite entertaining. It was interesting to me that the author felt the need to explain the rules of poker but not baseball or political polling, the reverse would've been helpful to me personally. I do really like how the book is printed on super smooth (but not glossy!) paper.

The introduction basically outlines the pitfalls:
The instinctual shortcut that we take when we have "too much information" is to engage with it selectively, picking out the parts we like and ignoring the remainder, making allies with those who have made the same choices and enemies of the rest. 
The story the data tells us is often the one we'd like to hear, and we usually make sure that it has a happy ending. 
We face danger whenever information growth outpaces our understanding of how to process it. 
Prediction is important because it connects subjective and objective reality.
Once you learn a new idea, you start seeing it everywhere, much like when you learn a new word, you start hearing it in every conversation. I recently started listening to the Secular Buddhism podcast, and in episode 2 (or was it 3?) it tells the story of 6 blind men describing an elephant, which is the same idea as "the forecaster's next commitment is to realize that she perceives [the objective truth] imperfectly". 

Part 1 describes how predictions about the 2008 financial crisis fail because it used out-of-sample data and defines the difference between uncertainty (not quantifiable) and risk (quantifiable).  "When you can't state your innocence, proclaim your ignorance: this is often the first line of defence when there is a failed forecast." reminds me the concept of due diligence in the engineering profession, whose purpose is exactly to safeguard against proclamations of ignorance. 

Part 2 describes the difference between foxes and hedgehogs, which represent two different personality types. Hedgehogs tend to let strong ideology cloud their judgement. 

Part 3 describes the litmus test of good predictions: that the accuracy should improve with additional data. "The key to making a good forecast [is] having a good process for weighing [both qualitative and quantitative] information appropriately".

Part 4 is the rare success story of weather forecasting, where computational models are amended with human judgement. The easy part is that we know a good amount of atmospheric science so the models are based on sound theory, the hard part is that weather systems are chaotic (non-linear and dynamic). 

Part 5 describes how in contrast, earthquakes forecasting haven't been so successful. Some failures are because the models are overfitted, meaning that too specific of a solution has been found for a general problem. Earthquakes are also complex (simple elements but complex interaction, I know I just used a word to define itself). 

Part 6 brings up the famous quotation of "correlation doesn't imply causation", and says that:
To not confused correlation for causation, one need to have a theory of what the cause is

Technology did not cover for the lack of theoretical understanding about the economy; it only gave economists faster and more elaborate ways mistake Noise for a signal.

The amount of confidence someone expresses in a prediction is not a good indicator of its accuracy.
Part 7 describes how human behaviour messes everything up even more:
In many cases involving prediction about human activity, the vey act of prediction can alter the way that people behave. Sometimes, as in economics, these changes in behaviour can affect the outcome of the prediction itself, either nullifying it or making it more accurate. Predictions about the flu and other infectious diseases are affect by both sides of this problem.
Pretty much every course I've taken has made a joke of if only we can get rid of the pesky occupants.

Part 8 formally introduces Bayesian probability and bashes a great deal on the stats that's most commonly taught. I don't feel as bad that I forgot most of what I've learned.
We learn about [the universe] through approximation, getting closer and closer to the truth as we gather more evidence. [...] The Bayesian viewpoint regards rationality as a probabilistic matter.

The frequentist approach towards statistics seeks to wash its hands of the reason that predictions most often go wrong: human error. It views uncertainty as something intrinsic to the experiment rather than something intrinsic to our ability to understand the real world.
It emphasizes the objective purity of the experiment - every hypothesis could be tested to a perfect conclusion if only enough data were collected. However, in order to achieve that purity, it denies the need for Bayesian priors or any other sort of messy real-world context. These methods neither require or encourage us to think about the plausibility of our hypothesis
Part 9 describes chess as an example of a deterministic problem that is not within our (or even a supercomputer's) practical capabilities to fully solve. Instead we employ heuristics (rules of thumb).

Part 10 gives a step by step example of Bayesian probability applied to poker.

Part 11 describes that unfortunately more accessible information cancels out the wisdom of the crowds as we adopt a herd mentality. Our decisions becoming dependant, which creates a positive feedback loop for mistakes instead of vice versa.

Part 12 is even more depressing as it describes the politicization of science and the difficulty of communicating uncertainty (it was already bad enough learning about it in ENV221).

Part 13 describes "our propensity to mistake the unfamiliar for the improbable" using terrorist attacks as a case study.

...

I'm not sure how well I'll actually apply the lessons learned to my life. Perhaps I'll at least analyze data for my courses/thesis better?

15 January 2018

foam

I finally started on making some pancakes! The delay is mostly because I was too lazy to pick up baking soda and baking powder whenever I'm at the grocery store, for some reason baking ingredients are on the opposite end of the store as produce.

But alas, Smitten Kitchen's sour cream pancakes:

I think they turned out well, considering that I haven't made pancakes for at least 3 years. But the credit goes to the clearly written recipe with both time estimate and visual cues. I was nervous while mixing the batter as it looked like way too much sour cream, and the mixture did not look like it wanted to come together with the beaten eggs; it'd be nice if Deb included photos of the batter (instead of the eggs in a bowl).

However, I don't think I'm a fan of this particular recipe. The pancakes turn out very...custard-y? Although to be honest I'm not sure what type of pancakes I prefer. Well that's why I have many other recipes to work through, including buckwheat crepes since I did find buckwheat four in my grocery store, it had pretty packaging to boost.

...

Also made texas caviar, which is really just a bean salad:

"just" a bean salad is doing this dis-service, it's a very tasty bean salad. This will definitely be in my lunch rotation once the weather warms up.

I'll admit my hubris in not wanting to use canned beans because I think I should be able to cook dried beans to textural perfection (ha...at least I can partially blame the dubious quality of grocery store beans). But my grocery store do not actually have dried black eye peas. In the end, it turns out to be good luck that I used canned beans because chalky beans would've made this horrendous.

14 January 2018

silence

Ming Thein's article on creative integrity is the exact message I want to convey whenever someone suggests to me about turning a hobby into a profession.

Don't wanna open a tea shop
Don't wanna be a food blogger

...except potentially opening a noodle bar.