07 May, 2010

The General Election, and 2006 Longyuanhao

The English, Scottish, Welsh, and Northern Irish are currently in the process of deciding their next Government.  The last four weeks have been the usual period of hectic, insincere pledges and mishaps from the various political parties.  Perhaps we should be thankful for small mercies - it took less than the 1+ years of the last Governmental election in the USA.


2006 Longyuanhao Yiwu
The correct answer, of course, being "anyone but Golden Brown"

As I sit at my desk, my other screen has a BBC web-page updating itself as new results come in, following the voting of yesterday.  It was Lei's first General Election, and she took great delight at exercising her right as an Englishwoman (!) to cast her vote.

Our system is such that we vote for whom we would like to represent us as a Member of Parliament (MP).  The party with the most MPs wins, and (usually) gets to form the next government.  This time, it's more complex, as no party has over 50% of the MPs, and so we might have to be frightfully European.  The English don't do consensus very well, and I can't see Belgian Eurocratic politics ever catching on here.

Our local choice was one of three classic party stereotypes: 
  1. the overweight, insincere Conservative candidate (traditional party of the privileged), who doesn't even live in Oxford (he lives in Westminster);
  2. the red-faced, sweaty, oiky Labour candidate (traditional party of the underprivileged); and
  3. the skinny, bearded, loose-fitting-suit-wearing Liberal Democrat candidate (traditional party of the terminally spineless). 
You couldn't have made it up.

So, I decided to shed some tears over my tong of 2006 Longyuanhao "Yiwu Xiangbing".   Unfortunately, it doesn't actually taste very nice, and so exacerbated my woes. 

Extra notes/tears may be found here (scroll down).


2006 Longyuanhao Yiwu
Capturing the mood, this tea sucks.

03 May, 2010

2009 Xizihao "Jingmai"

My day-job is in the area of getting computers to learn.  This could mean classifying human hospital patients as being "at risk" or "healthy" using histories of their vital signs, or perhaps classifying jet engines as being "OK" or "in danger of exploding" using data from engine-mounted sensors, or perhaps classifying masses in mammograms as being either "cancerous" or "not cancerous" using x-ray images.  The field is called "machine learning" - we gave up the name "artificial intelligence" about 15 years ago, as we're not really trying to construct intelligence, but systems that can classify and predict based on data.

The general idea is that you make observations using sensors, and then use those observations to classify the item you've sensed, or to predict its future behaviour based on its history.  Some people like to use their powers for the forces of darkness (financial prediction), while I choose to use mine for the forces of good (medicine). 

Fear is the path to the dark side. 
Fear leads to anger. 
Anger leads to hate. 
Hate leads to suffering.



2009 Xizihao Daxueshan
Yes, it's more Xizihao from Houde.  Some things never change!

Suppose we were to construct a system that could classify pu'er, based on some "sensory data": flavours, scents, textures, etc.  Some progress has been made with sensors that can approximate tastebuds, but the human nose is proving more difficult.  There is an example of this type of machine in the wine world, where a researcher trained an "artificial sommelier" to classify wine types based on chemical data obtained from a prototype of such a sensor.  Given data, we can use statistical methods to classify new examples - that is, we can classify.

What we, as tea drinkers, are up to behind all the drinking, is a similar classification task.  We acquire data by drinking lots of tea, and each tasting becomes an example in our internal  knowledge base.  Sometimes, we have the "labels" corresponding to the data ("this was tieguanyin"), so we can begin to learn what pu'er tastes like, and what wulong tastes like.  We might acquire more data, such that we can distinguish subclasses within one of those classes: we might be able to tell shupu from shengpu, within the "pu'er" class, for example. 

One level further, we start to form finer-grain classifications.  As we acquire data, we can tell young cakes, from middle-aged cakes, from mature cakes.  Given enough data, we can begin to discern old-tree from plantation, or overcooked "drink it now" tea from clean, aggressive tea more suitable for storage.

As we accumulate more data, we can begin to discern regional differences.  Chances are that most of us are around about this stage, give or take.


2009 Xizihao Daxueshan
This Jingmai has pleasant enough leaves - Xizihao always looks good


Discerning regions is easiest when the data are clearly distinguishable.  Tea from the outer regions of Yunnan is among these, I think.  Lincang is quite easy to tell apart from, say, traditional Xishuangbanna teas.  Drink enough, obtain enough data, and the classification begins to take care of itself.

Jingmai is another example of a tea that stands out in a cluster on its own.  There's very little benefit in me attempting to list those features that I ascribe to Jingmai, as they have to be learned and assimilated personally.  However, for what it's worth, I notice a nutty, savoury character common to most cakes labelled "Jingmai" that I have come across, perhaps also containing an almost sour, citrus-like ending.


2009 Xizihao Daxueshan
Some honest leaves if ever I saw them

This Jingmai from Xizihao is more of the same.  I appreciate its bright yellow colour - alongside its bold kuwei [bitter finish], it hasn't been "dumbed down".  It has a tangy, sour citrus-like ending, and tastes rather like a young version of an old tea.  Consequently, it's tempting to extrapolate and imagine how this might turn out in five years.

I found some roughness in this tea, which started out with the almost ragged citric finish, and became a cheek-abrading (yet somehow very nice) brew near the end.  It lasted well, nonetheless.

At half the price (this was $100 / 400g from Houde), this may have begun to tempt me.  As it is, my hard-earned currency is destined to be spent elsewhere, I suspect.

Give us a few years, and we'll have a decent nose-and-throat sensor sorted out...

02 May, 2010

Every Branch

Xiaobu


every branch
on the Li River mountains
holds my gaze