Fay Weldon on Jane Austen, writing, reading, and life. (Letters to Alice, 1985)

     Fay Weldon. Letters to Alice on first reading Jane Austen (1985). An epistolary novel, in which Weldon gives advice about reading, writing, and life, and expatiates on how they intertwine and react on each other.
     Alice is at university, doesn’t like Pride and Prejudice, and is writing a novel. Will she take Aunt Fay’s advice? Will Aunt Fay mend her relationship with her sister and brother-in-law? Will Alice finish her novel? Read the book and find out. It’s worth reading for many reasons, chief of which is Aunt Fay, whose company and opinions are exhilarating. Is she a version of Fay Weldon? Probably, but as Aunt Fay says, there is the truth of real life and the truth of fiction. Recommended, worth searching for. ****

Kinsey finds more family: W is for Wasted

     Sue Grafton. W is for Wasted (2013). Two apparently unrelated deaths, one a murder, eventually tie up each other’s loose ends. Kinsey’s investigations garner her some relatives on her father’s side. Homeless people are a problem. Kinsey’s love life stutters, maybe in the next book (the last one Grafton wrote) there’ll be some kind of resolution.
     So the backstories move along a few steps, Kinsey discovers she likes cats afer all. Grafton has to use 3rd person interludes to move one of the plots along, and the reader knows all the guilt and innocence before Kinsey does. A long novel, more of a character study than a mystery. The plot focusses on how Kinsey discovers what the reader already knows. Grafton’s interest has shifted from solving crimes to understanding them and their effects. ***

Money and Nature: Lapham's Quarterly I-2 & I-3

 

    Lewis Lapham, ed. Lapham’s Quarterly: Vol.1:2 “About Money” & Vol.1:3 “Book of Nature” (2008) The excerpts about money are in roughly historical order. They form a summary of the developing understanding of money, as well as a sometimes entertaining account of what can go wrong when people mistake money for wealth. Money is either the elixir of life or the worst invention of humankind.
     The earliest ideas ascribed intrinsic value to money: a gold coin had some objective value simply because it was gold. That idea began to unravel when the Spaniards brought tons of the stuff from South America and promptly triggered almost ruinous inflation. The latest ideas about money emphasise that it’s information: Almost all money these days exists as electronic data about some account balance. Money is a system of abstract IOUs. Instead of an IOU for, say, 10 bushels of wheat, we have an IOU for, say, $50. That $50 could be used to buy 10 bushels of wheat Or 8 measures of oil. Or a cask or two of wine. Or whatever.
     There are several accounts of bubbles, eg, the Dutch tulip mania of the 1600s. Ponzi schemes and other frauds also appear. These debacles occur because people want money. They see the bubbling trade in tulips as a means of amassing money. They see the fraudster’s con as a means of amassing money. Since both bubbles and frauds depend on credit for their initial success, they debase the value of money: they are one of the drivers of inflation.
  

There’s more, but I won’t enlarge further. See my other posts aboiut money for further
comments.
     Lapham claims he doesn’t understand the concept of  “The Book of Nature”. This collection belies the claim. It records the full range of human responses to the natural world, from denial that we are part of it (we “have dominion” over it, after all) to acceptance that we wholly depend on it (but on current evidence are destroying it). These two responses are present in the earliest myths. For example, Genesis records that God made Adam from the dust of the ground. That make humans part of the natural order. It also records that God gave humankind dominion over the every living thing. That puts humans above and outside the natural order. Or so the standard interpretation goes. More recent theology argues that “dominion” means stewardship. We rule the Earth on behalf of the Creator.
     Lapham’s quarterly collections add up to a history of the ideas that govern our choices. They show that our ancestors expressed every current notion about how the world works and how we should live. ****

Perception: Colours

Fragment of a conversation in a newsgroup. The book did not figure inthe conversation. I think it supports my stance that colour is in the brain.

[A]
  I was once asked "How many colors are there?". A difficult question,   which many people can't answer, they've confused "how many colors" with   "how many WORDS for colors". 2^24 (16,777,216) is a better answer than that.

[B]
 I agree with 2^24, that seems to be as much as the eye can distinguish.

[C]
 Which doesn't mean that reality is so limited. Note that some animals see better than humans, which isn't relevant either.

[Me]
There's a difference between colours as measured by a spectrometer and colours as perceived by a human. Eg, there is no such colour as "brown" in the spectrum. Or "pink". Or "grey". Or etc.

The 2^24 number of colours is the combinations of colour data used to display colours on a screen. Whether there are actually that many colours displayable on a given screen is another issue: screens vary quite a bit in quality, though much less nowadays than they did in the Olden Days. And whether a human can distinguish them all is another issue. And whether they can replicate natural colours in all weathers is another issue again. As anyone who's tried to make a photo "look right" knows.

As for "see better", that's not a clear concept either.

When it comes to perception, the only thing we can objectively measure or observe is what colour (or other sensory) differences the animal can distinguish. While it's true that bees can distinguish ultraviolet wavelengths, that doesn't mean they "see better". They see well enough for their survival, and that's what counts.

Or take frogs. Judging by their behaviour, they can't see fly-sized blobs unless those blobs move. I surmise that's similar to human peripheral vision, which is much better at distinguishing moving blobs of light than still ones.

Bottom line: what's "out there" isn't what we think it is.

The cost of idling the car

From
http://oee.nrcan.gc.ca/transportation/idling/wastes.cfm?attr=8

"... In fact, one of the most powerful arguments in favour of reduced idling is an economic one.
For the average vehicle with a 3-litre engine, every 10 minutes of idling costs 300 millilitres
(over 1 cup) in wasted fuel – and one half of a litre (over 2 cups) if your vehicle has a 5-litre
engine. Unnecessary idling wastes fuel – and wasted fuel is wasted money...."

My Mitsubishi Outlander has a 3l V6 engine which requires high-octane fuel. So at 1.60/litre (more or less), 10 minutes of idling costs about 50 cents, or approximately a nickel a minute.

Or $3.00 per hour.

H'mm.

Footnote: On hot days, at our local mall parking lot, I often see people sitting in their cars with the windows rolled up, the engine and air-conditioing running. Even on days when a nice breeze blowing through open windows would keep the car cool. I think this indicates that fuel s too cheap.

Grafton: V is for Vengeance. Shoplifting and murder.

     Sue Grafton.  V is for Vengeance (2011) Kinsey spots a shoplifter, turns her in. The perp’s confederate almost runs down Kinsey in the parking garage. From there the plots gets complicated, what with an organised shop-lifting business, a dysfunctional crime family, bent cops, and damaged people. Justice, of a sort, is done, and some perps will face a judge. As usual, Kinsey faces death and incurs injuries, but there’s less gore than usual.
     Grafton’s plot requires several chapters of 3rd person narration. She handles these well. I get the impression she feels more than a little constrained by Kinsey’s 1st person POV. The book is bigger than most of Grafton’s work, but it still feels unfinished. Grafton has always leaned towards a combination of social comedy and romance. The crime plots are just a rack to hang the clothes on.
     A pretty good read, but this time around I didn’t feel compelled to keep on reading, and there were stretches of a few days when I didn’t pick up the book. **½

Artificial Intelligence (AI): A series of notes

2005-06-20
“If it looks like a duck, and walks like a duck, and quacks like a duck, then it’s a duck” (Ancient wisdom)

Unless it’s a model of a duck.

Artificial Intelligence is model building – we want autonomous machines, but the best we can do is build models of autonomous machines.

Eg, an artificial ant could be made to behave like an ant in many ways, but not as an ant in an anthill, or capable of making more ants.

2015-10-21
It’s probably possible to make an artificial ant that behaves like an ant in anthill. We may even be able to make an artificial ant that can reproduce in some way.

However, “behave like an ant” is not well defined. There are too many behaviours, and some are obviously easier to mimic than others. Nevertheless, it will soon be possible to make an ant-size robot that can navigate like an ant, climb vertical surfaces like an ant, etc.

But it will always be a model of ant, and therefore its behaviour will in some respect will not be antlike, and in other respects will be a bad imitation of ant behaviour. That’s simply the nature of models. Models are mixtures of emulation and imitation.

2016-05-15
Intelligence is even less well-defined than “ant behaviour”. We can mimic some intelligent behaviours, eg, sorting, learning correlations, recognising patterns, and so on, which are useful to augment human tasks such as diagnosis of a fault or illness, or finding the data we want. If a task is well enough defined, we can build a machine to do it.

But that’s the problem: “Intelligence” is simply not well enough defined. My notion of it is the ability to apply and adapt existing knowledge and insight to unanticipated problems. Every term in that definition is fuzzy and vague. Anyhow, some people (including me) would argue it’s more of a definition of creativity than intelligence.

Is consciousness part of  “intelligence”? Many people would say it is. A machine that merely solves problems isn’t intelligent, it’s just an algorithm. It’s not enough to know how to do long division, you have to be able to recognise when and why you should do it. An intelligent entity then would be able to apply the rules of the algorithm to another problem. This claim entails that intelligence can abstract rules and patterns, and recognise them in different contexts.

“Understanding” is another component of intelligence. Isn’t it? Well, it does have something to do with learning: an intelligent person is one who can make sense of new explanations. “I don’t get it” at one extreme means “I haven’t figured it out yet”, at the other it means “I can’t figure it out”. The latter is a measure of intelligence.

And that’s just three attempts to make sense of “intelligence”. We’re long way from knowing exactly what we mean by “artificial intelligence”. Far enough that we may not even recognise it when we see it.

The recent development of “deep learning” artificially intelligent neural nets crystallises the problem. It’s already clear that we can evaluate the results of their operations, but we can’t figure out how they do it. What’s more, they have come up with solutions that humans have not only not produced, but have trouble recognising as viable solutions. For example, some AIs are better then humans at recognising cancerous tissue.

2018-07-03
If we accept “intelligence” as a label for problem-solving abilities, then consciousness is not required. That makes the neural-net AIs more than a little spooky.