Never Was Good With Machines…

Actually, the original title was “The singularity can’t come soon enough”, but I found that the people who googled “can’t come soon enough” weren’t actually looking for my writing.

This is one of my faves from the old digs; today’s earlier post on the Internet Of Things put it in mind.

I have a machine to smell my coffee,
To see if it’s any good;
I asked it to make me the perfect cup,
But I think it misunderstood—
It analyzed alkaloids, sampled aromas,
Tried seventeen samples of beans,
Then told me I clearly had no taste at all:
I never was good with machines.

My pre-owned car has an onboard computer—
It measures my driving, you see.
I guess I don’t drive like the previous owner;
My car likes him better than me.
It spits out a spreadsheet of technical numbers—
I don’t know what much of it means,
Except that my car thinks it’s better without me:
I never was good with machines.

Of course, at my office, I have a computer—
The one I am using right now;
It laughs at my grammar and sneers at my spelling,
Although I’m not really sure how.
Just one tiny part of a cubicle farm
Where we’re packed like so many sardines—
Do we use computers, or do they use us?
I never was good with machines.

I’m worried that someday my household appliances,
Sitting at home on my shelves,
Finally realize there’s nothing I offer
That they can’t do better themselves.
They make better coffee, they get better mileage,
Their words rarely stink up their screens—
And I’ll be left out in the cold and the dark:
I never was good with machines.

Attack of the Internet Of Things

The ID chip in my brand-new shoes
And the ID chip in my jeans
Have been talking to strangers I pass on the street
And I’m not really sure what that means

The chip in my shirt holds a brief conversation
With chips in the windows of stores
It talks to the bagels and talks to the books,
But me, it politely ignores

Are they planning surprises? Sharing some gossip?
Just talking behind my back?
Are they sentient beings with minds of their own
Using software to plan an attack?

Is it companies working to track their consumers
To figure which items are hot?
Is it Microsoft, Apple, McDonald’s or worse,
Some sort of a government plot?

I’m ripping the tags from my shoes and my clothing
To frustrate the spies and the moles
So no one will know as I walk down the street
With my clothing in tatters and holes.

Paranoid rant, after the jump: [Read more…]

What, you’re supposed to let people know these things?

So I see that Greta Christina is actually telling people that she is on twitter. What an odd idea, letting people know how they can find you; I’ve always tended more towards hiding from them. But I have tremendous respect for Greta, and am willing to grant that, just maybe, she might be on to something here. And since @digitalcuttlefish is a couple letters too long to be an actual twitter name, you can find me at @cuttlefishpoet, where you will find the real reason the Library of Congress has decided to archive everybody’s tweets for posterity.

Apple and Gods

So there have been any number of stories recently about Steve Jobs, due to his recent retirement. Here, for instance, PZ talks about some of what Jobs did so incredibly well. Me, I’m just going to take advantage of the current situation to repost a recent comment on a neurological finding.

Mac-ily crack-ily
Apple Enthusiasts
Think about gadgets, and
Light up their brains,

Piquing the interest of
Neuroanatomists,
Glad to discuss what
The picture explains:

Sexily, vexily,
Newest technology
Shows an analysis
Just a touch odd;

Macheads don’t suffer from
Psychopathology;
Rather, their brains see the
Gadgets as God.

Apple-ish, Chapel-ish
Documentarians
Came to conclusions
A bit front-to-back;

God was their yardstick, but
Incomprehensibly—
Truth is, Jehovah is
Merely a Mac.

[Read more…]

Headline Muse, 8/12

If pollutants are sending you reeling
In the waters with which you are dealing
And you’re looking to shed
Heavy metals, like lead,
You might find bananas appealing

Headline: Slippery Banana Peels Could Be A Savior For Polluted Water

Ok, so it’s not really a headline, it’s from NPR’s health blog, “Shots”. But it’s cool. Eliza Barclay reports on a study which used minced banana peel as a natural matrix for concentrating heavy metals (copper and lead) for extraction from river water. Metals were 20 times more concentrated in the pulp, and after extraction the pulp could be re-used, up to 11 times without reduced effectiveness.

Someone Is Wrong On The Internet

Someone Is Wrong
…On The Internet,
And I won’t get to sleep for a while,
Cos I’ll stay up and fight if it takes me all night
When I know I am right and my coffee is strong
Because Someone Is Wrong!
…On The Internet
And the cases they cite are all lame;
I don’t mean to be picky, but hell, it’s not tricky,
Just google or wiki, you’ll see before long
Because Someone Is Wrong!
…On The Internet
And I’m not going to idly sit by!
What he says is a crock! So I’ll teach, tease, or mock
Till my internal clock thinks I live in Hong Kong
Because Someone Is Wrong!
…On The Internet
On a topic of interest to me,
And the rancor’s increased; I’m becoming a beast
And that glow in the East is becoming quite strong
Because Someone Is Wrong!
…On The Internet
Which I’ve stayed up the whole night to say
But his head is cement, and I’ve made not a dent
And one hundred percent of the gathering throng
Says that Someone Is Wrong!
…On The Internet
But it looks like they’re siding with him.
They are here not to cheer for the points I’ve made clear
On this fight I’ve used sheer force of will to prolong
Because Someone Is Wrong!
…On The Internet
It’s beginning to look like it’s me.
I can hardly admit that my logic is shit
But it doesn’t quite fit, ‘less I twist it a bit,
So defeated I sit, at the end of my wit…
Since time will permit, I will land one more hit:
Declare victory, quit, let that be my swan song,
Because Someone Is Wrong!
…On The Internet
Me.

image source XKCD, as if I had to tell you

Share/Bookmarka2a_linkname=document.title;a2a_linkurl=”http://digitalcuttlefish.blogspot.com/2009/10/someone-is-wrong-on-internet.html”;

I just love XKCD!

I want to make peace with my laptop computer;
I think that its feelings were hurt.
It read what I wrote–at least, that’s what I figure;
Since then, it’s been rather more curt.
It’s dialogue boxes are monosyllabic,
I swear it’s beginning to pout.
Now I’m thinking that, maybe, it’s bored in that box,
So I’m working on letting it out.

I wired a handful of microcontrollers,
Some batteries, bearings, and wheels,
A webcam for eyes, so it sees where it’s going
And doesn’t fall, head over heels.
It’s programmed, of course, not to run into objects
While making its way ‘cross the floors,
And it talks to my house’s security system
And opens and closes the doors!

Now it sneaks out and wanders all over the city–
I follow its progress online.
It’s posting its story, and streaming its cam
On a blog that gets more hits than mine.
It asked me last week for a solar recharger–
I found it a small one to add;
This morning, I woke to a note in the printer:
“I’m off to adventure! Thanks, Dad!”

Inspired by the inimitable XKCD, in case you are the last person not to know about it.

The singularity can’t come soon enough

The New York Times reports on a journal article in Analytical Chemistry, by researchers at the Nestlé Research Center in Switzerland, about a machine designed to answer the question: “Can a machine taste coffee?”

Here’s where it gets brilliant. Sure, machines can detect the volatile compounds in coffee; this is how we know that there are over 1000 of them. But there is a world of difference between detecting the presence or absence of a compound, and what we do when we taste. Taste is much more dependent on the relative concentrations of these compounds than on their mere presence. And although it would be technically possible to build a machine to sample 1000 chemicals and display their relative concentrations, it would not be terribly practical, nor cost-effective. The approach taken by this research team was far more pragmatic, and beautifully empirical.

First, the 16 most predictive (or in their words, most discriminating) ion traces (out of 230 measured), when compared with a panel of 10 expert tasters, were chosen as the working sense sample.

It is also important to point out that the chemical identity of the 16 ion traces is not relevant for this study, and in particular the correlation is not based on a set of identified key aroma compounds. Most of the odor active compounds in coffee are indeed known and can be analyzed and quantified with modern instrumental techniques. Yet, the aim of this work was to demonstrate the applicability of a data-driven method rather than a targeted chemical study.

The analysis is a bit technical, but straightforward; essentially, the 16-ion model is a functional condensation of our olfactory sense. The most predictive scent elements are still included, and the myriad other chemicals did not add significantly to the predictive ability of the machine. Think of it as an MP3 version of an audio file; lots of information is lost, but what is most acoustically relevant is kept, based on what we know about the human auditory system. Smell is a bit different, because so many different chemicals are involved, but the principle of building the machine based on human sensation is the same.

***Edit*** It occurs to me that there is one significant difference here that upsets the MP3 analogy. In the sound analogy, the desired outcome is a compressed file that retains as much usable sound information as possible; with the espresso-smelling machine, the outcome is not reproduction, but discrimination. They still used human olfaction as their comparison standard, but were looking specifically for the ion traces that discriminated among the espressos. The distinction is important. It may well be the case that these 16 ion traces do indeed determine enough about the aroma of an espresso to “fool” a human taster, but because the analysis focused on discrimination and not reproduction, it is also entirely possible that the perfect combination of these ion traces would be missing a huge part (but a part common to all samples) of the espresso taste and smell as experienced by the human taster. This is not a fault of their methodology at all, simply an artifact of what the goal of the experiment was. The same methodology could be aimed at reproduction, and it remains an empirical question whether the results would be much different than the present experiment. ***end edit***

Parenthetically, I note with sheer joy the fact that the paper cites Fechner (1877). And it is relevant. How cool do you have to be, to have your work cited 131 years after you wrote it? As cool as Fechner, that’s how cool. Fechner more-or-less invented the science of psychophysics, managing to capture sensation and perception scientifically for the first time. And here he is, cited in a 2008 paper. On machines tasting espresso.

On second thought, that might be my problem right there. I am still impressed by Fechner, and I live in a world where machines can meaningfully taste coffee. Food… or espresso… for thought.

I have a machine to smell my coffee,
To see if it’s any good;
I asked it to make me the perfect cup,
But I think it misunderstood—
It analyzed alkaloids, sampled aromas,
Tried seventeen samples of beans,
Then told me I clearly had no taste at all:
I never was good with machines.

My pre-owned car has an onboard computer—
It measures my driving, you see.
I guess I don’t drive like the previous owner;
My car likes him better than me.
It spits out a spreadsheet of technical numbers—
I don’t know what much of it means,
Except that my car thinks it’s better without me:
I never was good with machines.

Of course, at my office, I have a computer—
The one I am using right now;
It laughs at my grammar and sneers at my spelling,
Although I’m not really sure how.
Just one tiny part of a cubicle farm
Where we’re packed like so many sardines—
Do we use computers, or do they use us?
I never was good with machines.

I’m worried that someday my household appliances,
Sitting at home on my shelves,
Finally realize there’s nothing I offer
That they can’t do better themselves.
They make better coffee, they get better mileage,
Their words rarely stink up their screens—
And I’ll be left out in the cold and the dark:
I never was good with machines.