Coast to Coast is the first track on Elliot Smith's final, posthumous album "From a Basement on a Hill," and it sets the tone for the rest of the album: disjointed, dense, fraying and beautiful.
http://www.youtube.com/watch?v=bAvqZsRhjwk&fmt=6
Coast to Coast begins with a portion of the song played in reverse. Enter twin lumbering drum tracks and an out of tune slide guitar lead. I've listened over 50 times and just now realized that Elliot's whistling along with the guitar track. His first line: "Last stop for a resolution."
The lyrics are juvenile, but cognizant and self-examining. Elliot has no new ideas and is therefore useless to those who are expecting more (including you!). Instead of deliberate invention, he takes a "kitchen sink approach," and shovels all of his recording and songwriting reserves into the studio cauldron (did he know beforehand that this would be his final effort?).
This "kitchen-sink" approach explains why there's at least 3 guitar tracks, a piano track, a distorted bass, 2 drum tracks, 3 separate vocal tracks, several additional "background" tracks featuring a lightning-speed poetry reading (and whistling). It's chaotic, but its beauty is evident in the way "Coast to Coast" grows and reveals itself with every subsequent listen.
At any moment, the wheels could detach from the wagon and the barely-together instruments which compose the song could careen into the abyss. Yet "Coast to Coast" marches ahead with minor regard for refrain or repetition, as Elliot bemoans that he's "got no new act to amuse you." Its structure is unconventional, and the rapidity of changes suggests a songwriter who is easily bored, or seeking to outdo himself. The droning piano, which would normally have a centering effect, somehow edges us closer to the brink.
At around the 4 minute mark, the poetry track which was submerged in the mix bubbles up. Is it the outside world leaking in? The spoken words supplant us from a musical trance, especially if we reacted to them by yanking off our headphones.
As the instruments slide into a black hole, these voices take over, and the track ends. We missed the last stop; nothing is resolved.
Showing posts with label music. Show all posts
Showing posts with label music. Show all posts
Friday, April 1, 2011
Saturday, November 7, 2009
I just finished reading Goedel Escher Bach
GEB alternates dialogues and essays on the author's staggering range of fixations and obsessions in which Hofstadter adds his own remarkable insights and comparisons on topics including music, art, mathematics, genetics and philosophy. GEB's sprawling nature follows tangled paths but eventually loops back to the question of intelligence, souls, free will and self-awareness.
The unorthodox structure is what sets the book apart, but the braiding of ideas may lead to a takeaway of: "Ok, that's interesting, and you're clever, but what is the chief takeaway here?"
This is a common criticism which led led Hofstadter to author the psuedo-sequel "I Am a Strange Loop" (which I haven't read), in which he distills his arguments more directly and concisely (and personally -- he imagines a low-resolution "simulation" of his wife's mind within his own after her death).
Anyone who completes GEB comes away with an honorary computer science degree, as there's a heavy focus on computability theory, data and data structures, natural language processing, AI, recursion, memory, hardware, software, all under the guise of philosophy and investigating what gives rise to self-awareness and intelligence.
On top of this, the GEB reader receives an introduction to the art of Escher, Magritte, Bach, John Cage, as well as some basics of neuroscience, boolean logic, zen philosophy, number theory, music theory and molecular biology.
Although the number theory and biology chapters dragged, I was fascinated by the discussion of the Goedel incompleteness proof and the implications it had for the mathematics community at the turn of the century. There is also a fascinating section on AI that starts with Turing tests and pattern recognition and ends with the remarkable conclusion that a truly AI may be terrible at all the things that people may struggle with as well, such as rapid computation or chess playing.
At the least, GEB presents a multitude of ideas and food for thought. At its best, it instills lucid notions of how our minds work and what gives rise to life, language and intelligence.
The unorthodox structure is what sets the book apart, but the braiding of ideas may lead to a takeaway of: "Ok, that's interesting, and you're clever, but what is the chief takeaway here?"
This is a common criticism which led led Hofstadter to author the psuedo-sequel "I Am a Strange Loop" (which I haven't read), in which he distills his arguments more directly and concisely (and personally -- he imagines a low-resolution "simulation" of his wife's mind within his own after her death).
Anyone who completes GEB comes away with an honorary computer science degree, as there's a heavy focus on computability theory, data and data structures, natural language processing, AI, recursion, memory, hardware, software, all under the guise of philosophy and investigating what gives rise to self-awareness and intelligence.
On top of this, the GEB reader receives an introduction to the art of Escher, Magritte, Bach, John Cage, as well as some basics of neuroscience, boolean logic, zen philosophy, number theory, music theory and molecular biology.
Although the number theory and biology chapters dragged, I was fascinated by the discussion of the Goedel incompleteness proof and the implications it had for the mathematics community at the turn of the century. There is also a fascinating section on AI that starts with Turing tests and pattern recognition and ends with the remarkable conclusion that a truly AI may be terrible at all the things that people may struggle with as well, such as rapid computation or chess playing.
At the least, GEB presents a multitude of ideas and food for thought. At its best, it instills lucid notions of how our minds work and what gives rise to life, language and intelligence.
Sunday, August 16, 2009
When a band I like comes to town, I'll know
The List is a comprehensive listing of all the known shows coming to the Bay Area listed by artist and by venue.
There are hundreds of concerts and nearly 1500 bands in the list so I threw together a script to scrape it and intersect those bands with the artists in my iTunes library.
The result is, I now know that these acts are playing in the near future:
The next step is to scrape the concert details as well, use fuzzy matching, run it automatically, and set up alerts.
But this only took 15 minutes to write in python and it would have taken me way longer to parse manually.
EDIT:
Instead of doing a set intersect, I now use difflib to find "close matches." It's slower but still runs start to finish in about 10 seconds, which is fine considering especially that the data changes infrequently.
I also unescape the ampersand in the iTunes xml, and filter out "The " because:
...an exact match preceded by 'the' is penalized more than a suffix. So 'pixies' would match 'pixiestickers' instead of 'the pixies' in the case where I only select the top match (since ideally there's a one-to-one mapping).
Instead of writing my own fuzzy matching algorithm, for now I'll just chop off 'The ' and live with the results. Although some of the matches aren't useful, it does better at finding bands such as ...and you will know us by the trail of dead and The Ting Tings.
There are hundreds of concerts and nearly 1500 bands in the list so I threw together a script to scrape it and intersect those bands with the artists in my iTunes library.
The result is, I now know that these acts are playing in the near future:
atmosphere
bat for lashes
beirut
blink 182
butthole surfers
calexico
cat power
collective soul
dan deacon
deerhoof
deerhunter
dropkick murphys
elvis costello
fever ray
flipper
ghostface killah
girl talk
green day
grizzly bear
in flames
kenny rogers
lil wayne
m.i.a.
mastodon
meat puppets
mirah
modest mouse
mstrkrft
no age
nofx
pearl jam
placebo
porcupine tree
sunny day real estate
tenacious d
thievery corporation
tv on the radio
weezer
yo la tengo
The next step is to scrape the concert details as well, use fuzzy matching, run it automatically, and set up alerts.
But this only took 15 minutes to write in python and it would have taken me way longer to parse manually.
EDIT:
Instead of doing a set intersect, I now use difflib to find "close matches." It's slower but still runs start to finish in about 10 seconds, which is fine considering especially that the data changes infrequently.
I also unescape the ampersand in the iTunes xml, and filter out "The " because:
>>> import difflib
>>> difflib.get_close_matches('foo', ['the foo', 'foods'], n=1)
['foods']
...an exact match preceded by 'the' is penalized more than a suffix. So 'pixies' would match 'pixiestickers' instead of 'the pixies' in the case where I only select the top match (since ideally there's a one-to-one mapping).
Instead of writing my own fuzzy matching algorithm, for now I'll just chop off 'The ' and live with the results. Although some of the matches aren't useful, it does better at finding bands such as ...and you will know us by the trail of dead and The Ting Tings.
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