Καλά, ο Χαρδαβέλας έχει σταματήσει να με εκπλήσσει από καιρό, αλλά πραγματικά τόσο γ.τ.π. δημοσιογραφική έρευνα είναι εντυπωσιακή, έως παιδαγωγική θα έλεγα.
Παιδαγωγική με την έννοια του ότι μας δείχνει ο άνθρωπος πως τα ΜΜΕ μπορούν να πάρουν μία πληροφορία και να την διαστρέψουν και να την παρουσιάσουν έτσι ώστε να περάσει στον κόσμο μία συγκεκριμένη άποψη.
Από την άλλη, είναι εντυπωσιακό το ότι απλά μόλις άνοιξα την τηλεόραση έπεσα στο σημείο της εκπομπή όπου έκανε αναφορά σε μία μπούρδα με την οποία είχα ασχοληθεί και παλιότερα και συγκεκριμένα με αφορμή ένα άρθρο στο Indymedia (βλέπε Inymedia-αρβύλα και ο Μετεωρίτης).
Διευκρινίζοντας αυτό που έγραψα παραπάνω, το Indymedia τότε είχε γράψει αυτά που είχε γράψει, παρουσιάζοντας την όλη ιστορία ως έργο των Αμερικάνων (την αδιαθεσία των κατοίκων εκεί που έπεσε ο Μετεωρίτης δηλαδή), τώρα οι Πύλες του Ανεξήγητου παρουσιάζουν το όλο πράγμα ως ενδεικτικό της Θεωρίας της Πανσπερμίας.
Για το συγκεκριμένο γεγονός πάντως, μπορεί όποιος θέλει να βρει περισσότερες πληροφορίες στο αρχικό ποστ. Εδώ απλά επαναλαμβάνω το λινκ από το Bad Astronomy Blog.
Για την Θεωρία της Πανσπερμίας, απλά θα πω ότι δεν απαντά σε κανένα ερώτημα για την προέλευση της ζωής. Απλά μεταθέτει το ερώτημα κάπου αλλού. Ενδιαφέρον, σχετικά με όλα αυτά, έχει και το τελευταίο ποστ του Βιολόγου.
Btw, στο τελευταίο κομμάτι της εκπομπής άκουσα μερικές απίστευτες πίπες (ο Einstein τρελάθηκε μετά το E=mc^2 και διάφορα τέτοια) που κάνουν την όλη εκπομπή πολύ promising για μαργαριταρόκηπο, οπότε άμα δω και την υπόλοιπη ίσως επανέλθω με περισσότερη δημοσιογραφία του κώλου.
3 σχόλια:
Κι εσύ πάλι σαββατιάτικα στον καναπέ με τον Χάρδα και τον Γουδη απέναντι...
Και να σκεφτείς ότι είχα πάει και είχα κάνει τη γλάστρα στην περίφημη εκπομπή του με τον Γκέλερ.
Αλήθεια!
A haemoglobin molecule consists of four chains of amino acids
twisted together. Let us think about just one of these four chains. It
consists of 146 amino acids. There are 20 different kinds of amino acids
commonly found in living things. The number of possible ways of
arranging 20 kinds of thing in chains 146 links long is an inconceivably
large number, which Asimov calls the 'haemoglobin number'. It is easy
to calculate, but impossible to visualize the answer. The first link in
the 146-long chain could be any one of the 20 possible amino acids.
The second link could also be any one of the 20, so the number of
possible 2-link chains is 20 x 10, or 400. The number of possible 3-link
chains is 20 x 20 x 20, or 8,000. The number of possible 146-link
chains is 20 times itself 146 times. This is a staggeringly large number.
A million is a 1 with 6 noughts after it. A billion 11,000 million) is a
1 with 9 noughts after it. The number we seek, the 'haemoglobin
number', is (near enough) a 1 with 190 noughts after it! This is the
chance against happening to hit upon haemoglobin by luck. And a
haemoglobin molecule has only a minute fraction of the complexity of
a living body. Simple sieving, on its own, is obviously nowhere near
capable of generating the amount of order in a living thing. Sieving is
an essential ingredient in the generation of living order, but it is very
far from being the whole story. Something else is needed. To explain
the point, I shall need to make a distinction between 'single-step'
selection and 'cumulative' selection. The simple sieves we have been
considering so far in this chapter are all examples of single-step
selection. Living organization is the product of cumulative selection.
The essential difference between single-step selection and
cumulative selection is this. In single-step selection the entities
selected or sorted, pebbles or whatever they are, are sorted once and for
all. In cumulative selection, on the other hand, they 'reproduce'; or in
some other way the results of one sieving process are fed into a
subsequent sieving, which is fed into . . ., and so on. The entities are
subjected to selection or sorting over many 'generations' in succession.
The end-product of one generation of selection is the starting point for
the next generation of selection, and so on for many generations. It is
natural to borrow such words as 'reproduce' and 'generation', which
have associations with living things, because living things are the
main examples we know of things that participate in cumulative
selection. They may in practice be the only things that do. But for the
moment I don't want to beg that question by saying so outright.
Sometimes clouds, through the random kneading and carving of the
winds, come to look like familiar objects. There is a much published
photograph, taken by the pilot of a small aeroplane, of what looks a bit like the face of Jesus, staring out of the sky. We have all seen clouds that
reminded us of something - a sea horse, say, or a smiling face. These
resemblances come about by single-step selection, that is to say by a
Single coincidence. They are, consequently, not very impressive. The
resemblance of the signs of the zodiac to the animals after which they
are named, Scorpio, Leo, and so on, is as unimpressive as the predictions
of astrologers. We don't feel overwhelmed by the resemblance, as we are
by biological adaptations - the products of cumulative selection. We
describe as weird, uncanny or spectacular, the resemblance of, say, a leaf
insect to a leaf or a praying mantis to a cluster of pink flowers. The
resemblance of a cloud toaweaselisonly mildly diverting, barely worth
calling to the attention of our companion. Moreover, we are quite likely
to change our mind about exactly what the cloud most resembles.
Hamlet. Do you see yonder cloud that's almost in shape of a camel?
Polonius. By the mass, and 'tis like a camel, indeed.
Hamlet. Methinks it is like a weasel.
Polonius. It is backed like a weasel.
Hamlet. Or like a whale?
Polonius. Very like a whale.
I don't know who it was first pointed out that, given enough time, a
monkey bashing away at random on a typewriter could produce all the
works of Shakespeare. The operative phrase is, of course, given enough
time. Let us limit the task facing our monkey somewhat. Suppose
that he has to produce, not the complete works of Shakespeare but just
the short sentence 'Methinks it is like a weasel', and we shall make it
relatively easy by giving him a typewriter with a restricted keyboard,
one with just the 26 (capital) letters, and a space bar. How long will he
take to write this one little sentence?
The sentence has 28 characters in it, so let us assume that the
monkey has a series of discrete 'tries', each consisting of 28 bashes at the
keyboard. If he types the phrase correctly, that is the end of the
experiment. If not, we allow him another 'try' of 28 characters. I don't
know any monkeys, but fortunately my 11-month old daughter is an
experienced randomizing device, and she proved only too eager to step
into the role of monkey typist. Here is what she typed on the computer:
UMMK JK CDZZ F ZD DSDSKSM
S SS FMCV PU I DDRGLKDXRRDO
RDTE QDWFDVIOY UDSKZWDCCVYT
H CHVY NMGNBAYTDFCCVD D
RCDFYYYRM N DFSKD LD K WDWK
HKAUIZMZI UXDKIDISFUMDKUDXI
She has other important calls on her time, so I was obliged to program
the computer to simulate a randomly typing baby or monkey:
WDLDMNLT DTJBKWIRZREZLMQCO P
Y YVMQKZPGJXWVHGLAWFVCHQYOPY
MWR SWTNUXMLCDLEUBXTQHNZVIQF
FU OVAODVYKDGXDEKYVMOGGS VT
HZQZDSFZIHIVPHZPETPWVOVPMZGF
GEWRGZRPBCTPGQMCKHFDBGW ZCCF
And so on and on. It isn't difficult to calculate how long we should
reasonably'expect to wait for the random computer (or baby or monkey)
to type METHINKS IT IS LIKE A WEASEL. Think about the total
number of possible phrases of the right length that the monkey or baby
or random computer could type. It is the same kind of calculation as
we did for haemoglobin, and it produces a similarly large result. There
are 27 possible letters (counting 'space' as one letter) in the first
position. The chance of the monkey happening to get the first letter-M
-right is therefore 1 in 27. The chance of it getting the first two letters
— ME - right is the chance of it getting the second letter - E - right (1 in
27) given that it has also got the first letter - M - right, therefore 1/27
x 1/27, which equals 1/729. The chance of it getting the first word -
METHINKS - right is 1/27 for each of the 8 letters, therefore (1/27) X
(1/27) x (1/27) x (1/27). .., etc. 8 times, or (1/27) to the power 8. The
chance of it getting the entire phrase of 28 characters right is (1/27) to
the power 28, i.e. (1/27) multiplied by itself 28 times. These are very
small odds, about 1 in 10,000 million million million million million
million. To put it mildly, the phrase we seek would be a long time
coming, to say nothing of the complete works of Shakespeare.
So much for single-step selection of random variation. What about
cumulative selection; how much more effective should this be? Very
very much more effective, perhaps more so than we at first realize,
although it is almost obvious when we reflect further. We again use
our computer monkey, but with a crucial difference in its program. It
again begins by choosing a random sequence of 28 letters, just as
before:
WDLMNLT DTJBKWIRZREZLMQCO P
It now 'breeds from' this random phrase. It duplicates it repeatedly,
but with a certain chance of random error - 'mutation' - in the
copying. The computer examines the mutant nonsense phrases, the
'progeny' of the original phrase, and chooses the one which, however
slightly, most resembles the target phrase, METHINKS IT IS LIKE A WEASEL. In this instance the winning phrase of the next 'generation'
happened to be:
WDLTMNLT DTJBSWIRZREZLMQCO P
Not an obvious improvement! But the procedure is repeated, again
mutant 'progeny' are 'bred from' the phrase, and a new 'winner' is
chosen. This goes on, generation after generation. After 10 generations,
the phrase chosen for 'breeding' was:
MDLDMNLS ITpSWHRZREZ MECS P
After 20 generations it was:
MELDINLS IT ISWPRKE Z WECSEL
By now, the eye of faith fancies that it can see a resemblance to the
target phrase. By 30 generations there can be no doubt:
METHINGS IT ISWLIKE B WECSEL
Generation 40 takes us to within one letter of the target:
METHINKS IT IS LIKE I WEASEL
And the target was finally reached in generation 43. A second run of
the computer began with the phrase:
Y YVMQKZPFfXWVHGLAWFVCHQXYOPY,
passed through (again reporting only every tenth generation):
Y YVMQKSPFTXWSHLIKEFV HQYSPY
YETHINKSPITXISHLIKEFA WQYSEY
METHINKS IT ISSLIKE A WEFSEY
METHINKS IT ISBLIKE A WEASES
METHINKS IT ISJLIKE A WEASEO
METHINKS IT IS LIKE A WEASEP
and reached the target phrase in generation 64. m a third run the
computer started with:
GEWRGZRPBCTPGQMCKHFDBGW ZCCF
and reached METHINKS IT IS LIKE A WEASEL in 41 generations of
selective 'breeding'.
The exact time taken by the computer to reach the target doesn't
matter. If you want to know, it completed the whole exercise for me,
the first time, while I was out to lunch. It took about half an hour.
(Computer enthusiasts may think this unduly slow. The reason is that the program was written in BASIC, a sort of computer baby-talk. When
I rewrote it in Pascal, it took 11 seconds.) Computers are a bit faster at
this kind of thing than monkeys, but the difference really isn't
significant. What matters is the difference between the time taken by
cumulative selection, and the time which the same computer, working
flat out at the same rate, would take to reach the target phrase if it
were forced to use the other procedure of single-step selection: about a
million million million million million years. This is more than a
million million million times as long as the universe has so far existed.
Actually it would be fairer just to say that, in comparison with the
time it would take either a monkey or a randomly programmed computer
to type our target phrase, the total age of the universe so far is a
negligibly small quantity, so small as to be well within the margin of
error for this sort of back-of-an-envelope calculation. Whereas the time
taken for a computer working randomly but with the constraint of
cumulative selection to perform the same task is of the same order as
humans ordinarily can understand, between 11 seconds and the time it
takes to have lunch.
There is a big difference, then, between cumulative selection (in
which each improvement, however slight, is used as a basis for future
building), and single-step selection (in which each new 'try' is a fresh
one). If evolutionary progress had had to rely on single-step selection, it
would never have got anywhere. If, however, there was any way in
which the necessary conditions for cumulative selection could have
been set up by the blind forces of nature, strange and wonderful might
have been the consequences. As a matter of fact that is exactly what
happened on this planet, and we ourselves are among the most recent,
if not the strangest and most wonderful, of those consequences.
It is amazing that you can still read calculations like my
haemoglobin calculation, used as though they constituted arguments
against Darwin's theory. The people who do this, often expert in their
own field, astronomy or whatever it may be, seem sincerely to believe
that Darwinism explains living organization in terms of chance -
'single- step selection' - alone. This belief, that Darwinian evolution is
'random', is not merely false. It is the exact opposite of the truth.
Chance is a minor ingredient in the Darwinian recipe, but the most
important ingredient is cumulative selection which is quintessentially
nonrandom.
O Χαρδαβέλλας και οι λοιποί της ίδιας μπουρδολογίας βοηθούν όλους μας να κάνουμε μια καλή επανάληψη αραιά και που σε πράγματα που ήδη ξέρουμε.Όντως παιδαγωγικό!
Χαρδαβέλλας,Ε,εσωτέρικα φόρουμ,ομοιοπαθητική,ψευδοεπιστήμη,
συνωμοσιολογίες και το αφεντικό τρελλάθηκε.
Πάντως ο Dawkins ήταν απαραίτητος για λίγο evo 101.
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