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• Lesson 1: no “special purpose” genes
• Lesson 2: genetic conservatism
• Lesson 3: change through “tweaks & twiddles”
• Lesson 4: the importance of the environment
“Every digital computing
device contains certain relay
like elements with discrete
equilibria. Such an element
has two or more distinct states
in which it can exist
indefinitely...It is worth
mentioning that the neurons
of the higher animals are
definitely elements in the
above sense... Following W.
Pitts and W.S. McCulloch...we
ignore the more complicated
aspects of neuron
functioning.”
John von Neumann
• CPU and memory are separate
• the processor is very fast
• serial operation
• very reliable parts; but the whole computer may break easily
• computers are programmed
• the memory and CPU are the same
• the parts (neurons) are very slow
• parallel; enormous interconnectivity
• unreliable parts; but the whole brain is very reliable
• brains learn
Things digital computers do well
Things human brains do well
• Numeric computation
• Symbolic computation
• Repetitive operations
• Follow instructions
• Find subtle patterns (intuition?)
• Find novel solutions by analogy
• Learn
x = (.5 + 3.9) cos(31.2) - b cos((44.3/41 + 1)7)
Eliza
Eliza: Hello. I am Eliza. How can I help you?
Me: You can’t help me at all.
Eliza: You like to think I can’t help you, do you not?
Me: I am sure of it.
Eliza: How long have you been sure of it?
Me: Ever since I was 10 years old.
Eliza: Why do you tell me you were 10 years old just now?
Me: You are not a real person
Eliza: Does it please you to believe I am not a real person?
Scripts, Schemata, and Frames
John went to McDonald's with Mary.
They ordered a hamburger and fries.
John gave the woman at the counter $3.49.
They left.
• What is McDonalds?• Why did John and Mary go there?• Why did John give the woman money?• Did they eat anything?
John went to McDonald's restaurant with Mary.
They ordered a hamburger and fries.
Suddenly, Mary's husband Lenny burst in with a shotgun.
John hid under a table.
• Why did John and Mary go to McDonalds?
• Why did John hide under the table?
• Did John get to eat his Big Mac?
• What were they doing before going to McDonalds?
• Where will Mary’s husband spend the rest of his life?
• fragile (vs. graceful degradation)– fixed repertoire– limited to well-defined domains
• how to get the knowledge in the system
fever, runny nose, muscle ache -> flu
fever, runny nose -> ?
Input Output
no fever, runny nose -> allergies
no fever, skin rash -> staphylococcus infection
“ought” ->
“ouch” ->
“tough” ->
“through” ->
“though” ->
“plouty” -> ?
“plough” -> ?
How do you pronounce “ou”?
“aw”
“au”
“uh”
“oo”
“oh”
input
h idden
output
My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.My grandmother lives near us. I like to visit my grandmother.
“I like to go to my grandmother’s house. Well…because
she gives us candy. Well ... and we eat there sometimes.
Sometimes we sleep overnight there. Sometime when
I got to go to my cousin’s ...”
manyyearsagoaboyandgirllivedina
castlebytheseatheyplayedwithadr
agon
00011 10111 00010 11011 11011
00100 10111 01111 01000 10111
11000 10010 10111 . . .
(m)
(a)
(n)
(y)
(y)
(e)
(a)(r)
(s)
(a)
(g)
(o)
(a)
(b)
(o)
(y)
(a)
(n)
(d)
(g)
(i)
(r)
(l)
(l)
(i)
(v)
(e)
(d)
(b)
(y)
(t)
(h)
(e)
(s)
(e)(a)
(t)
(h)
(e)
(y)
(p)
(l)
(a)
(y)
(e)(d)
(h)
(a)
(p)(p)
(i)(l)
(y)
(m)
0
0.5
1
1.5
2
2.5
3
3.5
Err
or
Time
Word learningstatistical learning
Saffran, Aslin, Newport, 1996
• 8 mo. old infants
• Passive exposure to 2 minutes of artificial
nonsense language
• Then present “words” vs. “non-words”
• Infants listened more to novel “non-words”
0000000000000000000000000000010
0000000000000000000000000010000
0000000000000000000001000000000
0000010000000000000000000000000
0000000000000000000100000000000
0000000000000000100000000000000
0001000000000000000000000000000
0000100000000000000000000000000
0100000000000000000000000000000
0000000000000000000100000000000
0000000000001000000000000000000
0000000000100000000000000000000
0010000000000000000000000000000
0000000010000000000000000000000
0000000000000000000100000000000
0000000000000000001000000000000
0000000000000000001000000000000
0000000000000000000100000000000
1000000000000000000000000000000
0000000000000000000000000010000
0000000000000000000001000000000
0000010000000000000000000000000
0000000000000000000100000000000
0000000000000000100000000000000
0001000000000000000000000000000
0000100000000000000000000000000
0100000000000000000000000000000
0000000000000000000100000000000
0000000000001000000000000000000
0000000000100000000000000000000
0010000000000000000000000000000
0000000010000000000000000000000
0000000000000000000100000000000
0000000000000000001000000000000
0000000000000000001000000000000
0000000000000000000100000000000
1000000000000000000000000000000
time
(woman)
(smash)
(plate)
(cat)
(move)
(man)
(break)
(car)
(boy)
(move)
(girl)
(eat)
(bread)
(dog)
(move)
(mouse)
(mouse)
(move)
(book)
(smash)
(plate)
(cat)
(move)
(man)
(break)
(car)
(boy)
(move)
(girl)
(eat)
(bread)
(dog)
(move)
(mouse)
(mouse)
(move)
(book)
Input Output (prediction)
.
.
bo
yg
irl
cat
dog
boo
kro
ckse
ese
es
hea
rhe
ars
catc
hca
tch
esw
ho
tha
tw
hich .
CURRENT INPUT
PREDICTED NEXT WORD
etc.
etc.
bo
yg
irlca
td
og
bo
okro
ckse
ese
es
hea
rhe
ars
catc
hca
tche
sw
hoth
at
wh
ich
.
CURRENT WORD
PREDICTED NEXT WORD
NOUNS
VERBS
DO absent
DO optional
DO obligatory
small
big
edible
breakable
ANIMATES
INANIMATES
HUMANS
ANIMALS
milk
bottle
bed
chair
kitty
doggie
cookie
candyhorse
birdmommy
daddyJane
go
run
see
man
drink
Do you want to eat a MACAROON?
“Critical mass effect”:
A critical number of words must be
learned before categories, concepts,
and relationships will become apparent.
Once that number is learned…things
take off.