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then and now?
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0.589
AUDIENCE: Yes.
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0.365
SPEAKER 1: OK.
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0.583
So that's J. What happens next?
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1.567
AUDIENCE: [INAUDIBLE].
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1.677
SPEAKER 1: OK.
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0.583
That's K. K, L, good.
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3.77
B, that's easy.
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0.91
On top.
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0.55
A, even easier.
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1.02
On top.
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1.036
AUDIENCE: Am I going to finish this entire thing?
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1.314
SPEAKER 1: Yes.
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0.74
We need 13 more, give or take.
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2.498
M and--
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0.952
AUDIENCE: N.
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0.5
SPEAKER 1: N, O. I didn't do a very good job there.
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3.51
U, V. OK, definitely not good.
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2.97
Y. That's good.
1,314.73
1.06
It goes toward the end.
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1.01
R, a little harder.
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2.77
But this is actually a good situation for us
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1.92
to be in because-- you keep going, I'll keep talking.
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2.208
So even as Allison is sorting this, she's
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2.682
dealing with each of these blue books one at a time.
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2.25
But notice what's happening to her right hand.
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2.14
There literally is more and more work, it seems, happening in her right hand
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3.77
because as she encounters R or now W, not only does she need more thought,
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3.58
she also needs to do more flipping to actually find
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2.41
the right spot for W. This is H. She's doing the same thing again.
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2.98
So it feels like the algorithm has started to slow down.
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3.3
At first, it was pretty easy to just make a short list.
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2.61
But now that the list is getting longer, it
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2.01
feels like she's fixing a lot of work, or finding a location is
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3.91
getting harder and harder.
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2.49
Or at least taking longer and longer.
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1.83
Maybe the alphabet itself is not that much more difficult.
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2.51
Now, we have I. I can only stall so much longer.
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3.01
G.
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0.5
AUDIENCE: Sorry.
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0.29
SPEAKER 1: No, that's fine.
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1.125
E, good.
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0.505
OK.
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0.5
So it's getting a little easier because we're at the beginning.
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3.28
Sorted.
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0.77
So what were you thinking?
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1.39
What was that algorithm?
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1.255
AUDIENCE: It was just take a letter, take another letter,
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2.375
and then test to see if the letter is before or after.
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3.294
SPEAKER 1: OK, good.
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0.833
AUDIENCE: And then put it in the correct place on either side.
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2.103
SPEAKER 1: Perfect.
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0.43
So a perfect way of thinking about this as well.
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1.82
So thank you so much.
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0.945
AUDIENCE: Thank you.
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0.405
SPEAKER 1: Very nicely done.
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1.166
And suppose the problem's a little harder.
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2.144
I'll do this one myself here.
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2.21
But suppose we have some playing cards.
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2.22
And these are the type that probably everyone here can see.
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3.42
So here is a standard deck of cards, including
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4.09
the jokers, which we won't need.
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1.636
How do you go about sorting things like this?
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1.874
I don't know if-- actually, I didn't think in advance.
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4.88
I should have shuffled these.
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1.88
So if you want to shuffle these cards.
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2.35
This is not going to end well.
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2.11
OK.
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0.73
So suppose we have all of these cards nicely shuffled here.
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3.45
And I have before me a big problem, a big pile of cards.
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3.215
And the goal, for whatever reason, you wanted to start the game
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2.625
or you like to be orderly, is to sort the cards.
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2.1
What's your algorithm going to be for sorting these cards?
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4.081
What might you do?
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0.749
Yeah.
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0.702
AUDIENCE: [INAUDIBLE].
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0.916
SPEAKER 1: Do them in piles based on the number.
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1.999
OK, so here's the number 2.
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1.51
So you want to make a pile for all the 2's?
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2.02
OK, so we can do that.
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1.19
So here's a pile for all the 4's.
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1.467
And let me make myself some more room.
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1.583
So we can put 2's here.
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1.2
4's here.
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0.77
Here's a 3.
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0.584
So I'm going to put this in between the 2 and the 4.
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2.166
Here's a 5.
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0.96
I'm going to put that over here.
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1.43
And if I jump around, here's a Jack.
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1.52
So this is going to go way over there.
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2.09
7, 8.
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1
6 can go over here.
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1.59
Here's another 4, so I can put it here.
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2.83
And I can bucketize all of the cards.
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2.47
So this is good intuition because it makes a pretty big problem, 52 cards,
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4.11
a little more tenable.
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1.149
You can just now flip through all of the cards one at a time,
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2.541
or whatever you encounter first.
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1.53
And just drop it in the correct bucket.
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2.01
But that's, of course, not going to get you to the end.
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2.291