Turing - Revision history

Adamcolton at 00:17, 12 June 2016

2016-06-12T00:17:17Z

← Older revision		Revision as of 00:17, 12 June 2016
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	"Ok, point conceded."		"Ok, point conceded."

			--- Sections Elided (for now) ---

			=== Episode Six ===
			They sent Margret-the-intern to Stephen. It wasn't her fault, but she was the only "hobbit" that couldn't say "no, fuck-no, you do, I won't fucking do it".

			Margret-the-intern timidly knocked on his office door and Stephen instantly knew (because an intern was knocking on his door when everone else seemed to have business that took them far rom his office) that something was terribly wrong.

			"Yes..."

			"There's, uh, sort of, a problem. Dan was running some tests a three weeks ago. Right before they started on episode 5. He was working on the character shader. And one of his simulations produced a plot he really like - so he printed it off. He thought it would be a fun memento. But-and we're not sure how this happened-it ended up in the hands of production."

			Stephen start to brush the concerns aside, "Ok, so we ran with a dev script. That's fine. Episode 5 has been our highest rated to date. Just don't let anyone know that...", he stopped mid-sentence as the realization hit him.

			"Dan ran this on dev"
			"Yes"
			"As a test"
			"Yes"
			"Oh, fuck"
			"Margret"
			"Yes?"
			"Please go away now"
			"Ok"

			Before Margret-the-intern had closed the door, Stephen had Stan on the phone and relayed Margret's (on behalf of the more cowardly hobbits) message.

			"I'm missing something, you wouldn't be this concerned if we simply ran with an unsanctioned plot." Stan asked Stephen.

			"Yeah, here's the issue; Hedy keeps track of a massive story-universe. Every character in the show has a fully family tree going back at least 5 generations - each member with their own full back story. The strength of the AI isn't in the sort of fuzzy thinking that humans use when telling a story, it's sheer force of details. The database of every detail is hundreds of terabytes. So dev doesn't store state - that is, when we run a test, it doesn't save it's changes. So the point where the story left off, after episode 5, is lost. The official universe is ready to pick up after episode 4."

			"Oh, fuck"

			"Yeah"

			"Ok, get everyone on board, I want our best plan to fix this in three hours"

			An hour later, Stephen was standing in front of the project leads going over the details of how screwed they were for the third time.

			"So we need to come up a with a plan. Somehow we need to be able to get Episode 6 out of Hedy."

			One of the producers spoke up immediately, "We could do 'it was all a dream', episode 5 didn't happen, or have them time travel back to the end of episode 4 something like that"

			A murmor went up. Everyone was on the same page there - episode 5 had been great, rolling it back would be a huge hit to their ratings.

			Then Freddy spoke up. "Thank god I'm a lazy son-of-bitch. Stephen, I'm happy to inform you that I never put a true random source on it. I always meant to, but a Unix time seed worked well enough". Then Freddy got up and left.

			The room froze for a minute, then the hobbits burst into commotion while everyone else sat dumbstruck. The producer that had offered the original 'dreaming/time-travel' solution chimed in again after a few seconds, "What the fuck does that mean?"

			Stephen, still laughing to himself, "Hedy makes billions of random choices to produce a script. Getting even one of them wrong will produce a wildly different script. But if you made every choice the same, you'd get the same script both times. What Freddy just told us is that if we can figure out the exact second that Dan ran his program, we duplicate every random choice it made. All we have to do is modify his code to write the state-of-the-universe back when it's done. Then we'll be able to get our Episode 6".

	[[Category:writing]]		[[Category:writing]]

Adamcolton: /* Story */

2016-06-11T23:49:32Z

Story

@@ Line 54: / Line 54: @@
 The video of Freddie sharing a smile with Tom froze as Stan Ulam enthusiastically tapped the spacebar on a thin computer.
-"We hired him shortly after that. Actually, you can see me right there in the corner with my phone. I was sending a message that we had to hire him then. He's continued working on Turing, he's got a whole team now. But we have a perception problem. We need a demonstration of the algorithms power - Deep Blue vs Kasperov, Watson on Jeopardy. We want to use Turing to write a show."
+"We hired him shortly after that. Actually, you can see me right there in the corner with my phone. I was sending a message that we had to hire him then. He's continued working on Turing, he's got a whole team now. But we have a perception problem. We need a demonstration of the algorithms power - Deep Blue vs Kasperov, Watson on Jeopardy, AlphaGo ver Lee Sedol. We want to use Turing to write a show."
 [[Category:writing]]

Adamcolton: /* Characters */

2016-06-11T23:13:55Z

Characters

← Older revision		Revision as of 23:13, 11 June 2016
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	== Notes ==		== Notes ==
	=== Characters ===		=== Characters ===
	* Owner of Netflix style movie service		* Conroy Jons: Owner of Netflix style movie service
	* Stan Ulam: Elon Musk style investor		* Stan Ulam: Elon Musk style investor
	* Freddie Williams: Created the core algorithm for his Ph.D at Carnagie Mellon		* Freddie Williams: Created the core algorithm for his Ph.D at Carnagie Mellon

Adamcolton at 17:17, 9 March 2016

2016-03-09T17:17:01Z

← Older revision		Revision as of 17:17, 9 March 2016
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	The Musk character is seen by many as the face and therefor the creator. But as the project is unveiled to the public, he is adamant that he didn't build it, just saw the value and funded it. Focus shifts to Fred Williams, and he tries to explain that he developed the core algorithm, but it was only a variation on earlier algorithms and the real work was in tuning it and building the modules.		The Musk character is seen by many as the face and therefor the creator. But as the project is unveiled to the public, he is adamant that he didn't build it, just saw the value and funded it. Focus shifts to Fred Williams, and he tries to explain that he developed the core algorithm, but it was only a variation on earlier algorithms and the real work was in tuning it and building the modules.

			Diversity in tech. Very few programmers fit the stereotype. Introverts work well on integrated teams. Cultural and gender diversity builds better products.
	== Story ==		== Story ==
	Freddie Williams sat down in front of a panel of six. Five of the members were hard scientists. Or mathematicians. That was an eternal debate amongst them. But they all agreed the sixth member did not belong because he was the "old kook". Not that they would ever call him that outside their most guarded moments, calling Tom Kilburn, one of the most eminent philosophers, an old kook would be career suicide, even for an esteem professor of computer science. Even if all reputable computer scientists knew he was an old kook, it simply wasn't said.		Freddie Williams sat down in front of a panel of six. Five of the members were hard scientists. Or mathematicians. That was an eternal debate amongst them. But they all agreed the sixth member did not belong because he was the "old kook". Not that they would ever call him that outside their most guarded moments, calling Tom Kilburn, one of the most eminent philosophers, an old kook would be career suicide, even for an esteem professor of computer science. Even if all reputable computer scientists knew he was an old kook, it simply wasn't said.

Adamcolton: /* Story */

2016-03-09T16:57:58Z

Story

← Older revision		Revision as of 16:57, 9 March 2016
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	"Well, I started there. I fed it a corpus of every children's story I could find. And it produced stories that had plot, characters, even the prose was not bad. But they didn't fit together right. Most children's stories have a moral. Some point that the story is getting across. Without that it's just sort of a fever dream of princesses, dragons, knights and talking cutlery. That was the real challenge, giving Turing a goal, write a story with a specific point to it. The essence of that algorithm - well, it's five algorithms and two data structures, are described in detail from pages 72 through 112. The next part isn't in the thesis though.		"Well, I started there. I fed it a corpus of every children's story I could find. And it produced stories that had plot, characters, even the prose was not bad. But they didn't fit together right. Most children's stories have a moral. Some point that the story is getting across. Without that it's just sort of a fever dream of princesses, dragons, knights and talking cutlery. That was the real challenge, giving Turing a goal, write a story with a specific point to it. The essence of that algorithm - well, it's five algorithms and two data structures, are described in detail from pages 72 through 112. The next part isn't in the thesis though.

	Once I had that, it turned out to be flexible. One time I gave it the instruction to produce a story whose moral was 'Always try a Monte Carlo simulation first'~~, I was a bit frustrated at the time~~. But to my surprise, it used it's web crawler to pull in enough information to describe a Monte Carlo simulation. Sure, it was a talking badger explaining ~~Monte Carlo to his friends and~~ how his uncle ~~used it to steal~~ the kingdom that was his hereditary right. But it wasn't a bad summary. So I switch the corpus over ~~thesuses (thesi? please somebody tell me what word~~ to ~~use here)~~ and with a little tweaking I was producing pretty decent papers.		Once I had that, it turned out to be flexible. One time, as a joke, I gave it the instruction to produce a story whose moral was 'Always try a Monte Carlo simulation first'. But to my surprise, it used it's web crawler to pull in enough information to describe a Monte Carlo simulation. Sure, it was a talking badger explaining how his uncle had stole the kingdom that was his hereditary right and only a simple but generic optimization algorithm would let him find justice. But it wasn't a bad summary. So I switch the corpus over to academic text and with a little tweaking I was producing pretty decent papers.

	The last step was to convert the elements of my research over to a story it could tell. The result is the document you have in front of you. And three other dissertations that I sold ~~to panicked grad students~~. Kidding."		The last step was to convert the elements of my research over to a story it could tell. The result is the document you have in front of you. And three other dissertations that I sold on the black market. Kidding."

	The level of ~~wispering~~ and note passing among the five very serious members of the committee had been escalating as Freddie explained the source of his ~~disertation~~. Now that he sat silently it rose to a very quiet fervor. Before they could ask any of their questions, Tom spoke up.		The level of whispering and note passing among the five very serious members of the committee had been escalating as Freddie explained the source of his dissertation. Now that he sat silently it rose to a very quiet fervor. Before they could ask any of their questions, Tom spoke up.

	"Is Turing conscious?", asked the old kook.		"Is Turing conscious?", asked the old kook.

	"Sort of. ~~Considering he~~ wrote a very technical description of himself, I would argue he is self-aware. He is capable of abstract thought, even directed self learning."		"Sort of. He wrote a very technical description of himself, I would argue he is self-aware. He is capable of abstract thought, even directed self learning. That's not to say he has a human mind."

	"I'm not sure the term 'sort of' belongs in a rigorous defense of a computer science ~~thesis~~", said the old kook ~~as he propped up a straw man, then leaned back in his chair to show Freddie he was going to stay out of his way while he skewered it through the heart.~~		"I'm not sure the term 'sort of' belongs in a rigorous defense of a computer science dissertation", said the old kook.
	~~I can't Fur Elise (at least not past the first few bars) so I can sort of play. And~~ .

	"Sure it does. When I get a 76% on a math test, I sort of understand that subject. If Turing meets 76% of the definitions of conscious, he's sort of conscious. I'm awake and talking to you, so I'm sort of conscious. I'll be less conscious tonight when I'm sleeping, but more conscious this afternoon when my hangover wears off"		"Sure it does. When I get a 76% on a math test, I sort of understand that subject. If Turing meets 76% of the definitions of conscious, he's sort of conscious. I'm awake and talking to you, so I'm also sort of conscious. I'll be less conscious tonight when I'm sleeping, but more conscious this afternoon when my hangover wears off"

	The video of Freddie sharing a smile with ~~time~~ froze as Stan Ulam enthusiastically tapped the spacebar on a thin computer.		The video of Freddie sharing a smile with Tom froze as Stan Ulam enthusiastically tapped the spacebar on a thin computer.

	"We hired him shortly after that. Actually, you can see me right there in the corner with my phone. I was sending a message that we had to hire him then. He's continued working on Turing, he's got a whole team now. But we have a perception problem. We need a demonstration of the algorithms power - Deep Blue vs Kasperov, Watson on Jeopardy. We want to use Turing to write a show."		"We hired him shortly after that. Actually, you can see me right there in the corner with my phone. I was sending a message that we had to hire him then. He's continued working on Turing, he's got a whole team now. But we have a perception problem. We need a demonstration of the algorithms power - Deep Blue vs Kasperov, Watson on Jeopardy. We want to use Turing to write a show."

	[[Category:writing]]		[[Category:writing]]

Adamcolton: /* Story */

2016-03-09T16:47:55Z

Story

← Older revision		Revision as of 16:47, 9 March 2016
Line 35:		Line 35:
	One of scientists leaned forward and asked, "I'm not sure I follow, your dissertation is about 'Turing'. You have examples of nursery rhymes and children's stories it composed. You describe the algorithm."		One of scientists leaned forward and asked, "I'm not sure I follow, your dissertation is about 'Turing'. You have examples of nursery rhymes and children's stories it composed. You describe the algorithm."

	"Well, I started there. I fed it a corpus of every children's story I could find. And it produced stories that had plot, characters, even the prose was not bad. But they didn't fit together right. Most children's stories have a moral. Some point that the story is getting across. Without that it's just sort of a fever dream of princesses, dragons, knights and talking cutlery. That was the real challenge, giving Turing a goal ~~- make this~~ point. The essence of that algorithm - well, it's five algorithms and two data structures, are described in detail from pages 72 through 112. The next part isn't in the thesis though.		"Well, I started there. I fed it a corpus of every children's story I could find. And it produced stories that had plot, characters, even the prose was not bad. But they didn't fit together right. Most children's stories have a moral. Some point that the story is getting across. Without that it's just sort of a fever dream of princesses, dragons, knights and talking cutlery. That was the real challenge, giving Turing a goal, write a story with a specific point to it. The essence of that algorithm - well, it's five algorithms and two data structures, are described in detail from pages 72 through 112. The next part isn't in the thesis though.

	Once I had that, it turned out to be flexible. One time I gave it the instruction to produce a story whose moral was 'Always try a Monte Carlo simulation first', I was a bit frustrated at the time. But to my surprise, it used it's web crawler to pull in enough information to describe a Monte Carlo simulation. Sure, it was a talking badger explaining Monte Carlo to his friends and how his uncle used it to steal the kingdom that was his hereditary right. But it wasn't a bad summary. So I switch the corpus over thesuses (thesi? please somebody tell me what word to use here) and with a little tweaking I was producing pretty decent papers.		Once I had that, it turned out to be flexible. One time I gave it the instruction to produce a story whose moral was 'Always try a Monte Carlo simulation first', I was a bit frustrated at the time. But to my surprise, it used it's web crawler to pull in enough information to describe a Monte Carlo simulation. Sure, it was a talking badger explaining Monte Carlo to his friends and how his uncle used it to steal the kingdom that was his hereditary right. But it wasn't a bad summary. So I switch the corpus over thesuses (thesi? please somebody tell me what word to use here) and with a little tweaking I was producing pretty decent papers.

Adamcolton: /* Story */

2016-03-09T16:46:47Z

Story

← Older revision		Revision as of 16:46, 9 March 2016
Line 27:		Line 27:

	Before any of the panel had a chance to begin the inquiry, Freddie jumped into his defense.		Before any of the panel had a chance to begin the inquiry, Freddie jumped into his defense.
	"I'd like to start with two confessions. The ~~thesis (thesi?)~~ you have in front of you were not penned by hand. I was aided by a machine, I call it a 'printer'".		"I'd like to start with two confessions. The dissertation you have in front of you were not penned by hand. I was aided by a machine, I call it a 'printer'".

	Five of the six member were not amused. One was grinning and after jotting a few notes, started twirling a pen playfully.		Five of the six member were not amused. One was grinning and after jotting a few notes, started twirling a pen playfully.
Line 33:		Line 33:
	"The second confession is that the words were not penned by my mind. I was aided by a machine, I call it 'Turing'".		"The second confession is that the words were not penned by my mind. I was aided by a machine, I call it 'Turing'".

	One of scientists leaned forward and asked, "I'm not sure I follow, your ~~thesis~~ is about 'Turing'. You have examples of nursery rhymes and children's stories it composed."		One of scientists leaned forward and asked, "I'm not sure I follow, your dissertation is about 'Turing'. You have examples of nursery rhymes and children's stories it composed. You describe the algorithm."

	"Well, I started there. I fed it a corpus of every children's story I could find. And it produced stories that had plot, characters, even the prose was not bad. But they didn't fit together right. Most children's stories have a moral. Some point that the story is getting across. Without that it's just sort of a fever dream of princesses, dragons, knights and talking cutlery. That was the real challenge, giving Turing a goal - make this point. The essence of that algorithm - well, it's five algorithms and two data structures, are described in detail from pages 72 through 112. The next part isn't in the thesis though.		"Well, I started there. I fed it a corpus of every children's story I could find. And it produced stories that had plot, characters, even the prose was not bad. But they didn't fit together right. Most children's stories have a moral. Some point that the story is getting across. Without that it's just sort of a fever dream of princesses, dragons, knights and talking cutlery. That was the real challenge, giving Turing a goal - make this point. The essence of that algorithm - well, it's five algorithms and two data structures, are described in detail from pages 72 through 112. The next part isn't in the thesis though.

Adamcolton: /* Story */

2016-03-09T16:45:24Z

Story

← Older revision		Revision as of 16:45, 9 March 2016
Line 24:		Line 24:

	== Story ==		== Story ==
	Freddie Williams sat down in front of a panel of six. Five of the members were hard scientists. Or mathematicians. That was an eternal debate amongst them. But they all agreed the sixth member did not belong because he was the "old kook". Not that they would ever call him that outside their most guarded moments, calling Tom Kilburn, one of the most eminent philosophers, an old kook would be career suicide, even for an esteem professor of computer science. Even if all reputable computer scientists knew he was an old kook, it simply wasn't ~~done~~.		Freddie Williams sat down in front of a panel of six. Five of the members were hard scientists. Or mathematicians. That was an eternal debate amongst them. But they all agreed the sixth member did not belong because he was the "old kook". Not that they would ever call him that outside their most guarded moments, calling Tom Kilburn, one of the most eminent philosophers, an old kook would be career suicide, even for an esteem professor of computer science. Even if all reputable computer scientists knew he was an old kook, it simply wasn't said.

	Before any of the panel had a chance to begin the inquiry, Freddie jumped into his defense.		Before any of the panel had a chance to begin the inquiry, Freddie jumped into his defense.

Adamcolton at 16:44, 9 March 2016

2016-03-09T16:44:16Z

@@ Line 1: / Line 1: @@
 AI is used to write a TV show. Billed as a "Deep Blue" and "Watson" style challenge.
-== Characters ==
+== Notes ==
 * Owner of Netflix style movie service
-* Elon Musk style investor
+* Stan Ulam: Elon Musk style investor
-* Fred Williams: Created the core algorithm for his Ph.D at Carnagie Mellon
+* Freddie Williams: Created the core algorithm for his Ph.D at Carnagie Mellon
-== Plot Elements ==
+=== Plot Elements ===
 Conflict with writers union. This will end up tying back around as the AI being a tool. Cite the chess games after Deep Blue. Also hint of it being used in writing political speeches. And tailoring question and closing arguments for lawyers.
@@ Line 13: / Line 14: @@
 One of the episodes ends up getting a really bad review and there is a lot of debate over where the blame lies. The fact that it's not clearly with the script ends up being a strong argument for the AI.
-== Philosophical Elements ==
+=== Philosophical Elements ===
 A machine is just as "happy" doing what it was designed to do as a person is doing what they were "designed" to do.
@@ Line 22: / Line 23: @@
 The Musk character is seen by many as the face and therefor the creator. But as the project is unveiled to the public, he is adamant that he didn't build it, just saw the value and funded it. Focus shifts to Fred Williams, and he tries to explain that he developed the core algorithm, but it was only a variation on earlier algorithms and the real work was in tuning it and building the modules.
-[[Category:Writing]]
+== Story ==

Adamcolton: Created page with "AI is used to write a TV show. Billed as a "Deep Blue" and "Watson" style challenge. == Characters == * Owner of Netflix style movie service * Elon Musk style investor * Fred..."

2016-03-09T03:46:03Z

Created page with "AI is used to write a TV show. Billed as a "Deep Blue" and "Watson" style challenge. == Characters == * Owner of Netflix style movie service * Elon Musk style investor * Fred..."

New page

AI is used to write a TV show. Billed as a "Deep Blue" and "Watson" style challenge.

== Characters ==
* Owner of Netflix style movie service
* Elon Musk style investor
* Fred Williams: Created the core algorithm for his Ph.D at Carnagie Mellon

== Plot Elements ==
Conflict with writers union. This will end up tying back around as the AI being a tool. Cite the chess games after Deep Blue. Also hint of it being used in writing political speeches. And tailoring question and closing arguments for lawyers.

The show is a sci-fi show and ends up having the "robot betrays inventor" trope. Themes on children, ties back to Frankenstein.

One of the episodes ends up getting a really bad review and there is a lot of debate over where the blame lies. The fact that it's not clearly with the script ends up being a strong argument for the AI.

== Philosophical Elements ==
A machine is just as "happy" doing what it was designed to do as a person is doing what they were "designed" to do.

We don't lose control of our creations often, instead we lose control of people.

What is creativity? Is a person remixing the cultural elements they've learned more authentic than a machine doing it.

The Musk character is seen by many as the face and therefor the creator. But as the project is unveiled to the public, he is adamant that he didn't build it, just saw the value and funded it. Focus shifts to Fred Williams, and he tries to explain that he developed the core algorithm, but it was only a variation on earlier algorithms and the real work was in tuning it and building the modules.

[[Category:Writing]]