Artificial Artificial IntelligenceIntelligenceWhere it has been and where it Where it has been and where it should be goingshould be going

AI is conceived….(slowly)AI is conceived….(slowly)

66thth Century - First mention of any type of automata in Homer’s Century - First mention of any type of automata in Homer’s IliadIliad, with the mention of Hephaestus’, the God of Fire, workshop., with the mention of Hephaestus’, the God of Fire, workshop.

55thth Century- Aristotle codifies the first formal deductive reasoning Century- Aristotle codifies the first formal deductive reasoning system: Syllogistic logic.system: Syllogistic logic.

1515thth and 16 and 16thth Century- Mechanical clocks first appear in Europe. Century- Mechanical clocks first appear in Europe. 1642- Pascal invents the mechanical calculator, the “Pascaline.”1642- Pascal invents the mechanical calculator, the “Pascaline.” 1673- Leibniz improves upon Pascal’s calculator and envisions a 1673- Leibniz improves upon Pascal’s calculator and envisions a

“universal calculus of reasoning” to decide arguments “universal calculus of reasoning” to decide arguments mechanically.mechanically.

1919thth Century- AI in literature: Hoffman’s Century- AI in literature: Hoffman’s The SandmanThe Sandman, Goethe’s , Goethe’s FaustFaust, and Shelley’s , and Shelley’s FrankensteinFrankenstein..

AI is articulated… (sort AI is articulated… (sort of)of)

Babbage produces a small working model of Babbage produces a small working model of the Difference Engine and persuaded the the Difference Engine and persuaded the British government to finance a larger model.British government to finance a larger model.

Babbage couldn’t return what he promised.Babbage couldn’t return what he promised. Babbage ignores the Difference Engine in Babbage ignores the Difference Engine in

pursuit of the Analytical Engine, a machine that pursuit of the Analytical Engine, a machine that could do not only arithmetical calculations but could do not only arithmetical calculations but also analysis and reasoning. also analysis and reasoning.

The AI story continuesThe AI story continues

Ava Lovelace, Byron’s daughter, takes Ava Lovelace, Byron’s daughter, takes an interest in Babbage’s work. an interest in Babbage’s work.

1890- Herman Hollerith performs the US 1890- Herman Hollerith performs the US census using a machine that encoded census using a machine that encoded information using punch cards.information using punch cards.

1923- The term “robot” is introduced into 1923- The term “robot” is introduced into the English language in Karel Capek’s the English language in Karel Capek’s play, play, Rossum’s Universal RobotsRossum’s Universal Robots..

TuringTuring (this guy didn’t smile very (this guy didn’t smile very

often often so this pic was a find)so this pic was a find)

Turing Test: Any machine that could hold a Turing Test: Any machine that could hold a conversation with a person who cannot see conversation with a person who cannot see who he is talking and cannot distinguish who he is talking and cannot distinguish whether it is a machine or human is intelligent. whether it is a machine or human is intelligent.

Universal Machine: A machine that has the Universal Machine: A machine that has the ability to learn any number of tasks and ability to learn any number of tasks and perform them. (Humans are a universal perform them. (Humans are a universal machine or at least close enough.)machine or at least close enough.)

Intelligence comes from organization.Intelligence comes from organization.

CyberneticsCybernetics

Communication within both living being and machinesCommunication within both living being and machines Norbert Wiener says this is the source of intelligent behavior. Norbert Wiener says this is the source of intelligent behavior. This is obviously not a process limited to human beings and thus This is obviously not a process limited to human beings and thus

intelligence is not a characteristic limited humans. intelligence is not a characteristic limited humans.

John Von NeumannJohn Von Neumann(no luck on a smile from this guy)(no luck on a smile from this guy)

1942- Von Neumann comes to Princeton convinced 1942- Von Neumann comes to Princeton convinced that high-speed computing is the essential to the future that high-speed computing is the essential to the future of science and mathematics, and sets to work on the of science and mathematics, and sets to work on the design of the IAS machine.design of the IAS machine.

The IAS’s predecessors, ENIAC and EDVAC, were The IAS’s predecessors, ENIAC and EDVAC, were designed for specific tasks (nautical and bombing designed for specific tasks (nautical and bombing tables). The IAS could be manipulated to solve a wide tables). The IAS could be manipulated to solve a wide class of problems if only they were input properly.class of problems if only they were input properly.

1951- “anything that can be completely and 1951- “anything that can be completely and unambiguously described , anything that can be unambiguously described , anything that can be unambiguously put into words is ipso facto realizable unambiguously put into words is ipso facto realizable by a suitable finite neural network.”by a suitable finite neural network.”

The Dartmouth ConferenceThe Dartmouth Conference(Dartmouth College… artists rendering)(Dartmouth College… artists rendering)

The term “artificial intelligence” is The term “artificial intelligence” is adopted, to the chagrin of many of those adopted, to the chagrin of many of those presentpresent

McCarthy proposed the idea of a programming McCarthy proposed the idea of a programming language for use in problems requiring language for use in problems requiring conjecture and self-reference.conjecture and self-reference.

“ “We are a long way from even knowing what We are a long way from even knowing what questions to ask or what aspects to abstract for questions to ask or what aspects to abstract for theory. The present need is for a large theory. The present need is for a large population of concrete systems that are population of concrete systems that are completely understood…”completely understood…”

The Information-The Information-Processing ModelProcessing Model

Redefine the computer as an information Redefine the computer as an information processor not a calculating machine. processor not a calculating machine.

symbolic-functioning capabilitiessymbolic-functioning capabilities of of computers. computers.

a symbol is something that could stand a symbol is something that could stand for an object and its meaning, its uses, for an object and its meaning, its uses, and all other pertinent information about and all other pertinent information about it.it.

GamesGames kerplunk ->kerplunk ->

<- obvious<- obvious

The games computers played at first were the ones that were The games computers played at first were the ones that were most interesting from a computational standpoint: chess and most interesting from a computational standpoint: chess and checkers.checkers.

Samuel considered a different approach, instead of imitating a Samuel considered a different approach, instead of imitating a human thought process he wanted to enlist a new thought human thought process he wanted to enlist a new thought process all together.process all together.

““I think you study the way people solve problems to get an insight I think you study the way people solve problems to get an insight into what the real problem is…And then you sit down and say, into what the real problem is…And then you sit down and say, ‘Okay, given the technology available…how best can we solve the ‘Okay, given the technology available…how best can we solve the problem?”problem?”

““The machine, therefore, played a perfect ending without one The machine, therefore, played a perfect ending without one misstep. In the matter of the end game, I have not had such misstep. In the matter of the end game, I have not had such competition from any human being since 1954, when I lost my last competition from any human being since 1954, when I lost my last game.”game.”

The Game: ChessThe Game: Chess

Other programs of the day took advantage of the speed of the Other programs of the day took advantage of the speed of the computer processor, using it to search the field of possible board computer processor, using it to search the field of possible board configurations after each of its various possible moves and then configurations after each of its various possible moves and then choosing the optimal configuration. choosing the optimal configuration.

““if all you have is a machine that bests humans by means of if all you have is a machine that bests humans by means of speed alone, what really do you have?”speed alone, what really do you have?”

Economizing search strategies among a set of possibilities has Economizing search strategies among a set of possibilities has proven a key element in Artificial Intelligence to date.proven a key element in Artificial Intelligence to date.

Although we cannot mimic bird flight, we can still fly anywhere we Although we cannot mimic bird flight, we can still fly anywhere we want.want.

Side Note: In 1997 IBM’s Deep Blue defeated Garry Kasparov, the Side Note: In 1997 IBM’s Deep Blue defeated Garry Kasparov, the world’s reigning chess champion at that time.world’s reigning chess champion at that time.

Vs.

Pseudo-Intelligent Pseudo-Intelligent SystemsSystems (Cyrus Whitney far cooler than (Cyrus Whitney far cooler than

either of the two listed below)either of the two listed below)

PARRY – Imitated a paranoid patient and was PARRY – Imitated a paranoid patient and was made to be interviewed by psychiatristsmade to be interviewed by psychiatrists

PROSPECTOR – Analyzes geologic data and PROSPECTOR – Analyzes geologic data and makes interpretations and predictions. makes interpretations and predictions.

LUNAR – Contained a wealth of information LUNAR – Contained a wealth of information about moon rocks and was able to answer about moon rocks and was able to answer questions about them written in plain Englishquestions about them written in plain English

CYRUS – Was fed news articles about CYRUS – Was fed news articles about Secretary of State Cyrus Vance and was able Secretary of State Cyrus Vance and was able to be interviewed as if it were him. to be interviewed as if it were him.

They All Fall ShortThey All Fall Short

While impressive these systems only While impressive these systems only manage to simulate a small range of manage to simulate a small range of thinking.thinking.

None of them are able to provide any None of them are able to provide any meaning to the data they present. meaning to the data they present.

Still a long way from Turing’s Universal Still a long way from Turing’s Universal machine.machine.

<- Yao Ming

Ryan Foss->

RoboticsRobotics

In the late 1960s three major robotics projects got started in the In the late 1960s three major robotics projects got started in the United States. Each project had its own particular flavor but the United States. Each project had its own particular flavor but the general idea was to create some sort of independent thinking, general idea was to create some sort of independent thinking, interacting, machine. interacting, machine.

Robotics (a term coined by Isaac Asimov) was the practical Robotics (a term coined by Isaac Asimov) was the practical application of AI, and it ended up having a significant impact on application of AI, and it ended up having a significant impact on the theory.the theory.

Requirements for AI were rewritten, and a system now had to be Requirements for AI were rewritten, and a system now had to be able to demonstrate that it had an internal model of the world, be able to demonstrate that it had an internal model of the world, be clever enough to answer questions on a wide range of topics clever enough to answer questions on a wide range of topics (analytical and common), acquire information from the external (analytical and common), acquire information from the external world and update its model, and adhere to some goals within its world and update its model, and adhere to some goals within its range of physical limitation.range of physical limitation.

This new definition posed 3 major problems: How to incorporate This new definition posed 3 major problems: How to incorporate and generalize observations, how to represent non-physical real and generalize observations, how to represent non-physical real world data (say emotions), how to get knowledge about the world.world data (say emotions), how to get knowledge about the world.

Isaac Asimov this guy wrote a lot of stories about robots… but never met one

LanguageLanguage

One of the most obvious applications of a One of the most obvious applications of a narrowly defined/capable AI system is narrowly defined/capable AI system is interpreting one language into another. “The interpreting one language into another. “The pen is in the box.”pen is in the box.”

““The box is in the pen.”The box is in the pen.” AI therefore cannot be simply a information-AI therefore cannot be simply a information-

retrieval system, rather it must be something retrieval system, rather it must be something more like question-answering system that not more like question-answering system that not only processes data but also amends and only processes data but also amends and draws inferences from the input.draws inferences from the input.

Sorry no clever pictures for this slide

Applied AI Applied AI

DENDRAL- chemist’s assistant in interpreting DENDRAL- chemist’s assistant in interpreting the data from mass spectrography that the data from mass spectrography that operates at the level of a Chemistry Ph.D.operates at the level of a Chemistry Ph.D.

MACSYMA- mathematician's assistant that MACSYMA- mathematician's assistant that works faster than humans in manipulating works faster than humans in manipulating many types of algebraic expressions. many types of algebraic expressions.

There is also the Sussman and Stallman There is also the Sussman and Stallman program for understanding electronic circuits.program for understanding electronic circuits.

And many groups have dedicated their work to And many groups have dedicated their work to producing systems to aid doctors in all types of producing systems to aid doctors in all types of medical diagnosis.medical diagnosis.

Recent Attempts At AIRecent Attempts At AI

Temporal Difference – TD-GammonTemporal Difference – TD-Gammon A new approach to gamingA new approach to gaming Rather than play out the game ahead of Rather than play out the game ahead of

time, creates a set of goals with different time, creates a set of goals with different weights that are adjusted each time it playsweights that are adjusted each time it plays

Capable of competing with the best players Capable of competing with the best players in the world and even creating new in the world and even creating new strategies of its ownstrategies of its own

More Recent AI More Recent AI DevelopmentsDevelopments

Decision TreesDecision Trees Form of classificationForm of classification Consecutive tests of input properties guide data Consecutive tests of input properties guide data

toward correct leaves, or create new classes when toward correct leaves, or create new classes when necessarynecessary

Learning to ReasonLearning to Reason Similar to Turing’s idea that intelligent systems can Similar to Turing’s idea that intelligent systems can

mimic human developmentmimic human development Program is given a period to observe an Program is given a period to observe an

environment then expected to carry out inductive environment then expected to carry out inductive reasoning about that environment effectively. reasoning about that environment effectively.

Slacking off on the pictures

Where is AI going?Where is AI going?

Frederick Brooks: “The quantification of information Frederick Brooks: “The quantification of information embodies in structure.”embodies in structure.”

Jim Gray (Microsoft): “We have been handed a puzzle: Jim Gray (Microsoft): “We have been handed a puzzle: genomes and brains work. They use much more genomes and brains work. They use much more compact programming languages than we do.”compact programming languages than we do.”

Butlery Lampson: cars that don’t kill people and Butlery Lampson: cars that don’t kill people and automatic programming (programs that write other automatic programming (programs that write other programs).programs).

John McCarthy: computer programs with at least the John McCarthy: computer programs with at least the intellectual capabilities of humansintellectual capabilities of humans

Raj Reddy: “a computer that could read a chapter in a Raj Reddy: “a computer that could read a chapter in a book and answer the question at the end of the book and answer the question at the end of the chapter.”chapter.”

The Feigenbaum TestThe Feigenbaum Test

Similar to the Turing Test. Similar to the Turing Test. Perhaps a better challenge proposed by Feigenbaum is Perhaps a better challenge proposed by Feigenbaum is

as follows: manually program a novice view of a given as follows: manually program a novice view of a given domain, write software for the system that will read the domain, write software for the system that will read the next level in the field, augmenting new material with next level in the field, augmenting new material with that it already mastered. Allow the system to ask that it already mastered. Allow the system to ask questions, and answer dutifully. If absolutely questions, and answer dutifully. If absolutely necessary, direct intervention is permissible (i.e. hard-necessary, direct intervention is permissible (i.e. hard-code the new rules) though in no more than 10 percent code the new rules) though in no more than 10 percent of the new material. of the new material.

If the computational machine is capable of keeping up If the computational machine is capable of keeping up with the material such that it can pass subsequent with the material such that it can pass subsequent Feigenbaum tests then AI has been achieved.Feigenbaum tests then AI has been achieved.

What AI isn’t (our opinion)

• AI is not deterministic• AI isn’t an optimizing system.• AI isn’t a classification program.• AI isn’t a vast search of a problem

space.• AI doesn’t necessarily have to be human intelligence.

What AI is (or might be, we really aren’t sure)• AI is a system that understands the

information it processes• AI is a system that learns• AI is a system that can interact and

manipulate its environment• AI has initiative• AI can always respond even when the stimuli is

outside of its experience or internalized model of the world. (i.e. the response can be no response, the response cannot be the program crashing)