Learning Goals [revisited] Connecting with Computer Science. What is a Computer? Revisited. What is a Computer? Revisited. Minds and Machines

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1 Connecting with Computer Science Module V: Minds and Machines Part 3: Can Machines Think? Revisited Learning Goals [revisited] you should be able to categorize a well-described device as a computer or non-computer with clear, articulate reference to a given definition make strong and articulate arguments for and against the intelligence of proposed systems in your own words but appealing to the ideas laid out by Turing, Searle, Hawkins & Blakelee, and Aamodt & Wang What is a Computer? Revisited recall learning goal from first class: categorize a well-described device as a computer or non-computer with clear, articulate reference to a given definition we provided definitions on the first day of class and classified devices as computer or non-computer let s reconsider three of those definitions now, and classify some devices What is a Computer? Revisited a computer is a device (or collection of devices) that can do massive calculations, has electronic components and can store and process data store data and interpret given instructions to perform some process in the world use prior calculations or procedures to determine future calculations or procedures question: how would you interpret the words processes, instructions and procedures?

2 From your RQ13s: Is the ability to predict based on memory always a good indication of intelligence because sometimes it is hard for even human to predict in advance? We can use computers to predict, for example, weather. Does it mean computers are more intelligent in this example? (submitted by Siyue) A Yes B - No Analytical Engine Designed ca by Charles Babbage A machine which would have received instructions from punchcards pieces of paper with holes punched in them in special patterns. The machine would perform calculations described by the holes using steam-powered gears and cogs. Results of previous calculations could control what calculations l it performed next. Finally, it would print its results. ENIAC Developed in 1944 by Mauchly, Eckert et al. An electronic device which used vacuum tubes, electrical relays and other components to perform calculations. Operators wired together some of ENIAC s electrical devices to represent the commands it should execute. It then executed those commands, performing literally thousands of additions in a single second. It could not decide what commands to execute next based on the results of previous calculations. The Human Brain Developer/development year disputed; ca BC? The human brain is a large organ situated in the skull of the modern human. Capable of a wide range of tasks from mathematical calculations to identifying Jelly Bean flavors, the human brain coordinates most functions of its associated human. It receives sensory information from many devices (eyes, ears, toes, etc.) and also controls devices that act in the world (hands, voice box, toes, etc.). The structure of the human brain consists of a massive network of interconnected neurons interacting through chemical and electric processes.

3 The Domestic Cat Domesticated ca BC in Egypt What is a Computer? Clicker Poll A: computer B: non-computer A four-legged creature with a tail, covered in fur and possessed of retractable claws. Cats pretty much do whatever they want. Physically, the domestic cat weighs between about 2.5 and 10kg. computer definition analytical ENIAC cat human engine brain 1. do massive calculations, has electronic components and can store and process data 2. store data and interpret given instructions to perform some process in the world 3. use prior calculations or procedures to determine future calculations or procedures What is a Computer? Clicker Poll A: computer B: non-computer computer definition analytical ENIAC cat human engine brain 1. do massive calculations, has electronic components and can store and process data B B B 2. store data and interpret given instructions to perform A A? A? some process in the world B? B? 3. use prior calculations or procedures to determine future calculations or procedures A B A? B? A? B? Computer or Not, Using Definition 3 sample answer I would characterize a cat as a computer according to definition 3 because a cat can make complex calculations based on prior calculations. For example, a cat can calculate the amount of effort to expend in order to land seamlessly on the top of a high wall it has not encountered before and can recognize a dog from a cat. The computations underlying such actions are truly complex, going well beyond the capabilities of state-of-the-art machines today. A cat builds up knowledge of its world through play and exploration and uses this knowledge to make later predictions. A cat has a brain with hundreds of millions of neurons and thus billions of synapses comparable with the number of gates and connections of today s computers. Cats are therefore capable of calculations on a massive scale and use their computational capabilities in sophisticated ways.

4 Computer or Not, Using Definition 3 sample answer I would characterize a cat as a non-computer according to definition 3. A cat is capable of a limited range of calculations and procedures and most of them (such as recognizing the sound of a bird) are innate, i.e., not learned from prior calculations. For example, it is next to impossible to retrain a cat when it has decided that your quilt is a litter box you can make the cat go through the procedure of using the proper litter box as much as you want but as soon as you leave your bedroom door open it will revert to its old bad habit. A cat cannot do basic addition, recognize itself in the mirror, or myriad other tasks that we would expect of a general-purpose computer that can use prior calculations or procedures to determine future calculations or procedures. The domestic cat is an unpredictable creature. Can Machines Think? Revisited Hawkins and Blakelee (2004) bring new ideas about brain function to bear on this question ideas about what is understanding ideas about what is intelligence their ideas tie in beautifully with our (your) third definition of a computer Exercise: Do one of the following: Provide a definition of what is understanding based on pp of the reading by Hawkins and Blakeslee. Do you think that understanding, by this definition, could be achieved via symbol manipulation? Provide a definition of an intelligent system based on pp of the reading by Hawkins and Blakeslee. How does this definition differ from that of Turing as captured by the Turing Test? Is Chinook Intelligent? apply your new definitions A computer program, Chinook, beats the world's champion checkers player (Dr. Marion Tinsley), a person who had, in the past, beaten dozens of strong human players simultaneously, playing multiple games at once. Checkers commentators point out clever traps that the machine set and a surprising mistake that the human player made leading up to the loss. Is Chinook intelligent? Does Chinook understand? Use your definitions derived from Hawkins and Blakelee

5 Can Machines Think? Revisited Hawkins and Blakeslee are optimistic about the possibility of intelligent machines Aamodt and Wang are skeptical; they describe gaps between capabilities of computer and brain that will pose daunting technical challenges to the goal of building intelligent machines See: Sandra Aamodt and Sam Wang, Computers vs Brains judson.blogs.nytimes.com/2009/03/31/guest-column-computers-vs-brains Can Machines Think? Revisited Homework (exam-relevant!): Read Sandra Aamodt and Sam Wang, Computers vs Brains, judson.blogs.nytimes.com/2009/03/31/guest- nytimes column-computers-vs-brains Note: Aamodt and Wang are skeptical; they describe gaps between capabilities of computer and brain that will pose daunting technical challenges to the goal of building intelligent machines Neuron Neural Network neurons are like gates Neuron Neural Network neurons form networks dendrites receive inputs axons carries output output is a simple function of the input

6 Circuits vs Neural Networks memory capacity Circuits vs Neural Networks power consumption digital circuits the entire archived contents of the Internet fill just three petabytes (a million gigabytes) the brain s neural networks one cubic centimeter of human brain tissue contains 50 million neurons; several hundred miles of axons and close to a trillion synapses say a petabyte of information digital circuits the brain s neural networks by 2025, the memory use about 12 watts, an amount that of an artificial brain supports not only memory but all would use nearly a thought processes less than the gigawatt of power, energy consumed by a typical the amount currently refrigerator light consumed by all of Washington, D.C. Circuits vs Neural Networks decision-making algorithms digital circuits process information in precisely repeatable ways execute instructions provided as a high- level l program wiring doesn t change over time the brain s neural networks make approximations and find good-enough solutions use emotions to assign value to experiences, often enabling efficient evaluation of potential outcomes when information is uncertain wiring changes over time, enabling learning In Closing: Why Build Intelligent Machines? As neuroscientists, we re excited about the potential of using computational models to test our understanding of how the brain works. On the other hand, although it eventually may be possible to design sophisticated computing devices that imitate what we do, the capability to make such a device is already here. All you need is a fertile man and woman with the resources to nurture their child to adulthood. With luck, by 2030 you ll have a full-grown, college-educated, walking petabyte. A drawback is that it may be difficult to get this computing device to do what you ask. Sandra Aamodt and Sam Wang