Category: Timeline Stories

At the beginning of 1956, two young Cambridge scientists, the psychologist Gordon Pask (1928-1996) and physicist Robin McKinnon-Wood (1931-1995), created a hybrid teaching and learning analog computer, in response to a request by the Solartron Electronic Group for a machine to exhibit at the Physical Society Exhibition in London.

Gordon Pask was an English scientist, designer, researcher, academic, playwright, and one of the early proponents and practitioners of cybernetics, the study of control and communication in goal-driven systems of animals and machines. Originally trained as a mining engineer, he went on to complete his doctorate in psychology. His particular contribution was a formulation of second-order cybernetics as a framework that accounts for observers, conversations, and participants in cybernetic systems.

The operation of the machine, called Eucrates (after the archon of ancient Athens from the 6^th century BC, who was famed for neglect and excuses) was based on simulating the functioning of neurons. It was an embodiment of a conversation between machines, where one machine literally “teaches” the other. Let’s see the description of Eucrates, which appeared in the Monday, 4 June 1956, issue of TIME Magazine, London.

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A schoolteacher who is tireless, vigilant and indifferent to big red apples was on exhibit at London’s Physical Society. The teacher is electronic and the creation of two young Cambridge scientists, Physicist McKinnon-Wood and Psychologist Gordon Pask, under contract with Solartron Electronic Group Ltd. Designed for teaching such routine skills as typing and running radar equipment, the electronic teacher gives patient, individual attention.

The trouble with human teachers, say Wood and Pask, is that unless they are extremely good, they cannot observe in detail the intimate characteristics of each pupil. Each pupil’s biases, habits and individual eccentricities determine how he should be taught. He may favor his left hand over his right hand, or be able to remember odd numbers better than even ones. An ideal teacher should take all such matters into account and teach accordingly.

Solartron’s electronic teacher is set up to teach how to duplicate patterns of light in a frame containing eight lights. It starts the lessons by showing a single light. In another frame another light appears, telling the pupil which button to press. After a few such easy examples, the lessons get harder. Light patterns can be duplicated only by complicated operations with the buttons. The teacher gives clues, tells the pupil whether he is doing well or badly and makes him repeat over and over if he is making errors. Always understanding, the machine holds back a difficult exercise until the pupil is ready. If set up to teach typing, it can tell the pupil which finger to use and in which direction to move it. If the pupil is a hardened hunt-and-peck typist, the teacher will discover his sloppy habits and set about correcting them at once.

Wood and Pask got so interested in the teaching problem that they created an electronic pupil named Eucrates I, to give the electronic teacher a real workout. Eucrates is electronic but not bright. When not being taught, he is “thinking” in a confused way, and the electronic teacher must take account of his thinking habits. Eucrates follows instructions and observes clues, but is often wrong. If the teacher is too severe or goes too fast, Eucrates shows signs of electronic emotion, equivalent to bursting into tears. Then the electronic teacher is gentle with him until his little dials have stopped quivering.

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Later in 1956, Park and Wood invented Self-Adaptive Keyboard Instructor (SAKI), a machine, that adapts to the learner’s performance level (it was essentially a system for teaching people how to increase speed and accuracy in typing alphabetic and numeric symbols using a 12-key keyboard.) In late 1956, Park and Wood also created an improved version of Eucrates, called (surprise!) Solartron EUCRATES II.

In his book “An Approach to Cybernetics” (1961) Gordon Pask presents “learning machines”. Pask designates “Eucrates” as “simulating a pupil-teacher system”. The model reconstructs the behavior of “real neurons” and their “absolute refractory period”. The reactions of the “motor-elements” to the input are varying because of a shifting threshold: The threshold increases after the first input with the consequence for learners that they have to wait with further inputs until the threshold falls. “Memory-elements” react to the output of the “motor-elements”. The “memory-elements” are constructed following the example of “the synaptic connections of a neuron”: “Now it is obvious that various modes of activity and various forms of interaction [between a pupil and a teacher or the learning machine] will build up the network.” Pask writes this sentence after a short explanation of possible “interconnections” between “motor-elements” and the learning activities within the “network”. Capable of surviving within the “network” are only the connections that “mediate a favorable behavior”.

With the complex adding systems that we have today, it can be hard to grasp that people were using small stones or other objects as numerical devices from time immemorial. The word calculate itself comes from the Latin calculus, which means small stone. These methods of calculations introduced some elementary kind of abstraction, but people gradually realized that this method did not go far enough to satisfy their increasing needs. To count up to 1000, for example, they would have had to gather a thousand pebbles, which was enormous work.

That is why, once the principle of the numerical base had been grasped, the usual pebbles were replaced with stones of various sizes to which different orders of units were assigned. For example, if a decimal system was used, the number 1 could be represented by a small stone, 10 by a larger one, 100 by a still larger one, and so on. It was a matter of time before someone thought of arranging some pebbles over a big flat base stone, wire, or something else.

It is unknown when exactly were developed first devices to facilitate calculation, such as the counting board, or abacus. The counting board was invented when someone grasped the idea of placing pebbles or other objects in columns marked on a flat surface and assigning an order of units to the objects in each column. Later, loose objects in columns were replaced with beads that could slide along parallel rods.

There is unproved information, that a similar to the abacus device was used in Babylonia as early as 2400 BC. The word abacus itself is a Latin word, that comes from Greek άβακασ (board or table). The Greek word probably comes from the Semitic abk, which means sand, dust or to wipe the dust, which can suggest to us, that Greeks accepted the idea of an abacus from the Phoenicians (which is the case with the Greek alphabet, inspired by the Phoenician alphabet). Actually, the Romans applied the word abacus (and also the word calculi, which comes from calculus (stone, pebble) to various objects, all with the common characteristic of having a flat surface: tables used in different kinds of games, sideboards and the calculating device still known as the abacus. The Greeks used besides the above-mentioned type of abacus, also so-called dust abacus—a box, full of sand (or dust), divided into columns, over which can be arranged pebbles or other small objects.

The first written information about the abacus that survived to the present, is from the Greek historian Herodotus (480-425 B.C.), who mentioned also, that the ancient Egyptians used abacus. The oldest abacus, which survived to the present day, is the so-called Salamis abacus (see the nearby figure). It was named after the Greek island of Salamis, in the vicinity of which it was found in 1846 and was described later by the Greek archaeologist Alexander Rizo-Rangabe.

The Salamis abacus (kept now in the Epigraphical Museum of Athens) is dated around 300 B.C. and is a large slab of white marble (broken in half now), 149 cm long and 75 cm wide, with five parallel lines engraved into it and, below them, eleven parallel lines divided in half by a perpendicular line. The third, sixth, and ninth of these eleven lines are marked by crosses at their points of intersection with the perpendicular line. Three nearly identical series of Greek characters, which are numerical signs for noting sums of money in the Greek monetary system (the basic unit is drachma, but there are also 2 smaller units—obols and khalkoses, and 2 bigger, which actually were never minted—minas and talents), are engraved on three sides of the slab.

The four columns on the top were used for fractions of the drachma, the first one corresponding to khalkoses (1/48 of a drachma), the second to quarter-obols (1/24 of a drachma), the third to half-obols (1/12 of a drachma), and the fourth to obols (1/6 of a drachma). The next five columns were associated with multiples of the drachma: the first on the right corresponded to units, the second to tens, the third to hundreds, and so on. The last five columns (in the bottom part) were respectively associated with talents, tens of talents, hundreds, and so on. Since a talent was equivalent to 6000 drachmas, counters representing 6000 drachmas were replaced with one counter in the talents column. By means of these different divisions, the reckoner could perform addition, subtraction, and multiplication.

There is also another interesting old Greek artifact, the so-called Darius Vase, dated about 500 B.C., in the museum at Naples, which contains a picture of an abacus-like instrument (see the nearby drawing).

Pictures (but not an artifact yet) of a Roman table abacus were found on an Etruscan cameo, on a Roman pier, and on a relief of the Capitoline Museum in Rome.

The Roman abacus was similar to the Greek one (see the nearby photo). It consisted of a small metal tablet with parallel grooves, usually nine of them, each corresponding to an order of units, in which spherical counters slid. The abacus in the upper figure has 8 decimal positions (leftmost), for the units, tens, hundreds, and so on to the 100 millions (marked with I, X, C…). When the units of a certain order did not go beyond four, the reckoner indicated them in the corresponding lower groove by pushing up as many counters as necessary. When they reached or went beyond five, he first pushed down the counter in the upper groove (representing five units in the order of that groove), then pushed up as many counters as necessary in the lower groove. The ninth position from the left (marked with O) has an upper part containing one counter and a lower part containing five. It served to indicate multiples of an ounce, each lower counter representing one ounce and the upper counter six ounces. The rightmost groove is divided into 3 parts and is used to indicate a half-ounce, a quarter-ounce, and a duella, or a third of an ounce.

During the so-called Dark Ages in Western Europe, the art of counting with the abacus was more or less forgotten. One of the first scientists, who not only popularized the Hindu-Arabic digits but also reintroduced the abacus, was (surprise!) Gerbert d’Aurillac (c. 946-1003), archbishop of Rheims and chancellor of France, well-known as Pope Sylvester II (see the nearby image). Gerbert lived some time in Spain and took the idea of the abacus from Spanish Arabs (in 967, he went to Catalonia to visit the Count of Barcelona, and remained three years in the monastery of Vic, which, like all Catalan Monasteries, contained manuscripts from Muslim Spain and especially from Cordoba, one of the intellectual centers of Europe at that time). The abacus that Gerbert reintroduced into Europe had its length divided into 27 parts with 9 number jetons, so-called apices (this would exclude zero, which was represented by an empty column) and 1000 apices in all, crafted out of animal horn by a shieldmaker of Rheims. For example, with Gerbert’s abacus, the number 308 will be expressed with an apex for 3 in the hundreds column and with an apex for 8 in the column of units. According to his pupil Richer, Gerbert could perform speedy calculations with his abacus, which were extremely difficult for people in his day to think through in using only Roman numerals, that was one of the reasons Gerbert was suspected as a magician and servant of the Devil 🙂 Due to Gerbert’s reintroduction, the abacus became widely used in Western Europe once again during the 11^th century.

The first printed book on arithmetic and the operation of the abacus in Europe was the anonymous Arte dell’Abbaco, (Treviso, 1478). The most popular kind of abacus still in use during the Renaissance in Europe was a table on which lines marked off the different decimal orders (so-called reckoning table). The pebbles previously used as counters have been replaced by specially minted coin-like objects (like apices, introduced by Gerbert) that are cast, thrown, or pushed on the abacus table. They are called jetons from jeter (to throw) in France and werpgeld for “thrown money” in Holland. All administrations, merchants, bankers, lords, and rulers had reckoning tables with counters bearing their own marks, made of base metal, gold, or silver, depending on their rank or social position.

The value of a counter depended on its position. On consecutive lines, going from bottom to top, it was worth 1, 10, 100, 1000, and so on. Between two consecutive lines, it was worth five units of the line immediately below it. Addition was done in the left (or forward) part of the frame, by placing counters corresponding to the numbers involved, then reducing them and taking account of the value assigned to each location. To multiply two numbers, the reckoner began by representing the first one in the left part of the frame, then he eliminated one by one the counters representing this number as he replaced them in the right (or rear) part of the frame with their products by the second number. Computation on the reckoning table was taught till the eighteenth century. The fact that it was discussed in many European arithmetic books in the sixteenth, seventeenth, and eighteenth centuries gives an idea of how common it was. It was so firmly anchored in European tradition, that even when written computation with Hindu-Arabic numerals was becoming general, results obtained in that way were always checked on a reckoning table, just to be sure.

The reckoning table made addition and subtraction easy, but for more complex operations it was slow and required long training. This drawback must have been what prompted the fierce controversy that began early in the sixteenth century between the abacists, who clung to the reckoning table and the archaic Greek and Roman numerations, and the algorists, who advocated a form of written computation (see the nearby figure). Written computation was quickly adopted by scientists (especially by mathematicians and astronomers), while the reckoning table continued to be used in business and finance.

A quite different and much more advanced form and methods for calculation can be seen in the development of the abacus in Asia. The Chinese started to use counting boards, the prototype of the abacus, as early as the 4^th century BC. The Chinese counting board was a wooden plate, divided into columns, and calculations were made by means of bamboo or ivory sticks (see the nearby figure for the two ways of representation of digits). In the rightmost column are denoted units, in the next—tens, and so on. Some historians even claim, that this namely was the first use of the decimal numbering system in the world. The most famous Chinese mathematical text—Chiu chang suan shu (Nine Chapters on the Mathematical Art), which dates from the period of the Han Dynasty (206 B.C. to A.D. 220), gives details of algebraic operations on the counting board, including the solution of a system of n equations with n unknowns.

The long and gradual improvement of the Chinese counting board led to the development (sometimes in the 2^nd century) of a more convenient type of abacus—the bead abacus, mentioned in the book of Xu Yue, Supplementary Notes on the Art of Figures, written about the year 190 A. D. The Chinese bead abacus (so-called suanpan) has a rectangular wooden frame with thin rods across it. On each rod are placed seven glass or wooden beads: five (the number of fingers of a human) below the strip of wood, that divides the frame into two unequal parts, and two above it (the number of hands).

The rods correspond to numerical values increasing tenfold from right to left. (Base 10 is not obligatory, of course; another base, such as 12 or 20, could be used if an adequate number of beads were placed on the rods.) If the first rod on the right corresponds to units, the second one corresponds to tens, the third to hundreds, and so on. Users of the suanpan, however, do not always begin with the first rod on the right to represent whole numbers: they sometimes begin with the third from the right, reserving the first two for centesimal and decimal fractions.

Each of the five beads on the lower part of a rod has the value of one unit of the order corresponding to the rod, and each of the two beads on the upper part has the value of five units. Numbers are formed by moving beads toward the crossbar separating the upper and lower parts of the rods. To form the number four, for example, the user simply raises four beads on the lower part of the first rod on the right. For eight, he lowers one upper bead on that rod and raises three lower ones.

As can be seen, there is some kind of redundancy in the notation of numbers in suanpan. Nine units of the order corresponding to a given rod are represented by one upper bead with the value of five units and four lower beads with the value of one unit each. Five beads are thus enough to represent nine units. This raises the question of why each rod has seven beads, which allowed a total value of 15 to be entered. The reason is that in doing division on an abacus, it is often helpful to indicate, temporarily, a number greater than 9 on a single rod. For the three other operations, five beads on each rod are enough. In the case of division, however, the calculation may be simplified if a partial result greater than 9 is temporarily indicated on one rod.

Sometime in the late 16^th century, the Chinese suanpan was adopted in Japan, under the name soroban. The soroban however was gradually simplified, and from the middle of the 17^th century, the number of beads in the lower part was reduced to 4, while in the upper part remained only 1 bead. This means, that the redundancy of the suanpan was removed, due to the fact, that the older Chinese division method, which makes use of the cumbersome division table, was formerly replaced by the Japanese division method, which makes use of the multiplication table.

Another country, in which the bead abacus was extremely popular, apart from China and Japan, at least in recent times, is Russia. The Russian abacus, so-called русские счёты (russkie schoty) (see the nearby photo) was first mentioned in 1658, in an inventory book. The construction of schoty probably was based on the Chinese suanpan, but was quite different in the design. The main difference between suanpan and schoty is the horizontal position of the rods in the schoty (so the beads are slid right-to-left), and the rods have a slight curvature to prevent the “counted” beads from accidentally sliding back to the home position. The typical schoty has several (usually 8 to 10) decimal positions, and 1 position with 4 beads (which not only acts as a separator or for fractions, but can be also used for calculations in polushki, the Russian monetary system in this time was constituted by polushki, kopeiki (1 kopeika equal to 4 polushki), and roubles (1 roubla equal to 100 kopeiki)).

The Russian abacus has some improved variants, like Markov’s abacus (счетьi Маркова), double abacus (двойньiе счетьi), Ezerski’s abacus (счетьi Езерскаго), Kompaneiski’s abacus (счетьi Компанейскаго), etc.

The Russian abacus is still in common use today in shops and markets throughout the former Soviet Union, although it is no longer taught in most schools. Around 1820, the Russkie schoty was brought to Europe (first to France, under the name boulier-compteur), though not as a calculating device, but rather as a didactic tool for beginning course of arithmetic.

American Indians also used calculating tools. At the beginning of the 1600s, the Quechua nobleman Felipe Guaman Poma de Ayala wrote a letter to the King of Spain, containing 1179 pages. The letter includes several drawings that show quipus (recording devices used in the region of Andean South America, consisting of colored, spun, and plied thread or strings) and a picture of a counting board in the bottom left-hand corner of one of them (see the nearby picture). This is called the yupana and is presumed to be the counting board of the Incas.

In 1895 three of the mechanics, who worked in the factory of Arthur Burkhardt in Glashütte—Ernst Eduard Zeibig (1856-1944), Friedrich Eugin Straßberger (1857-1945), who started with Curt Dietzschold in 1878, and Josef Schumann (1862-1913), who was a foreman in the factory, decided to leave and to found a new factory for calculating machines—Rechenmaschinen-Fabrik “Saxonia” Schumann & Cie (there was an anonymous donor who believed in the entrepreneurial spirit of the three mechanics because they had no money to start a company.)

In this factory was produced the successful calculating machine Saxonia. Schumann left the company in 1912 (probably due to poor health because he died the next year), but the founders Zeibig & Straßberger continued to run the company together. Later on in 1920, the factory Saxonia merged with Burkhardt’s factory, and the newly joined company United Glashütte Rechenmaschinenfabriken was opened. It will continue production up to March 1929 when a bankruptcy of the company was opened.

Joseph Schumann was born in 1862 in Kostenblut, a village in Silesia, and learned watchmaking there. After his apprenticeship, he worked for some time for the prominent German clockmaker Gustav Eduard Becker (1819-1885) in Freiburg, Silesia (now Świebodzice, Poland). In 1883 Schumann moved to Glashütte and worked there for several years as a mechanic in Burkhardt’s calculating machine factory, then was appointed foreman. He died on 22 September 1913, in Glashütte at the age of 51.

The first models of the machine certainly are almost identical to Burkhardt’s Arithmometer, but later models had many improvements, such as a rotary setting lever by which a dust-tight encapsulation mechanism was possible, a moment cancellation mechanism, rolling box lid. There was even a model with a keyboard, instead of the traditional sliders of stepped-drum machines.

Over 12000 Saxonia machines were manufactured and sold from 1895 to 1914.

Great Britain’s first robot Eric was created in 1928 by the First World War veteran and a noted journalist Captain William Richards (known as WH) and by the early aviator and aircraft engineer Alan Reffell, to replace George VI (then the Duke of York) in opening the Exhibition of the Society of Model Engineers in London in September, 1928.

Captain Richards was secretary of the Society of Model Engineers, and when the Duke of York announced that was unable to open the Exhibition of the Society on 20 September 1928, he decided to create a robot to take the Duke’s place, using the help of the engineer Alan Reffell, whom he knew from his service in the air force. Richards was also an amateur engineer, keen on models and early technology. He must have been quite intrigued by Karel Čapek’s play, Rossum’s Universal Robots (R.U.R.), performed in London in 1923 and which is credited for being the first time the word robot was used. Thus Eric was born with RUR emblazoned on his chest.

At the appropriate time on that date in the Royal Horticultural Hall, Eric Robot arose, bowed, looked to the right and the left, and with appropriate gestures, proceeded to give a four-minute opening address, as sparks flashed from his teeth.

The Eric robot was manufactured in Gomshall in Surrey, where the Reffell family had a small motor business. It cost only £140 to build, weighed 45 kg, was 180 cm tall, and had light bulbs for eyes. It was operated by two people, and his voice was received live by a radio signal. Eric was able to stand, from an initial seated position, to turn his head in the direction of onlookers, to raise his arms, and to talk.

Although able to sit and stand, Eric could not move his legs to walk. The use of 35000 volts of electricity causes blue sparks to emanate from his teeth. His feet are fastened to a box, in which there is a twelve-volt electric motor. Inside his body, there is another motor, eleven electro-magnets, and about three miles of wire. He can move his arms and his head just as any real man does when speaking.

A report in the USA’s Brooklyn Daily Eagle newspaper dated 20 Feb 1929 states:
Eric Robot, “the perfect man,” made his first public appearance in America on the stage of the John Golden Theater, 58th St. and Broadway, yesterday afternoon.
Eric arrived from England with Capt. William Henry Richards, secretary of the Model Engineering Association of England, 14 days ago, and plans a tour of the continent. Eric is the mechanical man invented by Captain Richards after many years of private experimental work and was exhibited before the public for the first time 17 weeks ago in London.
Eric is made of aluminum, copper, steel, miles of wire, dynamos and electro-magnets. His eyes are two white electric bulbs, and his teeth, or rather tooth, is a blue bulb which, on the command, “Smile, Eric,” appears, accompanied by a sputtering sound. The upper half of Mr. Robot’s body, Captain Richards explained, is devoted to the speaking mechanism, and the rest to the movable parts. Eric made a five-minute speech yesterday, talking in an ordinary male voice. Eric was bombarded with questions by the audience, and having been posted with answers to hundreds of probable questions, made a fairly good showing.

The Eric robot was so successful that after his appearance he embarked on a world tour, with amazing crowds in Britain and Europe, before vanishing forever after the four-month promotional tour to the US in 1929. During the US tour, the robot introduced himself to an audience in New York as “Eric the robot, the man without a soul”. The New York Press described him as “the perfect man”.

Richards went on to conceive and build an improved robot called George in 1930, which he further co-developed with his son, W.E. (Ted) Richards, a motor engineer and WWI veteran. They traveled extensively together promoting George culminating in a tour of Australia in 1935-1936. George could deliver speeches in French, German, Hindustani, Chinese and Danish. He cost almost £2,000 to build, compared to Eric’s £140, and The Age newspaper described him as “the educated gentleman, alongside his rough-hewn awkward brother”.

Eventually, the outbreak of the Second World War in 1939 seems to have put an end to Richards’ activities with robots.

Biographies of William Richards and Alan Reffell

William Henry Richards was a man who wore many hats! He was born near Totnes, Devon, England on 4 September 1868. William began his civilian career as a printer from which he progressed to becoming a journalist. He and his first wife, Thirza, had four children and eventually settled in Camberwell, London.

In the late 1890s, Richards became a soldier, having served initially in the Royal North Devon Hussars, then in Imperial Yeomanry, which arrived in South Africa in March 1900 and took part in the Boer War. During the First World War, he served in Turkey (Gallipoli), then in Greece, Egypt, France, and Flanders, where it appears that he was a war correspondent.

After 1919 Richards was a journalist for the Plymouth-based Western Morning News, and later, the Manchester Guardian, The Illustrated London News, and the Daily Sketch. He was a member of the Press Club in London and later as he became more entrepreneurial, he was the proprietor of the London News Agency in Fleet Street, a specialty agency involved in sales and marketing. WH was also an amateur engineer, keen on models and early technology.

Richards was widowed in 1929 and remarried in 1930 to his secretary, Winifred. He retired to a country cottage in Guildford, Surrey, where he died on Christmas day (25 December) 1948, aged 80 years.

Alan Herbert Reffell was born on 14 March 1895 in Shere, Guildford, Surrey. His parents were William Joseph Reffell (1859-1931) and Kate Maria Boorer (1869-1909). He was the second of three sons and also had four sisters.

Alan Herbert joined the Royal Flying Corps as an Aircraft Mechanic before the outbreak of WWI aged only 18 in 1913. During the war, he served in a number of squadrons including some in France, and was awarded the 1914 (Mons) Star, the Victory Medal & the British War Medal, and the French Medaille Militaire. In 1919 he was transferred to reserve and in 1921 he was discharged.

Reffell married Violet Mary Durant (born 1897) on 21 November 1915 in Guildford, Surrey, and they had two sons: Roger Alan Reffell (1918-2007) and John L. Reffell (1920-1920).

Reffell was a holder of two patents in Britain and the USA for flotation gear for aircraft from 1932 (GB695198 and US1956494).

After the First World War, Alan Reffell ran a motor business in Gomshall Surrey, and worked on a number of interesting projects, including Eric Robot. He carried on his motor business between the wars and later expanded into making engineering lathes for a World War II government contract.

Alan Herbert Reffell died on 26 October 1979, at Crawley Sussex, aged 84.

Dr. Alexander John Thompson was a British statistician, the author of the last great table of logarithms, published in nine parts from 1924 to 1952. His table, the Logarithmetica Britannica, gives the logarithms of all numbers from 1 to 100000 to 20 places and supersedes all previous tables of similar scope, in particular the tables of Henry Briggs (1624), Adriaan Vlacq (1628) and Gaspard de Prony (1790s).

Thompson started his project of a new table of logarithms in 1922, celebrating the 300^th birthday of Briggs’ Arithmetica logarithmica. Initially, he started calculations of the tables with a single commercial mechanical calculating machine. However, he realized soon that with a special differential machine for processing four or five differences, the work could be done much more easily.

Thus Thompson constructed a machine (called Integrating and differencing machine), consisting of four successively arranged individual machines, standing on a staircase-shaped box and connected to each other (see the nearby figure). The assembly was made by the German company Triumphator in Leipzig-Mölkau. The individual machines were conversions from commercially available machines, that are expanded to 13 locations in the input mechanism.

Thompson’s desire for a printing unit and for mechanisms for automatically performing calculations failed because of the too-long development cycle and the associated high costs.

A detailed description of Thompson’s method of calculation and machine was compiled by Mr. Stephan Weiss (Die Differenzenmaschine von A. J. Thompson und die Logarithmetica Britannica).

Biography of Alexander John Thompson

Alexander John Thompson was born in 1885 in Plaistow, Essex, England (now a suburban area of East London). In 1905 he entered the Civil Service and served in a number of government departments. In 1920, A. J. Thompson joined the statistical staff of the General Register Office, Somerset House, London. Until his retirement in 1945, he was engaged in designing and writing official statistical reports on births, marriages, and deaths and on the Census of England and Wales.

A. J. Thompson was a Bachelor of Science (1911) and Ph.D. (1927, for Logarithmetica Britannica, parts IX (1924) and VIII (1927)), from the University of London. He was a member (1928-1965), vice-chairman (1938-1947), and chairman (1947-1948) of the Mathematical Tables Committee of the Royal Society.

Alexander John Thompson died on 17 June 1968, in Wallington, Surrey.

The robot word was conceived at the beginning of 1920 by the Czech writer and playwright Karel Čapek (with the help of his brother Josef, an acclaimed painter, graphic artist, writer, and poet), and was introduced in his drama R.U.R. (Rossum’s Universal Robots), published in November 1920 (see the lower image). Since then, and almost immediately, the robot word has become a universal expression in most languages for artificial intelligence machines, invented by humans.

How was the word robot invented, and what it means?

Karel Čapek described the occasion some 13 years later in the newspaper Lidové noviny of 24 December 1933 (in Kulturní kronika column, on page 12, see the text in English and the original report below):

The note of Prof. Chudoba about mentioning the Robot word in the Oxford dictionary and its derivation in English reminds me that I have an old duty. The author of the play RUR did not, in fact, invent that word, he merely ushered it into existence. It was like this: the idea for the play came to said author in a single, unexpected moment. And while it was still fresh he rushed immediately to his brother Josef, a painter, who was just standing by the easel, vigorously painting on a canvas.
“Listen, Josef,” the author began, “I think I have an idea for a play.”
“What kind of?” the painter mumbled (he really did mumble, because at the moment he was holding a brush in his mouth). The author told him as concisely as he could.
“Then write it,” the painter said, without taking the brush from his mouth or stopping to work on the canvas. His indifference was quite insulting.
“But,” the author said, “I don’t know what to call those artificial workers. I could call them Laboři, but that strikes me as a bit literal.”
“Then call them Roboti,” the painter muttered, brush in mouth, and carried on painting. So it happened…

How did the quick-witted Josef Čapek conceive the robot word? It seems Josef just wanted ASAP to get rid of his annoying younger brother, so he momentarily found the Czech equivalent of the proposed by Karel term laboři, using the Czech/Slavic word robota (meaning “(hard) work” not only in Czech, but also in the other Slavic languages like Bulgarian, Slovak, Russian, Serbian, Polish, and Ukrainian), which comes from the word rab (meaning “slave”). As it was mentioned in the report (Čapek is referring to the Czech writer, literary historian, and translator František Chudoba), it is also possible Josef to had encountered this word in some historic text, because according to the Oxford English Dictionary robot word was used to mean a central European system of serfdom whereby tenants’ rent was paid in forced labor or service. The system was abolished in the Austrian Empire in 1848 but was probably still in living memory in Čapek’s time.

How was the drama R.U.R. inspired?

Although in the second half of his life, Karel Čapek became a keen anti-fascist and anti-communist, as a young he was preoccupied with the difficult conditions of the factory workers and the brutal attitude of their managers ever since writing the story Systém (Krakonošova zahrada) together with his brother Josef, published in 1918. The memory of the Úpice (the hometown of Karel) textile workers on strike whom he had witnessed, seeing their march through the town, and the knowledge of newly introduced mass production and scientific management methods of manufacturing became his inspiration. In Systém Čapek brothers described the action of a greedy factory owner who tried to employ workers devoid of human needs, ideas, and emotions, purely to be used as automata and working machines to achieve the most efficient manufacturing means.

A further inspiration came at the beginning of 1920 when Karel took a tram from Prague’s suburbs to the city center. The tram was so uncomfortably overcrowded, that people were pressed together inside, even spilling outside onto the tram steps, appearing not like herded sheep, but like machines. Thus Karel imagined people not as individuals but as machines and during the journey thought about an expression that would describe a human being only able to work but not able to reason.

With that in mind, in the spring of 1920, Karel began to write a drama about the manufacture of artificial people from synthetic organic material who would free humans of work and drudgery, but finally due to overproduction those roboti would lead humankind to destruction and annihilation.

The play describes the activities of Rossum’s Universal Robots (R.U.R.) company that makes artificial people from man-made synthetic, organic matter. These beings are not mechanical creatures, as they may be mistaken for humans and can think for themselves. Initially, they seem happy to work for humans, but that changes with time, and at the end a hostile robot revolt points to the extinction of the human race, perhaps to be saved by a male robot and a female robot acting as Adam and Eve.

R.U.R. premiered in January 1921 and quickly became famous and influential in both Europe and North America. By 1923, it had been translated into thirty languages. The play was described as “thought-provoking”, “a highly original thriller”, “a play of exorbitant wit and almost demonic energy” and was considered one of the “classic titles” of inter-war science fiction.

Adolphus Sylvester Dennis (1857-1942), a former teacher at the Commercial College in Iowa City was an inveterate typewriter, calculator, and adding machine inventor, a man to whom at least 23 USA (as well as several Canadian and Great Britain) patents were issued, 12 of which were for typewriters. He also designed calculating machines, adding and recording machines, a “typographical adding machine” and a “computing machine”.

At the end of the 1880s, Dennis designed, and in 1890 patented, a typewriter with advanced duplex construction. In the early 1890s, he tried to attract business investors for its production and succeded. Dennis Duplex Typewriter Company of Des Moines, Iowa, started production in 1893. Despite predictions, the machine never took off and was manufactured for only a short time.

After this failure, around 1895 Dennis moved to Cleveland, Ohio, and started to design calculating and typewriting machines for the local manufacturers. The first patent of Dennis for a calculating device was US657266 (see the patent, applied 7 Dec 1895) for a typographical adding machine.

The typographical adding machine of Dennis employed one adding wheel and many totalizing wheels mounted in a sliding carriage and adapted to be engaged successively and operated by the adding wheel. His object was: (1) To provide an adding machine of simple, cheap, strong, and durable construction. (2) To provide in machines of this class having a series of totalizing wheels improved means for carrying the tens to the adjoining wheel to the left, for returning all of the wheels simultaneously to zero, and for elevating the wheels out of contact with the adding-wheels, so that printing may be carried on without the adding. (3) To provide improved and simplified paper and ribbon advancing mechanism to be operated by a return of the carriage.

Biography of Adolphus Dennis

Adolphus Sylvester Dennis was born on 12 May 1857 in Williamsburg, Clermont, Ohio. He was the son of William M. Dennis (1821–1907) and Eleanor (Foster) Dennis (1821–1880), who married in January 1842 and had nine children—3 girls and 6 boys (Adolphus was the 4^th son). In the middle 1860s, the family moved west to Iowa, where William used to work as a farmer. Adolphus spent his youth in Des Moines, Iowa, where on 24 June 1885 he married Francisca R. Cummings (1855-1920). They were the parents of at least one son and a daughter: Arthur Cummings (29 Jan 1887–3 Dec 1918), and Martha Sarah (1889–1982).

At the end of the 1880s, Dennis developed an advanced duplex typewriter. The design of this novel machine incorporated the use of two sets of keyboards, allowing users to push two keys at the same time, greatly increasing the speed at which a worker could produce documents. Some business people predicted the amazing new machine would replace the use of shorthand in offices. The Dennis Duplex Typewriter was showcased at the 1893 World’s Fair in Chicago. It received rave reviews for its performance, style, and durability. A fair committee highlighted the machine’s features: it doubled the speed of other typing machines, it could print two different letters of the alphabet as quickly as one letter by the traditional machines, it had two points of contact between the keys and paper, and it was strongly built. Although it was described as a “peculiar” invention, fairgoers also called it “ingenious.”

Business machine dealers who witnessed the Dennis typewriter in action at the fair proclaimed it the “finest automatic machinery in the world.” Their endorsements helped Dennis as he looked for additional investors for his factory back in Des Moines. He had plans to employ up to a thousand men within ten years at the factory where his machines would be built. The Humeston New Era newspaper reported that the typewriter’s World’s Fair exhibition allowed operators from all over the world to see the machine, and they were highly impressed. The article reported the machine—the “fastest writing machine in the world”—would become world famous. In fact, dealers from South Africa, South America, New Zealand, and Russia were applying to handle the duplex typewriter in their countries. In America, nine large cities now had dealers in the new typewriter.

Dennis wined and dined business investors in Des Moines. At one event he gave a lunch for prospective investors. About 150 people showed up to hear about the machine. Dennis said he had already invested $100,000 in his project. He asked attendees to help promote the machine as a “distinctively Des Moines invention.” An expert typewriter showed off the features of the machine at lunch, writing a sentence at the rate of 190 words per minute. He claimed he had been using one for a year and at one time had written as many as 206 words a minute on the duplex. It was reported that orders were already coming in for the machine.

George Anson Jewett (1847-1934), a Des Moines businessman, went into business with Dennis, and together they manufactured the duplex machine. Despite predictions, the machine never took off. It was over-produced and unnecessarily complicated, so it did not do well and its unique keyboard layout was scrapped.

After the failure of Dennis Duplex Typewriter, around 1895 Adolphus Dennis moved with his family to Cleveland, Ohio, where he continued his inventions. In the late 1910s, he moved to Oakland, California, and was still designing machines up to the early 1940s. For his last patents, Dennis applied on 30 Dec 1941, for a power-driven typewriter (US pat. No. 2331827), and for a calculating machine (US pat. No. 2365527), both assigned to Friden Calculating Machine Company. His son Arthur Cummings Dennis became a geologist and went into petroleum geology, working for various companies in the Midcontinent, but died young (together with his wife Alma Louise Proffer) with Spanish influenza in Wyoming in Dec 1918. Their thirteen-month-old daughter Frances managed to survive and was taken back to Oakland, California to be raised by her grandparents, Mr. and Mrs. Adolphus Dennis.

Adolphus Sylvester Dennis died on 23 May 1942 in Alameda County, California.

John Clinton Loehlin (1926–2020) was an American intelligence researcher, behavior geneticist, computer scientist, and psychologist. One of his groundbreaking achievements is the first attempt to endow a computer with emotion. In an effort to define and evaluate the major factors in “personality theory,” Loehlin wrote a computer program that was used to act as the intermediary between perception (input) and behavior (output).

In the early 1960s, Loehlin, a young professor at the University of Nebraska, became interested in computer models of personality. The idea originated in a paper presented by Loehlin at a conference on computer simulation and personality theory held at Princeton University, although the basic purposes and ideas in the computer simulation of psychological processes and behavior had been well defined by this time.

Initially, Loehlin basically created a small world of simulated automatons (termed Aldous after the author Aldous Huxley) and had them interact with one another to better understand what he had created. He defined each to have a “personality” or probabilistic way of reacting to threats–the “experiments” he ran with these different simulated creatures. Aldous was originally written on a Burroughs 205 Datatron computer entirely in assembly language. Burroughs 205 (see its Handbook) was a vacuum tube computer that cost a few hundred thousand dollars (equivalent to a few million today) and occupied an entire room.

Generally, Aldous was presented with a situation with certain characteristics and he responded based on some knowledge that had been previously acquired. Depending on the nature of the situation, Aldous may or may not receive further consequences. The Situation (external to Aldous) was defined with seven numbers. The first three were perceptual characteristics (0–9 for each of the three dimensions, thus there were 1000 possible perceptual situations). The next four numbers correspond to affective characteristics of the situation, based on Murray’s (1938) theory of situational “presses.” The four presses were defined as the relative probability of each situation to cause satisfaction, frustration, pain, and its power to do so. Thus there can be many combinations of stimulus perceptual characteristics.

Aldous had two storage locations—“immediate” and “permanent”,  to store information about how many times the present perceptual situation had been faced previously, how he responded to it each time before, and the class of perception and press to which this situation belongs. After Aldous responded, he had the capacity to adjust each of these memories to a degree that depended upon the reaction he produced, the consequence that the reaction produced, and the relative intensity of the response and the reaction. Aldous gave greater weight to recent memories and had the capacity to give a verbal (via a printout account) of his various memories at specific times. Loehlin called this “introspection.”

Once a stimulus situation had been introduced to Aldous he compared the situation with his memory. This included traces of previous encounters with the same and similar situations in the same perceptual classes. In addition, Aldous examined each press at essentially the same time for their individual attributes. Loehlin attempted to simulate human perceptual error by introducing a 6% error rate in this subsystem, so 6 out of every 100 stimulus characteristics were not recognized accurately by Aldous.

Once the situation was recognized by Aldous, an emotional reaction was developed based on the situational characteristics and the familiarity with the situation itself. For instance, if Aldous had never been exposed to a situation before, he would react based on any prior experience with similar classes of experience; Alternatively, if he has been exposed to that situation a few times before, he reacted based on this “experience.” In general, weight was given to the memories of that situation and to just the class of experiences but only if Aldous is familiar with the situation itself. In all, about 80% of responses were based on memory, and 20% were based on Aldous’s current mood (i.e., traces left from previous emotional characteristics). In terms of the reaction, Aldous had three possible emotional characteristics with which to react: (1) positively or with love; (2) with anger, or (3) with fear. Aldous calculated his own response predilection towards each of these. If one response was dominant, it interacted with its competitors to weaken them. If no response tendencies had been developed to a greater degree than another, Aldous developed emotional “conflicts.”

Aldous next selected an action based on the final emotion selected. He had three possible actions that corresponded to these emotional reactions: (1) approach; (2) attack; or (3) withdrawal. In addition, each of these could have two action strengths: (1) mild or (2) vigorous; or two non-action strengths (1) no action necessary, or (2) emotional “paralysis” (primarily caused by conflicts of relatively strong emotions). Thus, with all of the many possibilities of interactions, this behavior will be “physical” in only six ways. Only the verbal reports will show anything other than this.

Considering the presses of the situation, and Aldous’ behavioral actions, the external situation could feedback and affect Aldous in several ways. In fact, if Aldous approached there was always some consequence. If Aldous did nothing the situation must have some ability or power to affect; if Aldous avoided or attacked mildly the situation might have relatively high power; and if Aldous avoided or attacked vigorously the situation a very high power to cause a consequence. If there was no consequence there is no change in memory, but if there was a consequence there is a change in memory (Loehlin called this change “learning”). The consequence affects the situation and the response tendencies depend on the experience. That is, the more familiar Aldous was with the situation the less any consequence could happen that changed his “ideas” about it. This affected the entire class in the same way but with less of an effect.

Loehlin experimented with several “worlds” for Aldous—a hostile world where the presses of all the stimuli were injurious or frustrating, and a benign world where all the presses were satisfying. He also developed several “types” of Aldouses.

Loehlin spoke of this whole enterprise as an attempt to develop a “model of personality”, and planned to improve upon Aldous’s (a) limited ability to plan based on more than one situation, (b) his rather limited perceptual system and memory, and (c) the use of too many constant values.

Biography of John Loehlin

John Clinton Loehlin was born in Ferozepur, India, on 13 January 1926, the firstborn of Presbyterian missionary parents, Clinton Herbert Loehlin (1897-1987) and Eunice (Cleland) Loehlin (1899-1983). Clinton and Eunice were sent to India in the fall of 1923 to work under the Presbyterian Board of Foreign Missions, met during the voyage, and married on 31 Oct 2024. John had four sisters and a brother, James Herbert.

John grew up mainly in the Punjab region of northern India and attended the Woodstock School, an international coeducational residential facility in Landour, graduating in 1942. He moved to the USA to go to college, first in Ohio and later at Harvard, where he completed a bachelor’s degree in English, cum laude, in 1947. In 1947-49 worked in the research department of McCann-Erickson, an advertising firm in Cleveland, then started his research and teaching assistantships, at the Psychology Department of the University of California (Berkeley). A member of the United States Naval Reserve, he was called up for active duty during the Korean War, interrupting his graduate studies. He served in the Pacific from 1951-53, as a lieutenant of the US Navy. John returned to complete his Ph.D. in Psychology at Berkeley in 1957, with a dissertation on time perception.

Loehlin began teaching at the University of Nebraska, Lincoln, in 1957, where he met Marjorie Leafdale (1921-2021), who taught in the English Department. They married on 2 January 1962, and had two children, Jennifer Ann and James Norris.

In 1964 Loehlins moved to Austin for a visiting year at the University of Texas. That post turned into a permanent position, a joint appointment in Psychology and Computer Science. John Loehlin taught at Austin from 1964 to 1992, apart from a visiting semester at the Institute for Behavioral Genetics at the University of Colorado and a year at the Center for Advanced Study in the Behavioral Sciences in Palo Alto. He chaired the Psychology Department from 1979-83. He also served as president of the Behavior Genetics Association and the Society for Multivariate Experimental Psychology. John received the Dobzhansky Award from the former in 1991, and a Festschrift was held in his honor at the 2011 BGA meetings. He was a Fellow of the American Association for the Advancement of Science and a Charter Fellow of the American Psychological Society.

As Professor Emeritus of Psychology from 1992 until his death, he continued to be active in research and publication. His research was mainly on the interaction of genes and environment, especially on personality development. He also worked on the computer analysis of complex scientific data. He published seven scholarly books, some in multiple editions, and dozens of articles. He also enjoyed writing poetry, and brought out two volumes of verse; as a young man, he had poems published in The Cleveland Plain Dealer, Harper’s, and The New Yorker.

John Clinton Loehlin died on 9 August 2020 (aged 94), at his home in Austin, Texas.

Note: Material is based on the article “Loehlin’s Original Models and Model Contributions”, author: John J. McArdle, publisher: Behavior Genetics volume 44, 2014.

Shakey, the first mobile robot with the ability to perceive and reason about its surroundings, was created in the late 1960s at Stanford Research Institute (SRI) by a group of engineers, managed by Charles Rosen (1917-2002), as the project was funded by the Defense Advanced Research Projects Agency (DARPA).

In November 1963, Charles Rosen, a Canadian-American engineer, who had founded the Machine Learning Group at SRI, dreamed up the world’s first mobile automaton. In the next year, Rosen proposed building a robot that could think for itself, but his idea was met with skepticism by many in the nascent AI field. In the same year, Rosen applied for funding from DARPA, which grants funds for the development of emerging technologies. It took Rosen two years to get the funding (DARPA granted the researchers $750000 – more than $5 million in today’s money), and it took six more years, until 1972, before engineers at SRI’s AI Center finished building Shakey.

Shakey was a little less than two meters tall and had three sections. At the bottom was a wheeled platform (two stepping motors, one connected to each of the side-mounted drive wheels) that gave the robot its mobility, and collision detection sensors. Atop that were what looked like three slide-in units in a rack. Those held the robot’s camera-control unit and the onboard logic. Stacked on the uppermost unit was a range finder, a TV camera, and a radio antenna protruding from the top.

A radio link connected Shakey to a computer, which could process the incoming data, and send commands to the circuits that controlled the robot’s motors. Initially, an SDS (Scientific Data Systems) 940 computer was used. Around 1969, a more powerful DEC PDP-10 replaced the SDS 940. The PDP-10 used a large magnetic drum memory (that had the size of a refrigerator, holding some 1 megabyte) for swapping time-shared jobs in and out of working core memory.

Shakey used the Lisp programming language, as well as FORTRAN, and responded to simple English-language commands. A command to roll 2.1 feet would look like this:
SHAKEY = (ROLL 2.1)
Other commands included TILT and PAN, but there were also GOTO statements (which instead of jumping to a new position in the code) would actually cause the Shakey to go to a new position in the real world.
SHAKEY = (GOTO D4)
Which is more importantly, Shakey itself would first plan out the route it was going to take, even plotting a course around obstacles. And it could perform other useful tasks, like moving boxes.
SHAKEY = (PUSH BOX1 = (14.1, 22.7))

Shakey was presented in an extensive article in Life Magazine on 20 Nov 1970 (see the image below). A part of the article is as follows:
It looked at first glance like a Good Humor wagon sadly in need of a spring paint job. But instead of a tinkly little bell on top of its box-shaped body, there was this big mechanical whangdoodle that came rearing up, full of lenses and cables, like a junk sculpture gargoyle.
“Meet Shaky,” said the young scientist who was showing me through the Stanford Research Institute. “The first electronic person.”
I looked for a twinkle in the scientist’s eye. There wasn’t any. Sober as an equation, he sat down at an input terminal and typed out a terse instruction which was fed into Shaky’s “brain”, a computer set up in a nearby room: PUSH THE BLOCK OFF THE PLATFORM.
Something inside Shaky began to hum. A large glass prism shaped like a thick slice of pie and set in the middle of what passed for his face spun faster and faster till it dissolved into a glare then his superstructure made a slow 360⁰ turn and his face leaned forward and seemed to be staring at the floor. As the hum rose to a whir, Shaky rolled slowly out of the room, rotated his superstructure again and turned left down the corridor at about four miles an hour, still staring at the floor.

“Guides himself by watching the baseboards,” the scientist explained as he hurried to keep up. At every open door Shaky stopped, turned his head, inspected the room, turned away and idled on to the next open door. In the fourth room he saw what he was looking for: a platform one foot high and eight feet long with a large wooden block sitting on it. He went in, then stopped short in the middle of the room and stared for about five seconds at the platform. I stared at it too.
“He’ll never make it.” I found myself thinking “His wheels are too small. “All at once I got goose-flesh. “Shaky,” I realized, ”is thinking the same thing I am thinking!”
Shaky was also thinking faster. He rotated his head slowly till his eye came to rest on a wide shallow ramp that was lying on the floor on the other side of the room. Whirring brisky, he crossed to the ramp, semi-circled it and then pushed it straight across the floor till the high end of the ramp hit the platform. Rolling back a few feet, he cased the situation again and discovered that only one corner of the ramp was touching the platform. Rolling quickly to the far side of the ramp, he nudged it till the gap closed. Then he swung around, charged up the slope, located the block and gently pushed it off the platform.
Compared to the glamorous electronic elves who trundle across television screens, Shaky may not seem like much. No death-ray eyes, no secret transistorized lust for nubile lab technicians. But in fact, he is a historic achievement. The task I saw him perform would tax the talents of a lively 4-year-old child, and the men who over the last two years have headed up the Shaky project—Charles Rosen, Nils Nilsson and Bert Raphael—say he is capable of far more sophisticated routines. Armed with the right devices and programmed in advance with basic instructions, Shaky could travel about the moon for months at a time and, without a single beep of direction from the earth, could gather rocks, drill Cores, make surveys and photographs and even decide to lay plank bridges over crevices he had made up his mind to cross.
The center of all this intricate activity is Shaky’s “brain,” a remarkably programmed computer with a capacity more than 1 million “bits” of information. In defiance of the soothing conventional view that the computer is just a glorified abacus, that cannot possibly challenge the human monopoly of reason. Shaky’s brain demonstrates that machines can think. Variously defined, thinking includes processes as “exercising the powers of judgment” and “reflecting for the purpose of reaching a conclusion.” In some of these respects—among them powers of recall and mathematical agility–Shaky’s brain can think better than the human mind.
Marvin Minsky of MIT’s Project Mac, a 42-year-old polymath who has made major contributions to Artificial Intelligence, recently told me with quiet certitude, “In from three to eight years we will have a machine with the general intelligence of an average human being. I mean a machine that will be able to read Shakespeare, grease a car, play office politics, tell a joke, have a fight. At that point, the machine will begin to educate itself with fantastic speed. In a few months it will be at genius level and a few months after that its powers will be incalculable.”
I had to smile at my instant credulity—the nervous sort of smile that comes when you realize you’ve been taken in by a clever piece of science fiction. When I checked Minsky’s prophecy with other people working on Artificial Intelligence, however, many of them said that Minsky’s timetable might be somewhat wishful—”give us 15 years,” was a common remark—but all agreed that there would be such a machine and that it could precipitate the third Industrial Revolution, wipe out war and poverty and roll up centuries of growth in science, education and the arts. At the same time, a number of computer scientists fear that the godsend may become a Golem. “Man’s limited mind,” says Minsky, “may not be able to control such immense mentalities.”
Intelligence in machines has developed with surprising speed. It was only 33 years ago that a mathematician named Ronald Turing proved that a computer, like a brain, can process any kind of information—words as well as numbers, ideas as easily as facts; and now there is Shaky, with an inner core resembling the central nervous system of human beings. He is made up of five major systems of circuitry that correspond quite closely to how human faculties—sensation, reason, language, memory, ego—and these faculties cooperate harmoniously to produce something that actually does behave very much like a rudimentary person.
Shaky’s memory faculty, constructed after a model developed at MIT takes input from Shaky’s video eye, optical range finder, telemetering equipment and touch-sensitive antennae; taste and hearing are the only senses Shaky so far doesn’t have. This input is then routed through a “mental process” that recognizes patterns and tells Shaky what he is seeing. A dot-by-dot impression of the video input, much like the image on a TV screen, is constructed in Shaky’s brain according to the laws of analytical geometry. Dark areas are separated from light areas, and if two of these contrasting areas happen to meet along a sharp enough line, the line is recognized as an edge. With a few edges for clues, Shaky can usually guess what he’s looking at (just as people can) without bothering to fill in all the features on the hidden side of the object. In fact, the art of recognizing patterns is now so far advanced that merely by adding a few equations Shaky’s creators could teach him to recognize a familiar human face every time he sees it.
Once it is identified, what Shaky sees is passed on to be processed by the rational faculty—the cluster of circuits that actually does his thinking. The forerunners of Shaky’s rational faculty include a checker-playing computer program that can beat all but a few of the world’s best players, and Mac Hack, a chess-playing program that can already outplay some gifted amateurs and in four or five years will probably master the masters. Like these programs, Shaky thinks in mathematical formulas that tell him what’s going on in each of his faculties and in as much of the world as he can sense. For instance, when the space between the wall and the desk is too small to ease through, Shaky is smart enough to know it and to work out another way to get where he is going.
Shaky is not limited to thinking in strictly logical forms. He is also learning to think by analogy—that is, to make himself at home in a new situation, much the way human beings do, by finding in it something that resembles a situation he already knows, and on the basis of this resemblance to make, and carry out decisions. For example, knowing how to roll up a ramp onto a platform, a slightly more advanced Shaky equipped with legs instead of wheels and given a similar problem could very quickly figure out how to use steps in order to reach the platform.
But as Shaky grows and his decisions become more complicated, more like decisions in real life, he will need a way of thinking that is more flexible than either logic or analogy. He will need a way to do the sort of ingenious, practical “soft thinking” that can stop gaps, chop knots, make the best of bad situations and even, when time is short, solve a problem by making a shrewd guess.
The route toward “soft thinking” has been charted by the founding fathers of Artificial Intelligence, Allen Newell and Herbert Simon of Carnegie-Mellon University. Before Newell and Simon, computers solved (or failed to solve) non-mathematical problems by a hopelessly tedious process of trial and error. “It was like looking up a name in a big-city telephone book that nobody has bothered to arrange in alphabetical order.” says one computer scientist. Newell and Simon figured out a simple scheme -modeled, says Minsky, on “the way Herb Simon’s mind works.” Using the Newell-Simon method, a computer does not immediately search for answers, but is programmed to sort through general categories first, trying to locate the one where the problem and solution would most likely fit. When the correct category is found, the computer then works within it, but does not rummage endlessly for an absolutely perfect solution, which often does not exist. Instead, it accepts (as people do) a good solution, which for most non-numerical problems is good enough. Using this type of programming, an MIT professor wrote into a computer the criteria a certain banker used to pick stocks for his trust accounts. In a test, the program picked the same stock the banker did in 21 of 25 cases. In the other four cases the stocks the program picked were so much like the ones the banker picked that he said they would have suited the portfolio just as well.
Shaky can understand about 100 words of written English, translate these words into a simple verbal code and then translate the code into the mathematical formulas in which his actual thinking is done. For Shaky, as for most computer systems, natural language is still a considerable barrier. There are literally hundreds of “machine languages” and “program languages” in current use, and computers manipulate them handily, but when it comes to ordinary language they’re still in nursery school. They are not very good at translation, for instance, and no program so far created can cope with a large vocabulary, much less converse with ease on a broad range of subjects. To do this, Shaky and his kind must get better at Working with symbols and ambiguities (the dog in the window had hair but it fell out). It would also be useful if they learned to follow spoken English and talk hack, but so far the machines have a hard time telling words from noise.
Language has a lot to do with learning, and Shaky’s ability to acquire knowledge is limited by his vocabulary. He can learn a fact when he is told a fact, he can learn by solving problems, he can learn from exploration and discovery. But up to now neither Shaky nor any other computer program can browse through a book or watch a TV program and grow as he goes, as a human being does. This fall, Minsky and a colleague named Seymour Papert opened a two-year crash attack on the learning problem by trying to teach a computer to understand nursery rhymes “It takes a page of instructions,” says Papert, “to tell the machine that when Mary had a little lamb she didn’t have it for lunch.”
Shaky’s ego, or executive faculty, monitors the other faculties and makes sure they work together. It starts them, stops them, assigns and erases problems; and when a course of action has been worked out by the rational faculty, the ego sends instructions to any or all of Shaky’s six small on-board motors—and away he goes. All these separate systems merge smoothly in a totality more intricate than many forms of sentient life and they work together with wonderful agility and resourcefulness. When, for example, it turns out that the platform isn’t there because somebody has moved it, Shaky spins his superstructure, finds the platform again and keeps pushing the ramp till he gets it where he wants it—and if you happen to be the somebody who has been moving the platform, says one SRI scientist, “you get a strange prickling at the back of your neck as you realize that you are being hunted by an intelligent machine.”
With very little change in program and equipment, Shaky now could do work in a number of limited environments; warehouses, libraries, assembly lines. To operate successfully in more loosely structured scenes, he will need far more extensive, more nearly human abilities to remember and to think. His memory, which supplies the rest of his system with a massive and continuous flow of essential information, is already large, but at the next step of progress, it will probably become monstrous. Big memories are essential to complex intelligence. The largest standard computer now on the market can store about 36 million “bits” of information in a six-foot cube, and a computer already planned will be able to store more than a trillion “bits” (one estimate of the capacity of a human brain) in the same space.
Size and efficiency of hardware are less important, though, than sophistication in programming. In a dozen universities, psychologists are trying to create computers with well-defined humanoid personalities, Aldous, developed at the University of Texas by a psychologist named John Loehlin, is the first attempt to endow a computer with emotion. Aldous is programmed with three emotions and three responses, which he signals. Love makes him signal approach, fear makes him signal withdrawal, anger makes him signal attack. By varying the intensity and probability of these three responses, the personality of Aldous can be drastically changed. In addition, two or more different Aldouses can be programmed into a computer and made to interact. They go through rituals of getting acquainted, making friends, having fights.
Even more peculiarly human is the program created by Stanford psychoanalyst Kenneth M. Colby. Colby has developed a Freudian complex in his computer by setting up conflicts between beliefs (I must love Father, I hate Father). He has also created a computer psychiatrist and when he lets the two programs interact, the “patient’ resolves its conflicts just as a human being does, by forgetting about them, lying about them or talking truthfully about them with the “psychiatrist.” Such a large store of possible reactions has been programmed into the computer and there are many possible sequences of question and answer-that Colby can never be exactly sure what the “patient” will decide to do.
Colby is currently attempting to broaden the range of emotional reactions his computer can experience. “But so far,” one of his assistants says, “we have not achieved computer orgasm.”
Knowledge that comes out of these experiments in “sophistication” is helping to lead toward the ultimate sophistication—the autonomous computer that will be able to write its own programs and then use them in an approximation of the independent, imaginative way a human being dreams up projects and carries them out. Such a machine is now being developed at Stanford by Joshua Lederberg (the Nobel Prize-winning geneticist) and Edward Feigenbaum. In using a computer to solve a series of problems in chemistry. Lederberg and Feigenbaum realized their progress was being held back by the long, tedious job of programming their computer for each new problem. That started me wondering.” says Lederberg. “Couldn’t we save ourselves work by teaching the computer how we write these programs, and then let it program itself.”
Basically, a computer program is nothing more than a set of instructions (or rules of procedure) applicable to a particular problem at hand. A computer can tell you that 1 + 1 = 2—not because it has that fact stored away and then finds it, but because it has been programmed with the rules for simple addition. Lederberg decided you could give a computer some general rules for programming; and now, based on his initial success in teaching a computer to write programs in chemistry, he is convinced that computers can do this in any field—that they will be able in the reasonably near future to write programs that write programs that write programs…

Oliver Evans (1755–1819) was an American inventor, engineer, and businessman, a pioneer in the field of automation, who has been called the first great American inventor the Watt of America. Among his long series of accomplishments was designing and building the first fully automated industrial process in the late 1780s, a flour mill in Newport, Delaware.

In 1782, Oliver and two of his elder brothers, John (1846-1798) and Theophilus (1753-1809) purchased part of their father’s farm in Red Clay Creek, Delaware, to build a grain mill, as Oliver was put in charge of overseeing its construction. When the mill opened in September 1785, it was of a conventional design, but over the next five years, Oliver began to experiment with inventions to reduce the reliance upon labor for milling.

Evans’s first innovation was a bucket elevator to facilitate moving wheat from the bottom to the top of the mill to begin the process. Chains of buckets to raise water was an old Roman technology, used in various processes since antiquity. Evans had seen diagrams of their use for marine applications and realized with some modification they could be used to raise grain, so devised a series of bucket elevators around a mill to move grain and flour from one process to the next.

Another labor-intensive task was that of spreading meal, which came out of the grinding process warm and moist, needing cooling and drying before it could be sifted and packed. Traditionally the task was done by manually shoveling meals across large floors. For this purpose, Evans developed the hopper boy, a device that gathered meal from a bucket elevator and spread it evenly over the drying floor, as a mechanical rake would revolve around the floorspace. This would even out newly deposited meals for cooling and drying, while a gentle incline in the design of the rake blades would slowly move the flour towards central chutes, from which the material would be sifted.

At this time the U.S. Patent Office had not been organized yet, and several States exercised the privilege of granting exclusive rights to the use of the invention within their own boundaries. In 1786, Evans applied to the Legislature of Pennsylvania for a right to use his improvements in machinery for making flour, and also to use his steam wagons on the roads of the State. The following year the Legislature granted him only flour mil patent, but, on 21 May 1787, the Legislature of Maryland granted both rights for fourteen years. A similar patent was granted in 1789 by New Hampshire. In 1790, when the U.S. Patent Office was organized, Evans relinquished his State rights, and on 18 December 1790, a U.S. patent Number 3X was granted for his “method of manufacturing flour and meal.” This is said to be one of the three patents granted that year.

Evans had a rather abrasive personality and little tolerance for those who did not see the originality and importance of his inventions. This made it difficult for him to obtain financial backing, forcing him to depend on patent royalties.

Biography of Oliver Evans

Oliver Evans was born in Newport, Delaware on 13 September 1755. He was the fifth son of Charles (a Welsh-American) and Annika (Ann) Evans (nee Stalcop), a Swedish-American. Charles (1724-1799) and Ann (1729-1799) married in 1745 and had 12 children—8 boys and 4 girls. Charles Evans was a shoemaker by trade, though he purchased a large farm to the north of Newport on the Red Clay Creek and moved his family there when Oliver was still in his infancy.

Oliver was apprenticed to a wheelwright, or wagon maker, at the age of 15, and then he worked in several other mechanical trades. He was a thoughtful, studious boy, who devoured eagerly the few books to which he had access, even by the light of a fire of shavings, when denied a candle by his parsimonious masters.

The American Revolutionary War began when Oliver was 19. He enlisted in a Delaware militia company but saw no active service during the war.

In 1772, when only seventeen years old, Oliver began to contrive some method of propelling land carriages by other means than animal power and thought of a variety of devices, such as using the force of the wind and treadles worked by men. Soon into his hands fell a book describing the old atmospheric steam engine of Newcomen, and he was at once struck with the fact that steam was only used to produce a vacuum, while to him it seemed clear that the elastic power of the steam, if applied directly to moving the piston, would be far more efficient. Evans soon satisfied himself that he could make steam wagons, but could convince no one else of this possibility. In 1777 he completed a successful machine for making the wire teeth of wool cards, and then invented, but did not build, a machine for making and sticking the teeth in the leather backs.

In the early 1780s, Evans also began experimenting with steam power and its potential for commercial application. His early ideas culminated in a Delaware state patent application in 1783 for a steam-powered wagon, but it was denied as Evans had yet to produce a working model. That same year, aged 27, Evans married Sarah Tomlinson (1763-1816), daughter of John Tomlinson, a local farmer, in Old Swedes’ Episcopal Church in Wilmington. The couple will have three sons and four daughters.

In 1805 Evans designed a refrigeration machine that ran on vapor, although he never built one. Later his design was modified by Jacob Perkins, who obtained the first patent for a refrigerating machine in 1834.

The device for which Evans is best known today is his Oruktor Amphibolos (Amphibious Digger), built on commission from the Philadelphia Board of Health (Evans lived in Philadelphia since 1792). The Board was concerned with the problem of dredging and cleaning the city’s dockyards, and in 1805 Evans convinced them to contract with him for a steam-powered dredge. Evans built it, but Oruktor Amphibolos was never a success as a dredge, and after a few years of sitting at the dock was sold for parts.

In 1811, Evans founded the Pittsburgh Steam Engine Company, which in addition to engines made other heavy machinery and castings in Pittsburgh, Pennsylvania. The location of the factory in the Mississippi watershed was important in the development of high-pressure steam engines for use in riverboats.

In 1817 Evans compiled a list of all his inventions (some 80 in total). Some of his unfinished ideas that are known include a scheme for gas lighting, a means for raising sunken ships, a machine gun, a self-oiling shaft bearing, various types of gearshift for steam carriages, a dough-kneading machine, and a perpetual baking oven.

In 1816 Evans’ wife Sarah died, and he remarried two years later in April 1818 to Hetty Ward, who was many years his junior and the daughter of the New York innkeeper. In March 1819 Evans developed an inflammation of the lungs, and on 11 April, news reached him in New York that his shop Mars Works in Philadelphia had burned down. This bad news appears to have brought on a fatal attack of apoplexy, and he died on 15 April 1819 and was buried at Zion Episcopal Church in Manhattan.