Dream Machines: Thinking and Calculating

Descartes, “Discourse on the Method” (1637): “two very certain means” (translated) of telling a human-like machine from a human

In Part 5 of “Discours de la methode”, René Descartes starts from automata made by human hands (moving machines) and argues that animal bodies, too, are like machines made by God. He then writes that even if a machine looked like a human body and imitated its movements, there are “two very certain means” (translated) of telling it is not a real human. (1) A machine can never put words or signs together and answer according to the meaning of what is said in front of it, something even the dullest person can do. (2) Even if a machine does many things as well as a human or better, it will certainly fail at something else. Reason is a universal instrument that can be used in every situation, but a machine needs a particular arrangement of parts for each action, so it is practically impossible to fit into one machine enough arrangements to cover every situation in life. It can be read as an idea that came about 300 years before Turing’s “imitation game” (1950).

What happened next:On (1): in March 2025, researchers at a US university (UC San Diego) ran an experiment in which an interrogator chatted for 5 minutes with a human and a machine at the same time. They reported in a paper (arXiv) that a large language AI (GPT-4.5), told to play the part of a human, was judged to be the human 73% of the time (the announcement of one research group). Whether this counts as what Descartes called “to respond to the sense of everything said in its presence” (translated) is a matter of differing views. On (2): whether a machine that can act like a human in any situation in life (in today’s words, artificial general intelligence) has been built is still disputed in 2026 (see the records of the fourth boom’s predictions).

What we still don’t know:Whether a machine could have “a universal instrument” (translated) of reason mentioned in (2), and whether passing test (1) would mean the machine understands meaning, are still unsettled today. (In 1950 Turing himself replaced the question “Can machines think?” with a different question. See record → Turing publishes a paper discussing mac….)

Hobbes, “Leviathan” (1651): “Reason ... is nothing but Reckoning (that is, Adding and Substracting)”

In his book “Leviathan”, Chapter 5, “Of Reason, and Science”, Thomas Hobbes wrote that to reason (to think in a logical sequence) is nothing but adding parts to get a sum, or subtracting one sum from another to get the remainder. He then defined reason as “Reckoning” the chain of agreed general names (words), in other words as nothing more than adding and subtracting. He also wrote that logicians add names together to make statements, and add statements together to make syllogisms. And just as people make mistakes in arithmetic, he said, even the most careful people can make mistakes in reasoning. In the Introduction he asks whether a machine that moves by itself with springs and wheels (an automaton) might not be said to have “an artificiall life”. He asks whether the heart is not a spring, the nerves strings and the joints wheels, and then goes on to say that human art goes further still and makes “an Artificiall Man”, which is the commonwealth (the Leviathan).

Hosokawa Hanzo Yorinao publishes “Karakuri Zui”, a book that explains with diagrams how to make mechanical puppets

Hosokawa Hanzo Yorinao of Tosa published “Karakuri Zui” (Karakuri Zui), a book that explains how to build Japanese clocks and the inner mechanisms of 9 kinds of karakuri puppets, such as the tea-serving puppet, with diagrams of gears and springs. The tea-serving puppet moves forward when a teacup is placed on the tray it holds, stops when the cup is taken, and turns around and comes back when a cup is placed on it again. Whalebone was used for the springs.

Takeda Omi founds the karakuri (mechanical puppet) theater “Takeda’s Theater” (Japanese: Takeda no Shibai) in Dotonbori, Osaka

The first Takeda Omi used clockwork-based karakuri (mechanical devices) to open a theater devoted entirely to karakuri, “Takeda no Shibai” (Takeda’s Theater), in Dotonbori, Osaka. It showed the art of moving puppets and props by springs and water power at low prices. Because audiences wanted to know how the tricks worked, he also published a book explaining the mechanisms. The theater lasted about 100 years, and its techniques were passed on to joruri (Japanese puppet theater) and to festival float puppets.

The Jaquet-Droz automata: a boy who writes, a boy who draws, a girl who plays the organ (1768–1774)

The watchmaker Pierre Jaquet-Droz, his son Henri-Louis and Jean-Frédéric Leschot built three automata in La Chaux-de-Fonds between 1768 and 1774. The figures were named l’Écrivain (the Writer), la Musicienne (the Musician) and le Dessinateur (the Draftsman). Using clockwork, they write letters with a quill pen, draw pictures and play the organ. After touring Europe for a long time, the three were given to the city of Neuchâtel on May 1, 1909. They are now shown in demonstrations every month at the Neuchâtel Museum of Art and History in Switzerland (the name as Britannica writes it). However, according to a notice on the museum’s website that we saw on September 23, 2026, l’Écrivain cannot be run because of a faulty part and is being repaired.

Kempelen’s “Chess-Playing Turk”: a person was hiding inside

Kempelen, a nobleman from Pressburg in Hungary, built a machine at the court in Vienna for Empress Maria Theresa: a figure in Turkish dress that played chess on top of a cabinet. It toured Europe and America and amazed many people, but in fact a skilled chess player was hidden in the cabinet and moved it. As early as 1784 a book was published saying that a person was hidden inside and playing, and in 1821 a book appeared that explained with diagrams how the person hid. The machine was destroyed in a fire in Philadelphia in 1854.

Poe argues that a machine alone could not play chess, so a person must be moving it from inside

Edgar Allan Poe wrote an essay about the Chess-Playing Turk figure. Babbage’s calculating machine reaches its answers by a fixed procedure, but chess changes with the opponent’s moves, so Poe argued that a machine alone could not play it and that a human mind was running it. He also pointed out that a real machine should always win, yet the Turk sometimes loses.

What happened next:In 1950 Shannon proposed in a paper a way to have a general-purpose computer play reasonably good chess by a program, and pointed out that Poe’s argument does not hold. In May 1997, IBM’s computer Deep Blue beat the world champion of the time 3.5 to 2.5 in a six-game match in New York (IBM’s account).

Babbage announces a machine that calculates and prints tables of numbers automatically (the Difference Engine)

In an open letter to Davy, the president of the Royal Society, Charles Babbage of Britain described his plan for the Difference Engine. It is a machine that automatically calculates the tables of numbers used for logarithms and astronomy by repeatedly adding the differences between neighboring numbers, and even prints them. At the start of the letter he wrote that, out of the great drudgery of repeating the same calculations, he had thought of a machine that could take the place of one of the lowest workings of the human intellect.

Ada Lovelace publishes Babbage’s Analytical Engine description with long notes of her own

Ada Lovelace translated into English an account of Babbage’s “Analytical Engine” (a machine designed to calculate anything, given its steps by punched cards; it was never built), written in French by the Italian engineer Menabrea. She published it with notes about three times as long as the original. It was signed only A.A.L. In Note G she wrote that the machine does not pretend to originate anything; it can do whatever humans know how to order it to do.

What we still don’t know:What it means for a machine to have “no pretensions whatever to originate any thing” is still unsettled. (In 1950 Turing took up this sentence as “Lady Lovelace’s Objection” and replied that machines often surprise him.)

Lovelace’s forecast: “the engine might compose elaborate and scientific pieces of music”

In Note A, Lovelace argued that the Analytical Engine should be able to handle not only numbers but anything whose relations can be expressed in symbols. As an example, she wrote that if the relations between pitches of sound could be expressed in the machine’s symbols, the machine might compose music of any degree of complexity and length, elaborate pieces.

What happened next:The Analytical Engine itself was never built. About 110 years later, on August 9, 1956, at the University of Illinois in the United States, students performed the first three movements of a string quartet composed with the computer ILLIAC I (the Illiac Suite) (the university museum’s account; it was completed by the end of 1956, though some sources write 1957).

Boole’s “An Investigation of the Laws of Thought”: expressing the laws of reasoning in an algebra of 0 and 1

George Boole, professor of mathematics at Queen's College, Cork, published his book “An Investigation of the Laws of Thought”. Its aim was to express the laws of thought by which humans reason (think in a logical sequence) as calculations with symbols, like algebra, and to build the theories of logic and probability on that (Chapter 1, Section 1). Boole noticed that 0 and 1 are the only numbers that satisfy x×x = x (x² = x). He argued that if you consider an algebra in which the symbols x, y and z take only the two values 0 and 1, it has the same form as the laws of logic (page 37). This algebra of 0 and 1 was later called Boolean algebra, and became the basis of the logic circuits (AND, OR, NOT) studied in Information I (Japan’s required high-school informatics course).

The word “robot” is born in Čapek’s play “R.U.R.”

The Czech writer Karel Čapek published the play “R.U.R. (Rossum’s Universal Robots)”, in which artificial humans called “robots”, mass-produced from artificial materials, do the work. At the National Theatre in Prague it opened on January 25, 1921, and had been performed 63 times by 1927. “Robot” was coined from a word meaning labor, and in the story Karel himself wrote, it was his brother Josef, a painter, who gave the name.

What we still don’t know:We have not been able to open the original text of the story Karel himself wrote (a newspaper column; the year has not been confirmed in the sources).

Makoto Nishimura builds “Gakutensoku”, a large humanoid with changing facial expressions

The biologist Makoto Nishimura, then an editorial writer for the Osaka Mainichi Shimbun, built a humanoid (robot) named “Gakutensoku”, a name meaning “learning from the laws of heaven” (translated). It was shown at the 1928 Kyoto Grand Exposition commemorating the Imperial Enthronement. Using compressed air and rubber tubes, it moved its eyes, eyelids, cheeks, mouth, neck, both arms and chest, and changed its expression. It is said to have later gone to Germany and been lost. The Osaka Science Museum restored it in 2008.

What we still don’t know:Where in Germany and how the original Gakutensoku ended up is not known (the museum, too, writes “is said to” (translated)).

Asimov’s “Three Laws of Robotics” (1942): three rules that robots follow in his stories

The science fiction writer Isaac Asimov set out the three rules that robots obey, the “Three Laws of Robotics”, in clear form in the short story “Runaround”, published in the March 1942 issue of the magazine Astounding. (1) A robot may not injure a human being or, through inaction, allow a human being to come to harm. (2) A robot must obey orders given by humans, except where that would conflict with the First Law. (3) A robot must protect itself, as long as that does not conflict with the First or Second Law. In the story, vagueness of wording and conflicts between the laws became the seeds of the plot, for example a robot whose Third Law (self-protection) has been strengthened gets caught in a bind when priorities between the laws collide (SFE). Asimov later added the “Zeroth Law”, that a robot must not harm humanity as a whole (stated clearly in a 1985 work). The three laws went beyond science fiction and came to be discussed in debates about robots and AI (Britannica).

What we still don’t know:Even if rules are set in words, the results change depending on how words such as “human” and “harm” are defined (the many stories about definitions that SFE lists). The same challenge remains when we write in words the rules we want today’s AI to follow (this site’s view).

Akira Nakashima and Masao Hanzawa of NEC publish a theory for calculating relay circuits with formulas

Akira Nakashima and Masao Hanzawa, engineers at Nippon Electric Company (NEC), published in the journal of the Institute of Electrical Communication Engineers a theory for designing the relay circuits (switches operated by electricity) used in telephone exchanges and similar equipment by calculating with formulas of symbols. They discovered that if series and parallel connections of switches are written like addition and multiplication of symbols, they follow rules different from ordinary arithmetic. This had the same form as Boole’s logical calculus of 1854 (Boolean algebra), but Nakashima did not know Boolean algebra at the time. It is an idea that became the basis of later computer circuit design.

Turing, “On Computable Numbers”: defining what it means to be “computable” with a machine in the head

Alan Turing published the paper “On Computable Numbers, with an Application to the Entscheidungsproblem”. He simplified the steps of a person calculating with paper and pencil down to a “machine” that has a tape divided into squares (in place of paper), a head that reads and writes one square at a time, and only a finite number of states (Sections 1 and 9). He defined a number whose decimal digits this machine can write out as “computable”. He further showed that one machine (a universal machine) can compute any computable sequence if it receives the description of another machine on its tape (Section 6). And he showed that there is no method that always decides, by a fixed procedure, whether a logical formula can be proved (the answer to the decision problem) (Section 11). The next year this model was named the “Turing machine”, and it is regarded as a foundational model of the theory of computation and of computer science.

The McCulloch and Pitts paper: writing the brain’s nerve cells as a circuit of switches that fire or do not fire, in formulas

Warren McCulloch and Walter Pitts published the paper “A Logical Calculus of the Ideas Immanent in Nervous Activity”. Because the activity of a nerve cell (neuron) is “all-or-none” (it fires or it does not), they reasoned that the workings of a neural network can be described by propositional logic (logic with only two values, true and false). As premises for the calculation they set that firing is all-or-none, that a neuron fires when a certain number of synapses are stimulated at the same time, that if even one inhibitory synapse is active the neuron does not fire, and that the structure of the network does not change with time (page 118). They further wrote that if a tape and a reading device are added, this network can compute the same numbers as a Turing machine (page 129). It is regarded as a starting point of later research on artificial neurons.

What we still don’t know:The paper itself cautions that the “formal equivalence”, that a learning network can be replaced by a network whose structure does not change, is not an explanation of facts about the real brain (page 117). That real neurons do not work exactly as these premises assume (all-or-none, unchanging structure) can be used as an example for understanding the difference between a model and the real thing.

The McCulloch and Pitts paper: writing the brain’s nerve cells as a circuit of switches that fire or do not fire, in formulas

Warren McCulloch and Walter Pitts published the paper “A Logical Calculus of the Ideas Immanent in Nervous Activity”. Because the activity of a nerve cell (neuron) is “all-or-none” (it fires or it does not), they reasoned that the workings of a neural network can be described by propositional logic (logic with only two values, true and false). As premises for the calculation they set that firing is all-or-none, that a neuron fires when a certain number of synapses are stimulated at the same time, that if even one inhibitory synapse is active the neuron does not fire, and that the structure of the network does not change with time (page 118). They further wrote that if a tape and a reading device are added, this network can compute the same numbers as a Turing machine (page 129). It is regarded as a starting point of later research on artificial neurons.

What we still don’t know:The paper itself cautions that the “formal equivalence”, that a learning network can be replaced by a network whose structure does not change, is not an explanation of facts about the real brain (page 117). That real neurons do not work exactly as these premises assume (all-or-none, unchanging structure) can be used as an example for understanding the difference between a model and the real thing.

The ENIAC announcement: the Army release says “This mathematical robot” ... “it cannot do creative thinking”, while the newspapers say “electronic brain”

The US War Department announced ENIAC, an electronic calculating machine developed at the Moore School of Electrical Engineering of the University of Pennsylvania. According to the release, it had about 18,000 vacuum tubes, took up a room of 30 by 50 feet, weighed 30 tons, and was 1000 times faster than the most advanced general-purpose calculating machine of the time. Work began in July 1943 to produce firing tables (ballistic tables) for guns and bombs, and it was finished in the autumn of 1945. The calculation steps (the program) were set by reconnecting switches and cables by hand (Weik 1961). In those days people who did calculations were also called “computer”, and the release says that about 200 trained “computer” were needed to produce firing tables. The release calls ENIAC “This mathematical robot”, and also records that “it can carry out numerous ‘logical’ operations but that it cannot do creative thinking”.

Hebb’s “The Organization of Behavior”: the assumption that nerve connections that are used often become stronger

The psychologist Donald Hebb published the book “The Organization of Behavior: A Neuropsychological Theory”. In “A Neurophysiological Postulate” on page 62, he assumed that when cell A repeatedly or persistently takes part in the process of making cell B fire, some change happens in one or both cells, and A’s efficiency in firing B increases. In other words, the more a connection is used, the stronger it becomes. On the same page Hebb himself notes that there is no direct evidence for the mechanism. This idea is called the “Hebb rule”, and it became one of the starting points of both research on how the brain works and the learning methods of artificial neural networks.

What we still don’t know:In 1949 Hebb wrote that the mechanism (the growth of synaptic knobs) was the “most probable suggestion” but that there was no direct evidence (page 62). Later, experiments found a similar phenomenon (Nilsson). It can be used as an example of an idea put forward as an assumption that was confirmed later.

Weaver’s memorandum “Translation”: the first call to ask whether calculating machines could translate languages

Warren Weaver of the Rockefeller Foundation wrote a memorandum titled “Translation” on whether computers could be used for translation, and circulated it to people he knew. In 1947, in a letter to Professor Norbert Wiener of MIT, Weaver wrote that when he looks at an article in Russian, he says “This is really written in English, but ... coded in some strange symbols”, and asked about the idea of translating by computer. But Wiener replied that, frankly, he thought there was little hope for translation by machine-like methods because “boundaries of words in different languages are too vague ... connotations are too extensive”, and the matter went no further. In the memorandum, Weaver gave the idea of context: if you read a book through a mask with a hole only one word wide, you cannot tell whether “‘Fast’ may mean ‘rapid’; or it may mean ‘motionless’”, but if you widen the hole so that N words before and after can be seen, the meaning is settled. He proposed studying the statistical properties of language. Weaver himself repeatedly cautions that his ideas may be naive. This memorandum is regarded as the start of the field of machine translation (Nilsson).

IBM and Georgetown University give a public demonstration of machine translation from Russian

At IBM’s headquarters in New York, the computer IBM 701 translated Russian sentences prepared by language researchers of Georgetown University into English in a few seconds. It was a small experiment with a vocabulary of 250 words and only 6 grammar rules, but it was reported prominently, including on the front page of the New York Times, and it became the trigger for money to flow into machine translation research.

Dostert’s forecast: in 5 years, perhaps 3, machine translation in important areas of several languages may well be a reality

On the day of the demonstration, Dostert of Georgetown University said that it had become clear that translation by electronic processing is possible. And he predicted that “five, perhaps three years hence, interlingual meaning conversion ... may well be an accomplished fact”. At the same time, however, he stressed that it was not yet possible to feed in a Russian book and have an English book come out.

What happened next:According to Hutchins (2004), the impression that practical translation was near brought in a lot of research funding afterward. But the results of the following 10 years fell short of expectations, and the funders set up an investigation committee called ALPAC (report of 1966). Nilsson (2010) also writes that the research afterward was a disappointment.

Shannon publishes the paper “Programming a Computer for Playing Chess”

Claude Shannon of Bell Labs in the US published a paper on a way to make a general-purpose computer play chess by a program. Because reading every move through to the end of the game takes an enormous amount of calculation and is impossible, he proposed a method of looking a few moves ahead, scoring how good each position is, and choosing the best move.

Babbage writes that he thought “every game of skill is susceptible of being played by an automaton”, and that he tried to put a tic-tac-toe machine on show

In his memoirs, Babbage wrote that he chose to have a machine play games that need only the head, such as tic-tac-toe, checkers and chess, as a test of his way of thinking. When he asked people, most answered that games of skill require human reason. A small number who knew mathematics admitted that a machine might be possible, but insisted that no such machine could be built because even the simplest game has countless combinations. Babbage believed that any game could be played by a machine, and tried to raise money for the Analytical Engine by putting a tic-tac-toe machine on show, but gave up when he learned that other shows were not making money.

What we still don’t know:We have not checked how far the drawings of the tic-tac-toe machine were actually carried out.

Turing publishes a paper discussing machine intelligence through the “imitation game”

The British mathematician Alan Turing published a paper that replaces the question “Can machines think?” with the “imitation game”. The original is a game in which an interrogator tries to guess, using only written exchanges, which of a man and a woman in another room is which. Turing turned it into the question of how often the interrogator would be wrong if a machine played the man’s part. The paper also discusses answers to 9 objections and the idea of a “child machine” that is raised by education.

What we still don’t know:We have not confirmed on this site who first used the name “Turing test”, or when.

Neurosurgeon Jefferson’s lecture: only then “could we agree that machine equals brain”

Geoffrey Jefferson, professor of neurosurgery at the University of Manchester, objected to equating calculating machines with the brain in a lecture titled “The Mind of Mechanical Man”. He said that a machine could not be accepted as equal to a brain unless it wrote a sonnet (a 14-line poem) or a concerto because of thoughts and emotions it felt itself, and was also aware that it had written it. In his conclusion he voiced concern about the new danger of personifying machines.

What we still don’t know:Even if machines come to write poems and music, there is no known way to check from outside the conditions Jefferson set (whether it created from feelings it felt, and whether it knows the work is its own).

Turing’s forecast: “in about fifty years' time ... 70 per cent chance ... after five minutes”

In his 1950 paper, Turing set down his own forecast. In about 50 years, he wrote, computers could be made to play the imitation game well, and an average interrogator would have no more than a 70% chance of identifying correctly after 5 minutes of questioning. In the same paragraph he also wrote that by the end of the century the use of words and people’s ideas would have changed, so that one could “speak of machines thinking” without being contradicted.

What happened next:According to a survey paper from 2000 (Saygin et al.), no program had yet won the grand prize in the contest with prize money that had been held since 1991 (the Loebner Prize), and the records show that the machines were usually spotted quickly. In other words, in the year of the forecast, it had not come true in the form predicted. Some said the results of the 2000 contest “shows Turing’s prediction to have been in error”, but in the same year, 2000, Copeland wrote that “‘About fifty years’ does not mean ‘exactly fifty years’”. Then in March 2025, researchers at a US university (UC San Diego) published in a paper (arXiv) the results of an experiment in which an interrogator chatted for 5 minutes with a human and a machine at the same time. Of two large language AIs told to play the part of a human, one (GPT-4.5) was judged to be the human 73% of the time and the other (LLaMa-3.1-405B) 56% of the time (since there were two choices, the interrogator correctly spotted the first one only in the remaining 27%). But this is the announcement of one research group, and we have not confirmed later evaluations on this site. The part about being able to “speak of machines thinking without expecting to be contradicted” has not been confirmed.

What we still don’t know:Whether a machine being judged human in the 2025 experiment means that it can “think” is not known (Turing himself, regarding the original question as not worth discussing, replaced it with the game).

Turing tells radio listeners that “at the end of the century ... extremely difficult to guess whether the answers” come from a person or a machine

Turing gave a talk on BBC radio in Britain called “Can Digital Computers Think?”. He said he thought a program that makes a machine think would be found someday, and forecast that by the end of the century it would be extremely difficult to tell whether the answers to questions came from a person or a machine. Right after, he added “This only represents my opinion; there is plenty of room for others.”

What happened next:According to a survey paper from 2000 (Saygin et al.), no program had by then won the grand prize in the contest with prize money (the Loebner Prize), and machines were usually spotted quickly. In 2025, university researchers published a paper on an experiment in which, in a 5-minute conversation, a large language AI was judged to be human more often than the actual human (for details, see → Turing’s forecast: in about fifty years…).

Turing: “at least 100 years” (a radio discussion)

In January 1952 on BBC radio, four people (Turing, the mathematician Newman, the neurosurgeon Jefferson and the philosopher Braithwaite) discussed “Can Automatic Calculating Machines Be Said To Think”. When Newman asked whether it would be “a long time from now ... stand any chance with no questions barred”, Turing answered “Oh yes, at least 100 years, I should say.”

What happened next:The target year has not come yet (awaiting the answer). In 2025 an experiment was published in a paper in which a large language AI was judged to be human at a high rate in the 5-minute conversation form (see → Turing’s forecast: in about fifty years…), but we have not confirmed results for the long form (a game played “with no questions barred”) on this site.

What we still don’t know:We have not been able to view the broadcast script (AMT/B/6) itself on this site. We have not checked whether the recording survives.

Turing voices a worry: “If a machine can think, it might think more intelligently than we do”

On the radio in 1951, Turing said that if a machine can think, it might think more intelligently than we do. He said that even if we could keep the machines in a subordinate position, for example by switching off the power, the human race would feel greatly humbled. In a lecture script from the same period, he first said, “for the sake of argument, that these machines are a genuine possibility”, and then wrote that the machines would soon outstrip our feeble powers and that we must expect the machines to take control at some point.

What we still don’t know:Whether machines will become more intelligent than humans, and what would happen if they did, is still not known. The worry of 1951 is being discussed in the same form today, in the fourth boom (this record does not compare it with today’s debate).

Shannon’s forecast: machines that translate, arrange music and reason are “possible developments in the immediate future”

At the start of his chess paper, Shannon said that research on chess could be a stepping stone toward solving similar problems. As examples he listed eight, including machines that design circuits, translate languages, decide military operations, assign instruments to a melody, and carry out logical reasoning, and wrote that all of them seemed likely to come in the near future.

What happened next:A small-scale demonstration of a machine that translates languages was given in January 1954, four years later (→ IBM and Georgetown University give a pu…), but later research fell short of expectations for a long time (→ Dostert’s forecast: in 5 years, perhaps…). Music composed by a computer was performed in 1956 (the University of Illinois museum’s account). A logical reasoning program was built in 1955–56 (see the record of the Logic Theorist).

The Electrotechnical Laboratory builds a prototype of Japan’s first automatic calculator, the ETL Mark I (relay type)

The national laboratory Denki Shikenjo (its name in 1976 was Denshi Gijutsu Sogo Kenkyujo, the Electrotechnical Laboratory) built a prototype of Japan’s first digital automatic calculator, the ETL Mark I, using relays (electromagnetic switches) from telephone exchanges. The circuits were designed with a theory of logical mathematics devised within the laboratory. Following this success, the ETL Mark II, a practical machine using more than 20,000 relays, was completed in 1955 and was used for about 10 years.

Bunji Okazaki of Fuji Photo Film completes FUJIC, the first electronic computer to run in Japan

Designing lenses required calculating thousands of light paths. Bunji Okazaki of Fuji Photo Film got the idea of developing an electronic computer after reading an article in the 1948 magazine “Kagaku Asahi” about IBM’s calculator SSEC. Working almost alone for 7 years, he built FUJIC, an electronic computer with about 1,700 vacuum tubes. He showed it running in November 1955 and completed it in March 1956. It did lens calculations about 2,000 times faster than calculating by hand.

Eiichi Goto, a graduate student at the University of Tokyo, invents the “Parametron”, a computing component unique to Japan

Eiichi Goto, a graduate student in Hidetoshi Takahashi’s laboratory at the University of Tokyo, invented a new component for expressing 0 and 1, the “Parametron”. It makes use of the fact that the oscillation of a circuit of a coil and a capacitor settles into one of two states (the phase is either 0 or 180 degrees). At the time, research and development of parametrons was also going on at Nippon Electronic Measuring Instruments, the Nippon Telegraph and Telephone Public Corporation, Kokusai Denshin Denwa, Hitachi, Fujitsu, NEC and others, and at the University of Tokyo the parametron computer PC-1 was completed in 1958.

Ryoichi Yazu develops and sells Japan’s first mechanical desktop calculator, the “Jidosanban” (automatic abacus)

Ryoichi Yazu researched on his own and developed the “Jidosanban” (automatic abacus), a gear-driven calculator that takes in numbers using the same idea as the abacus. He obtained a patent in 1903 and put it on sale. With one cylinder and 22 gears it could add, subtract, multiply and divide. It was expensive at 250 yen per unit, but about 200 units were sold to government offices and others. During his research, Mori Ogai (Mori Rintaro, then head of the medical department of the 12th Division in Kokura) introduced him to a professor at Tokyo Imperial University and supported the development.

Osamu Tezuka’s “Tetsuwan Atom” (Astro Boy) begins serialization; the birthday in the story is “April 7, 2003” (translated)

Osamu Tezuka’s manga “Tetsuwan Atom” (Astro Boy) began serialization in the Kobunsha magazine “Shonen”. Atom is a boy robot with a heart, born from a supporting character in the earlier work “Atom Taishi” (Ambassador Atom, 1951). The story begins on April 7, 2003, in the 21st century, when Dr. Tenma, the director of the Ministry of Science, builds a robot that looks just like his son who died in an accident. On the real April 7, 2003, there were events such as newspaper features and the handing out of extra editions as “Atom’s birthday” (translated) (announcement by Sony Pictures).

What we still don’t know:We could not confirm from the official site and Sony Pictures’ announcement in which work and which episode the date “April 7, 2003” (translated) was first drawn (from the very start of the 1952 serialization, or in a later episode).