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In contrast to the IAS experiments, in which the organisms consisted solely of genetic code, the Tac-Tix experiments led to “the formation of non-genetic numerical patterns characteristic for each symbioorganism.
In biology this would be comparable to a world in which “the genetic material got into the habit of creating a body or a somatic structure only when a situation arises which requires the performance of a specific task (for instance a fight with another organism), and assuming that the body would be disintegrated as soon as its objective had been fulfilled.”
so the physical form is just a temporary structure
but knowledge of Barricelli’s experiments effectively disappeared through not being referenced in Arthur Burks’s compilation of von Neumann’s Theory of Self-Reproducing Automata, the authoritative text.
“I think his contributions to understanding genetic recombination in phages and bacteria, where his mathematical abilities could have been helpful, weren’t helpful,” says Frank Stahl, one of the critical reviewers, “because he came to the field with an idea of cherry-picking evidence that would support his view on what went on four billion years ago.”
Despite obvious dangers, most cells have maintained the ability to read gene sequences transferred from outside the cell. This vulnerability is exploited by malevolent viruses—so why maintain a capability that has such costs? One reason is to facilitate the acquisition of new, useful genes that would otherwise remain the property of someone else.
Life evolved, so far, by making use of the viral cloud as a source of backup copies and a way to rapidly exchange genetic code.
Alan Mathison Turing was born at Warrington Lodge, London, on June 23, 1912, to Julius Mathison Turing, who worked for the Indian Civil Service, and Ethel Sara Turing (née Stoney), whose family included George Johnstone Stoney, who named the electron, in advance of its 1894 discovery, in 1874.
David Hilbert, whose ambitious program of formalization set the course for mathematics between World War I and World War II. The Hilbert school believed that if a proposition could be articulated within the language of mathematics, then either its proof or its refutation could be reached, by logic alone, without any intervening leaps of faith. In 1928, Hilbert posed three questions by which to determine whether an all-encompassing mathematical universe could be defined by a finitary set of rules: Are these foundations consistent (so that a statement and its contradiction cannot ever both be
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In the spring of 1935—at the time of von Neumann’s visit to Cambridge—Turing was attending Max Newman’s lectures on the foundations of mathematics when the Entscheidungsproblem first attracted his attention. Hilbert’s challenge
“It is possible to invent a single machine which can be used to compute any computable sequence,”
Turing was able to construct, by a method similar to Gödel’s, functions that could be given a finite description but could not be computed by finite means.
“It is difficult today to realize how bold an innovation it was to introduce talk about paper tapes and patterns punched in them, into discussions of the foundations of mathematics,
why exactly was tape logic so critical. mechanizing proofs?
Before Turing, things were done to numbers. After Turing, numbers began doing things. By showing that a machine could be encoded as a number, and a number decoded as a machine, “On Computable Numbers” led to numbers (now called “software”) that were “computable” in a way that was entirely new.
was using numbers as machines accidentally leading to instruction sets?
ingenuity in encoding a message can resist a large amount
Turing and von Neumann were as far apart, in everything except their common interest in computers, as it was possible to get. Von Neumann rarely appeared in public without a business suit; Turing was usually unkempt. “He tended to be slovenly,” even his mother admits.40 Von Neumann spoke freely and with great precision; Turing’s speech was hesitating, as if words could not keep up with his thoughts. Turing stayed in hostels and was a competitive long-distance runner; Von Neumann was resolutely nonathletic and stayed in first-class hotels. Von Neumann had an eye for women, while Turing
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Turing’s design was captured in his “Proposed Electronic Calculator,” written for the National Physical Laboratory in the brief interval between being shown the EDVAC report in September 1945 and the end of the year. He delivered a complete description of a million-cycle-per-second Automatic Computing Engine (ACE), accompanied by circuit diagrams, a detailed physical and logical analysis of the internal storage system, sample programs, detailed (if bug-ridden) subroutines, and even an estimated cost of £11,200.41 As Sara Turing later explained, her son’s goal was “to see his logical theory of
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Turing’s approach to machine intelligence was as unencumbered as his approach to computable numbers ten years before. He continued, once again, from where Gödel had left off. Does the incompleteness of formal systems limit the abilities of computers to duplicate the intelligence and creativity of the human mind? Turing summarized the essence (and weakness) of this convoluted argument in 1947, saying that “in other words then, if a machine is expected to be infallible, it cannot also be intelligent.”47 Instead of trying to build infallible machines, we should be developing fallible machines
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hmm
Digital computers are able to answer most—but not all—questions stated in finite, unambiguous terms. They may, however, take a very long time to produce an answer (in which case you build faster computers) or it may take a very long time to ask the question (in which case you hire more programmers).
search engine learns from the collective human mind, all at once. Every time an individual searches for something, and finds an answer, this leaves a faint, lingering trace as to where (and what) some fragment of meaning is. The fragments accumulate and, at a certain point, as Turing put it in 1948, “the machine would have ‘grown up.’
except when search ends up being biasdd because it gives you only what you LIKE
now the Institute’s ambivalence toward the computer project, and lingering divisions over the Oppenheimer security hearings, began to wear down Johnny as well.
wow so yhe computerproject was jn trouble. or dead
Bigelow received job offers from UCLA, RAND, NYU, RCA, the University of Michigan, Hughes Aircraft, the Defense Mapping Agency, and even the Albert Einstein College of Medicine—all of which he refused. “Julian was a man who would take his soldering iron in there and just do it,” says Martin Davis. “He would have been much better off if he had never got that tenure [at IAS]. He would have got a job in industry, where he really would have flourished.”33 The Institute could not force him to resign, but they refused to increase his salary.
In the age of vacuum tubes, it was inconceivable that digital computers would operate for hundreds of billions of cycles without error, and the future of computing appeared to belong to logical architectures and systems of coding that would be tolerant of hardware failures over time. In 1952, codes were small enough to be completely debugged, but hardware could not be counted on to perform consistently from one kilocycle to the next. This situation is now reversed.
Self-reproduction is an accident that only has to happen once.
things that can maks copies of themselves , producing actual ogher things and not jusr information itself
A life form that assumes digital representation, for all or part of its life cycle, will be able to travel at the speed of light. As artificial intelligence pioneer Marvin Minsky observed on a visit to Soviet Armenia in 1970, “Instead of sending a picture of a cat, there is one area in which you can send the cat itself.”
Subrahmanyan Chandrasekhar
By mid-1953, five distinct sets of problems were running on the MANIAC, characterized by different scales in time: (1) nuclear explosions, over in microseconds; (2) shock and blast waves, ranging from microseconds to minutes; (3) meteorology, ranging from minutes to years; (4) biological evolution, ranging from years to millions of years; and (5) stellar evolution, ranging from millions to billions of years. All this in 5 kilobytes—enough memory for about one-half second of audio, at the rate we now compress music into MP3s.
Shock waves are produced by collisions between objects, or between an object and a medium, or between two mediums, or by a sudden transition within a medium, when the velocities or time scales are mismatched. If the difference in velocity is greater than the local speed of information, this propagates a discontinuity, a sonic boom being the classic example, as an aircraft exceeds the speed of sound.
Among the computers populating this network, most processing cycles are going to waste. Most processors, most of the time, are waiting for instructions. Even within an active processor, as Bigelow explained, most computational elements are waiting around for something to do next.
What the Americans termed “artificial intelligence” the British termed “mechanical intelligence,” a designation that Alan Turing considered more precise.
IBM soon became the dominant force in digital computing and, beginning with von Neumann’s one-day-per-month consulting contract, hired much of the talent that had accumulated at the IAS.
Rosenberg was offered an IBM Fellowship in 1969, which he declined, explaining that “the company was too large and corrupt.”
Einstein, in appreciation, granted Rosenberg a wide-ranging and candid interview, which Rosenberg recorded on high-fidelity equipment, but will not release. “Einstein said it must never be made public,” he explains.
had the highest hopes for, had been so misused. After their abortive venture with the Selectron, RCA never again took a decisive lead in digital computing, devoting their resources to commercial television and to their broadcasting spinoff, NBC.
Near the end, von Neumann, who could no longer work entirely without notes, asked one of his visitors, identified only as “JmcD,” for “a note regarding what we talked about last Wednesday,”
Richtmyer, like Bigelow, was surprised that computing remained largely stuck where von Neumann had left off, with machines and codes growing in power and complexity but not in the fundamental way the systems worked. “A curious phenomenon that has accompanied the development of software is a tendency for the hardware to become dependent on it,” he observed in 1965.52
