Brand-turing_short

Report
Overview and Summary
Michael Brand
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Manchester town hall
City &
country crests
Stars &
planets
depicted in
mozaic
Color-lit
16-foot
pipe organ
Victorian-era
neo-gothic
architecture
The 12
“Manchester
Murals”
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The Manchester baby
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Manchester coding
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Manchester carry chain
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◦ World’s first stored-program computer (1948)
◦ Followed by Manchester Mark-1 (first w/ fast randomaccess two-level store) (1949)
◦ Prototype for Ferranti Mark 1 (first commerciallyavailable general-purpose computer) (1951)
◦ Phase encoding, developed for Manchester Mark 1
◦ Used in Ethernet, RFID, etc.
◦ Fast adder with minimization of gate numbers
Virtual memory
Compiler compiler
◦ For the Ferranti Atlas (1962)
Gay village
Apple
University
of
Manchester
Pablo Picasso
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Turing’s official biographer
In addition to
◦ On Computable Numbers, with an application to the
Entscheidungsproblem, Proc. Lond. Math. Soc. (2) 42 pp
230-265 (1936); correction ibid. 43, pp 544-546
(1937).
 Introduction of “The halting problem” (Universal computing)
◦ Computing Machinery and Intelligence, Mind 49, pp
433-460 (1950)
 Introduction of “The Imitation Game”/”Turing test” (AI)
◦ The Chemical Basis of Morphogenesis, Phil. Trans. R.
Soc. London B 237 pp 37-72 (1952)
 Biological theory of individuation, symmetry-breaking and
pattern-forming
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There is also
◦ Intelligent Machinery (Written 1948. Unpublished)
◦ Reviews (Charles Darwin (NPL director)):
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“A bit thin for a year’s time off”
“A schoolboy’s essay”
“not suitable for publication”
“smudgy”
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Logic based approach to problem-solving
Intellectual activity is primarily search
Genetic algorithms (“evolutionary search”)
Neural networks (“unorganized machines”)
An early form of the imitation game.
A blueprint for connectionism
◦ It contained:
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Turing award winner: nondeterminism
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Turing and computability
◦ On Computable Numbers, with an application to the
Entscheidungsproblem, Proc. Lond. Math. Soc. (2)
42 pp 230-265 (1936); correction ibid. 43, pp 544546 (1937).
◦ The Word problem in Semi-Groups with
Cancellation, Ann. of Math. 52 (2), pp 491-505
(1950)
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Solved Hilbert’s 10th problem
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Turing and number theory
0
Critical line
Values on
critical line
can be
calculated as
real-valued
integral.
Approximate
and count
sign changes
for zeroes.
Critical strip
◦ Turing and the Riemann Hypothesis
ζ
1
“Turing’s
method”=
calculate total
number of
zeroes in
critical strip
via
approximated
integral.
“Turing’s method” is still in use
today. His (many) other
innovations on RH have since
been superseded. Examples
follow.
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Improved integral calculation for counting of
zeros on the critical line.
Improved finding places for suspected signchanges (a.k.a. Gram points)
Improved bounds for Skewes’s number (first
case of π(x)>Li(x). See Littlewood (1914))
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Systems of logic based on ordinals, Proc.
Lond. Math. Soc (2) 45 pp 161-228 (1939)
[was also Turing's Princeton Ph.D. thesis
(1938)] includes, under section “3. Number
Theoretic Theorems” a proof that
RH   02
◦ thus placing RH for the first time in the Arithmetical
Hierarchy.
◦ Kreisel (1958) later lowered this to
RH  10
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Automated calculation
◦ “tide-predicting machine” (1939 application to the
Royal Society. Never built due to work on Enigma)
◦ First to calculate zeroes mechanically (Mark-1)
“The calculations had been planned some time in
advance, but had in fact to be carried out in great haste.
If it had not been for the fact that the computer remained
in serviceable condition for an unusually long period from
3 p.m. one afternoon to 8 a.m. the following morning it is
probable that the calculations would never have been
done at all. As it was, the interval 2π.632 < t < 2π.642
was investigated during that period, and very little more
was accomplished.”
◦ Also: invented LU decomposition
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Turing award winner: RSA, differential
cryptanalysis
Turing and Enigma
Major mistakes (G):
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Usually, only inner rotor moves
Most strength is in plug-board, which can be bypassed
Plug-board connection is trivial
No fixed points
Message-keys were chosen badly
Operator errors (see Tutte’s reconstruction of Tunny)
Never willing to entertain suspicions of breakability
Major mistakes (B):
◦ Never guessed plug-board connection
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“The mythical man-month”; Turing award winner:
computer architecture
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Turing and the Pilot ACE
Turing’s 1945 proposal (as compared with EDVAC)
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and yet, had little impact on computing history.
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◦ is detailed to the register level (more than von Neumann’s
report)
◦ is more general-purpose
◦ 5x faster
◦ ¼ electronic equipment
◦ 3-op packed instructions (plus a “next” address)
◦ Fewer instruction fetches (obsoleted by larger memory)
◦ Optimal next instruction placement in delay lines
◦ Supports variable-length block transfers
◦ Punched card I/O directly attached.
◦ Why?
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Assumption: HW dear; people cheap
11 Central registers, each with its own
behaviors (properties, side-effects, implied
operators, implied targets, multiple names –
no accumulator)
No generic multiplication, no conditional
branching. Works in backwards-binary
No random access
No subroutine support
= A beast to program
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Turing award winner: model checking
Formal verification
Turing:
◦ Of course entscheidungsproblem, but also:
◦ Checking a Large Routine, Paper for the EDSAC
Inaugural Conference, 24 June 1949. Typescript
published in Report of a Conference on High Speed
Automatic Calculating Machines, pp 67-69.
 Proof of termination by transfinite induction (presaging
Floyd (1967))
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View as a graph problem
Formal languages for model definition (based
on temporal logic)
Symbolic model checking (storing partial
states)
Bounded model checking (Use SAT solvers to
consider the first k steps)
Node clumping
◦ CEGAR: Counter-example guided automatic
abstraction
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Turing award winner: Quicksort, CSP
Can computers understand their own
programs?
Turing: Self-simulation + verification + AI
Suggested alternate wording: can a computer
program provide its programmer with
pertinent information about itself?
Where the positive answer is already in use:
◦ Programs can check for buffer overflows
◦ Can generate test-cases for recent changes
◦ Can pinpoint cases where changes can make
programs slower
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Former world chess champion;
2½-3½ against “Deep Blue”
Turing’s paper machine
Turing and chess
◦ At Bletchley park: Hugh Alexander, James Macrae Aitken
◦ Turing’s Running Chess
◦ Early imitation game
◦ 15 seconds of silence?
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(1948) Turing designed the first chess algorithm. He
hand-simulated it (and lost) in a match against Alick
Glennie
Kasparov’s team implemented the algorithm. Found that
Turing inadvertently alpha-beta pruned.
◦ Changing the result in 10 of the game’s 24 moves.
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Today: “Advanced Chess” (GM+Comp vs. GM+Comp)
◦ Kasparov: Cooperation is key.
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”The algorithmic beauty of sea-shells”
Turing and Morphogenesis
Turing: inhibitor w. longer range (diffuses)
Activator
Inhibitor
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Today mainstream, but initial scepticism
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Stochastic results – but live organisms not so
initial state nonsymmetric
cannot produce axial patterns
negative concentrations in equations (fixed by
nonlinear reactions)
Explains a wide variety of phenomena
Hydra
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Periodicity
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Gradients
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Oscillations
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Phyllotaxis
centralization
◦ “...but with three or more morphogens it is possible
to have travelling waves. With a ring there would be
two sets of waves, one travelling clockwise and the
other anticlockwise. There is a natural chemical
wave-length and wave frequency in this case as well
as a wave-length; no attempt was made to develop
formulae for these...”.
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“Father of the Internet”, ICANN chair, Google VP
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IP-enabled surfboards, light-bulbs and toasters
Sensor-nets even in self-driving cars & wines
Bit-rot hazard → legal issues of IP
Data availability → privacy? new social norms?
techno+academic+legal+civil society+industry
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Interplanetary Internet
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“Watson”
“Jeopardy!”: Broad domain, speed, precision,
accuracy estimate
Ambiguity, anaphora resolution
Use of existing resources, no spec data
Sentence parsing + statistical aggregation +
context
Score competing hypotheses based on
evidence + recursively
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Was known as Cottonopolis
Presidential Rhyme Time: “Barack’s Andean pack
animals“
◦ Obama’s Llamas
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Fables & Folklore: “Gerda tries to rescue Kay from this
Hans Christian Andersen title royal”
◦ The Snow Queen
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The first named character in “The Man in the Iron
Mask” also to appear in the author’s previous work.
◦ D’Artagnan
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Submitted to Lincoln in June 1964 by the secretary of
treasury and accepted
◦ Offer of resignation.
 Or was it a friend request?
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AI+Robotics; past president of RoboCup
Learning by perception+cognition+action →
feedback. Learning by reusing solutions (“by
analogy”)
◦ Turing (Intelligent Machinery): computers apt in (i)
games, (ii) language, (iii) translation, (iv)
cryptography, (v) mathematics, of which the most
difficult is (ii) and requires sensory input and
locomotion. (“Roaming the countryside”)
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centrally/noncentrally controlled
Model world, plan to the goal
(probablistic, physics-based,
variable-detail), update on new
info
Add artificial goals to
heuristically approximate pruned
states
Purposeful perception: little of
the image gets processed.
Glass corridor
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Companion mobile robots
Active since 2009 & 2010 rsp.
Navigate Gates Hillman Center(*)
using the Kinect depth-camera,
WiFi, and/or LIDAR
Proactively ask for help
◦ Ask humans to press elevator buttons
◦ Follow humans (and each other) along
glass corridor
217,000-square-foot,
9 floors
(*)
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Turing award winner: PAC, #P, holographic
reductions, CF parsing, UniqSat∈P⇒RP=NP
Quantifying evolution
Basic question: humans have 3⋅109 base
pairs. How does evolution get there without
4^that time?
What are the possibilities for protein
expression? Algorithms for next generation?
How does evolution navigate the search
space?
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Samson Abramsky (game semantics, domain
theory): What is a process? (which two are equiv?)
Carole Goble (eScience, grid computing):
Universal social machines?
Manuella Veloso: Universal robots?
Ron Brachman (description logic; AI; VP Yahoo!
Labs): If intelligence is like athleticism in that
there is no single sport metric, what is our aim?
Moshe Vardi (model checking, database theory,
constraint satisfaction): Does the future need us?
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“Elephants don’t play chess”, iRobot
◦ Turing never meant the imitation game
as a test. It was meant to show the
theoretical possibility (nullifying the
emotional weight we put on
“intelligence”). He also suggested a “men
vs. women” variation (which people are
not good at) and wondered whether
computers can be told from humans by
their chess-play (which they normally
can).
◦ “Intelligence” is the appearance of
intelligence, which is in the ability to
interact. People love to
anthropomorphize (incl. other people).
Kismet
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Steve Furber (BBC micro; ARM 32-bit RISC
microprocessor): Higher intelligence is an
unnatural top layer over human intelligence. We
over-assume about our own intelligence. The
most rewarded ability is to lead a game of
football. Our assumed intelligence created a
barrier that makes it difficult for us to build AI.
Manuella Veloso: Intelligence is about physical
interaction, not abstract cognition. Learning is
also memory, not just adapting classification
parameters.
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Turing’s criteria for “winning” the imitation
game is a 30% success rate at fooling the
judge after a 5 minute conversation.
On the day of the centenary (June 23rd) the
biggest Turing test ever was staged at
Bletchley Park.
13-year-old Eugene Goostman managed to
fool judges 29% of the time.
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Donald Knuth
Roger Penrose
Andrew Yao
George Ellis
Martin Davis
Samuel Klein (Wikimedia Foundation)
...
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questions?

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