Turing Centenary Conference (Manchester)

22-25 June 2012

Overview and SummaryMichael Brand

Manchester town hall

Venue

The 12 “Manchester Murals”

Color-lit16-foot

pipe organ

Stars & planets

depicted in mozaic

City & country crests

Victorian-era neo-gothic

architecture

The Manchester baby◦ World’s first stored-program computer (1948)◦ Followed by Manchester Mark-1 (first w/ fast random-access

two-level store) (1949)◦ Prototype for Ferranti Mark 1 (first commercially-available

general-purpose computer) (1951) Manchester coding

◦ Phase encoding, developed for Manchester Mark 1◦ Used in Ethernet, RFID, etc.

Manchester carry chain◦ Fast adder with minimization of gate numbers

Virtual memory Compiler compiler

◦ For the Ferranti Atlas (1962)

Manchester and computing

Alan M. Turing (1912-1954)

Apple

University of

Manchester

Gay village

Computers are useless. They can only give you

answers.Pablo Picasso

Perspectives

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

Jack Copeland

There is also◦ Intelligent Machinery (Written 1948. Unpublished)◦ Reviews (Charles Darwin (NPL director)):

“A bit thin for a year’s time off” “A schoolboy’s essay” “not suitable for publication” “smudgy”

◦ It contained: 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

Jack Copeland (cntd)

Turing award winner: nondeterminism 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 544-546 (1937).

◦ The Word problem in Semi-Groups with Cancellation, Ann. of Math. 52 (2), pp 491-505 (1950)

Michael Rabin

Cri

tica

l st

rip

Solved Hilbert’s 10th problem Turing and number theory

◦ Turing and the Riemann Hypothesis

Yuri Matiyasevich

0 1

Cri

tica

l lin

e

Values on critical line can

be calculated

as real-valued

integral. Approximate and count sign

changes for

zeroes.ζ

“Turing’s method”=calculate

total number of zeroes in critical

strip via approxim

ated integral.

“Turing’s method” is still in use today. His (many) other innovations on RH have since been superseded. Examples follow.

Improved integral calculation for counting of zeros on the critical line.

Improved finding places for suspected sign-changes (a.k.a. Gram points)

Improved bounds for Skewes’s number (first case of π(x)>Li(x). See Littlewood (1914))

Some superseded achievements

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

◦ thus placing RH for the first time in the Arithmetical Hierarchy.

◦ Kreisel (1958) later lowered this to

Superseded achievements (cntd)

02RH

01RH

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)

◦ Also: invented LU decomposition

Superseded achievements (cntd 2)

“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.”

Turing award winner: RSA, differential cryptanalysis

Turing and Enigma Major mistakes (G):

◦ 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

Adi Shamir

“The mythical man-month”; Turing award winner: computer architecture

Turing and the Pilot ACE Turing’s 1945 proposal (as compared with EDVAC)

◦ 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.

and yet, had little impact on computing history.◦ Why?

Frederick P. Brooks

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

ACE peculiarities

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))

Edmund Clarke

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

Modern approaches to MC

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

Tony Hoare

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? (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.

Today: “Advanced Chess” (GM+Comp vs. GM+Comp)◦ Kasparov: Cooperation is key.

Gary Kasparov

”The algorithmic beauty of sea-shells” Turing and Morphogenesis Turing: inhibitor w. longer range (diffuses)

Hans Meinhardt

Activator Inhibitor

Today mainstream, but initial scepticism◦ 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

Morphogenesis (cntd)

Hydra

Periodicity

Gradients

Oscillations

Phyllotaxis

Morphogenesis (cntd 2)

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...”.

Turing’s forgotten result

Prospects

“Father of the Internet”, ICANN chair, Google VP

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

Interplanetary Internet

Vint Cerf

“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

David Ferrucci

Was known as Cottonopolis Presidential Rhyme Time: “Barack’s Andean pack

animals“◦ Obama’s Llamas

Fables & Folklore: “Gerda tries to rescue Kay from this Hans Christian Andersen title royal” ◦ The Snow Queen

The first named character in “The Man in the Iron Mask” also to appear in the author’s previous work.◦ D’Artagnan

Submitted to Lincoln in June 1964 by the secretary of treasury and accepted◦ Offer of resignation.

Or was it a friend request?

Jeopardy!

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”)

Manuella Veloso

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.

Solution? Soccer!

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

Practical? CoBots!Glass corridor

(*) 217,000-square-foot, 9 floors

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?

Leslie Valiant

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?

Panel: “Big Questions”

“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).

Rodney Brooks

Kismet

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.

Panel 2: “The Turing Test”

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.

Meanwhile – at Bletchley Park

Donald Knuth Roger Penrose Andrew Yao George Ellis Martin Davis Samuel Klein (Wikimedia Foundation) ...

Some of the many other people who presented

questions?

Thank you!