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1. The Game Of The Century

From linhares, 2 years ago

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Slide 1: “They say that lightning never strikes the same place twice but with Joost’s founders it could well become three in a row in terms of phenomenal startups.” TechCrunch http://www.techcrunch.com/2007/06/15/embedded-joost-will-change-the-market/

Slide 2: 2001 In 2002, the Kazaa Web site and logo was sold to Sharman Networks Ltd., which is incorporated on the island of Vanatu near Australia.

Slide 3: 2003

Slide 4: 2006: Joost 1.000.000 beta users 215 Channels 9208 Programs

Slide 5: Niklas Zennström & Janus Friis

Slide 6: “Lightning doesn’t strike twice” They’re thinking different! In the web, running under TCP-IP, data has a physical address. But to their fasttrack peer-to-peer technology, DATA has no physical address!

Slide 7: I invite you to think different.

Slide 8: I invite you to think what may be, perhaps, the next TCP-IP.

Slide 9: Organizing principles of cognitive technology: the game of the century Alexandre Linhares http://www.capyblanca.com http://www.intuition-sciences.com

Slide 10: All that fun in the XXth century! • Transistor and the computer revolution • DNA race • Space race • Nuclear race

Slide 11: Even more fun in the XXIth century! • Nanotechnology • Clean energy (or asphyxia) • The cognitive technology race …& the unknowns

Slide 12: A large-scale theory of the human brain • The cortical algorithm, or • fluid concepts evolving.

Slide 13: Our heroes

Slide 15: Kasparov once said “You have to have good enemies. I was lucky because I had Karpov.”

Slide 16: Our competitors

Slide 17: A declaration of War! …so, mr. Jeff Hawkins, can we be your worst enemies, please?

Slide 18: Science • Daniel Kahneman • Shane Frederick • Doug Hofstadter • Jeff Hawkins • Gerg Gigerenzer • Gary Klein • Bechara & Damasio • Intuition, Decision, Reason, Economics, Psychology, Computer Science, etc…

Slide 19: Linguists: syntax & semantics

Slide 20: Vision: 2D, 2½D, 3D sketches

Slide 21: AI: Minsky’s Frames

Slide 22: Neuroscience: huge number of studies, but no attempt at a large-scale theory

Slide 23: Hawkins 3 criteria for a theory • Time: brains process rapidly changing streams of information; there is nothing static about the brain • Feedback: the brain is “saturated with feedback connections” (p.25), some places with 10 times more connections going towards the input than from the input. • The brain is organized around a “repeating hierarchy”. This structural design seems important.

Slide 24: Current neural networks • Have usually three layers (disrespecting the complex design of the brain) • Do not process rapidly changing information, but only static patterns • Do not have feedback (even backpropagation does not count—since it’s bound only to a “learning phase”)

Slide 25: Is the brain modular? It seems to be. If you have a stroke in • Right parietal lobe, you can lose your ability to perceive (or conceive) anything on your left side; • Broca’s area: you can lose ability concerning the rules of grammar • Fusiform gyrus: lose ability to recognize faces (p.44)

Slide 26: However… • “The same layer, cell types, and connections exist thoughout”. (p.51) • “Newborn ferret brains can be rewired—so that they “see” with the “hearing” area of the brain” (~p.54) • Rats can be surgically rewired so that “pieces of [their] visual cortex [process] touch, instead of vision”. (~p.54)

Slide 27: What can we learn from this?

Slide 28: 1. Neuroscientists are evil. They get small, defenseless creatures, rewire their brains, and have a lot of fun doing these nasty things.

Slide 29: 2. The brain is NOT modular; it is plastic, and reorganizes rapidly to fit new incoming stimuli. “Congenitally blind adults use the [area] which ordinarily becomes dedicated to vision to read braille.” (p. 54) Why not the area dedicated to touch? Because “cells were not born to specialize in vision or touch or hearing.” (p.54)

Slide 30: The declaration of independence reads “all men are created equal” This is a declaration of functional independence that reads “all cells are created equal”

Slide 31: BUT WAIT! This can’t be right! Because if it were, then we could create new senses, based, for example, on radar technology.

Slide 32: Actually, we can. Paul Bach y Rita (U of Wisconsin) has helped blind people to see by linking a small camera with a chip on their tongues. Visual images are translated to pressure intensities, pixel by pixel, and the brain, over time, learns how to project “sensations in the tongue to images in space” (p. 61)

Slide 33: But wait! What this means is that the brain does not care which area is processing which type of information. The areas are function- independent. They can all implement the same functions. They work under the very same principles. They process information the same way. They implement one algorithm.

Slide 34: This algorithm – this information-processing mechanism – is our objective. We’re so close, and yet so far… Have you ever solved a Rubik’s cube?

Slide 36: I think we’re 5 or 6 moves away from solving this Rubik’s cube, of finding out the nature of this “neocortical algorithm”. So things look like a mess now; but if we get some steps right, we may solve it. What is the rule, then, for playing this game?

Slide 37: CHANGE! We must be able to implement things in such a way that everything and anything can change, and it is easy to do so. This is why this is also a course on software design. Good design enables change.

Slide 38: Software design 1. Closed for modification. The framework should, obviously, be closed for modification, once ready. This means that there must be a core set of underlying mechanisms which should not need to change in any other domain. This leads to the second requirement: 2. Open for extension. The framework, though having a closed, fixed, core, should be extensible, and applicable to new domains. This is obtained through inheritance, composition, loose coupling, the Hollywood principle, and so forth.

Slide 39: Software design 3. Information efficiency. It should be relatively easy to describe, in a high level, the workings of each part of the system. It should be possible for an astute observer to implement on their own the same ideas without having to look at our actual code. 2. Elegant implementation. This is a hard to define one. The system should be elegant, in the sense of providing all needed functionality, all the while maintaining a sense of simplicity and neatness. Beauty is achieved when everything is essential and nothing else is required.

Slide 40: Software design 5. Clean code. The code should be readable and understandable, without need for heavy (or even not-so- heavy) refactoring or heavy commenting. 6. A test history kept at each step. So that others may follow a step-by-step approach to implementation and be certain they're on the right track, tests for each major class should be preserved, and maintained even in the first executable version of NUMBO. 7. No globals. There is good evidence that there are no global variables in either the brain or the mind. So alternative approaches to global variables (such as temperature, the obvious candidate) should be strived for.

Slide 41: How does the brain get its job done?

Slide 42: How does the brain “see”, if it’s dark inside? How does the brain “hear”, if it’s silent inside? After information is fed “inside”, it starts to be processed. There are no images anymore, there are no sounds anymore, only information being processed, only number-crunching. The brain processes information, but…

Slide 43: The brain is not a computer …because the brain processes information, people have compared it to a computer, but that is misleading…

Slide 44: The brain is not a computer The brain is not a CPU The brain is memory; a machine to predict memory.

Slide 45: So the brain is like computer memory? NO. The brain is about “analogical memory”. It is about “invariant representations”.

Slide 46: The memory-prediction framework • Surprises get your attention • Understanding is about “generating expectations”, about “a state of meaningful anticipation”

Slide 47: Invariant representations & analogies Two examples: • How many daddies do I have? • Chess [From A. Linhares & P. Brum (2007) Understanding our understanding of strategic scenarios: what roles do chunks play? To Appear in Cognitive Science.]

Slide 48: Invariant representations & analogies How many daddies do I have?

Slide 49: Invariant representations & analogies Linhares and Brum (2007) to appear in Cognitive Science.

Slide 50: Invariant representations & analogies Linhares and Brum (2007) to appear in Cognitive Science.

Slide 51: Invariant representations & analogies Linhares and Brum (2007) to appear in Cognitive Science.

Slide 52: Invariant representations & analogies Linhares and Brum (2007) to appear in Cognitive Science.

Slide 53: This time, the science and the technology are coming together

Slide 54: Entrepreneurship • Is it possible to develop this technology? • Is it possible to create valuable applications? • Is it possible to succeed in Brazil?

Slide 55: Is it possible to develop this technology? 1. It will be hard; we are certainly close, but a Rubik's cube looks very messed up some steps prior to completion 3. Imagine the early days of TCP/IP; that’s where we’re going, but this time, there are ample applications waiting

Slide 56: Is it possible to create valuable applications? Anything that’s hard to do with computers and easy to do by humans

Slide 57: Is it possible to succeed in Brazil? • The major cost is Diet Coke & Pizza • Can we beat our competitors? – Will our systems pass the “do not suck” test? • The VCs are arriving

Slide 58: Draper Fisher Jurvetson Enters Brazilian Market “As part of the agreement the two new partners will also launch a $100 million fund, DFJ FIR Brazil Fund II, targeting offshore investors wanting to invest in Brazilian companies in high-growth industries.” DivX, Skype, Mobile 365, and Baidu

Slide 59: Summary 1. Welcome to the race for cognitive technology 2. We will search for the central organizing principles of the human mind 3. The same thing is going on all over the cortex 4. The brain processes information, but it’s not a CPU 5. The brain is a machine to predict analogical memories 6. Where are we in this race?

Slide 60: Image credits Mad scientist: http://en.wikipedia.org/wiki/User:J.J. Dendrites Merge: http://www.flickr.com/photos/neurollero/15002021/in/set-366106/ Jeff Bezos: Associated Press/Ted Warren Skype founders: http://www.skype.com