WHAT IS ARTIFICIAL

INTELLIGENCE?

CONTRADICTIONS

“Infinity is infinity but infinity doesn’t adequately

contain itself.”

Russell’s Paradox of “class of all classes which are

not members of themselves

Illustrated: Barber of Seville

Each man in town either shaves himself, or goes to the

barber

The barber shaves only those who do not shave

themselves

Who shaves the barber?

GÖDEL'S INCOMPLETENESS THEOREMS

Proved that the systems of mathematical logic are

flawed.

No matter how large you make your set of axioms,

in arithmetic there will always be statements that

are true, but cannot be proven so.

Another way of saying this, for us technology

managers: No matter how much data you have,

even infinitely many data bits, you cannot prove all

true statements.

FROM ESOTERIC TO CONCRETE - DISRUPTIVE

INNOVATION IN MATHEMATICS

Alan Turing – The Halting Problem

For mathematicians, how do you know if the problem

you are working on is inherently unsolvable (Hilbert’s

Second Problem), or extraordinarily difficult (Fermat’s

Last Theorem)?

In conceiving an answer, Turing turned to something more

basic: uncomputability. What are the limits of

computation? The machine he constructed, The Turing

Machine, was the conceptual creation of what we today

call the computer.

WHY DOES THIS MATTER?

Every single one of us will have our lives inexorably

and profoundly changed over the coming decades

by AI.

It is important because it tells us what AI is NOT.

Internet ≠ TV, only better

AI ≠ human intelligence, only better (perfect memory)

Establishes a respect for the AI technology, but a

deep and abiding admiration for the natural

technology of the human mind.

FROM IDEA TO INNOVATION

Innovation = Commercialization of Ideas. AI

developed only as an idea until the hardware could

catch up. Now, with the situations somewhat

reversed, funding is pouring into AI research.

DARPA’s CALO project in 2003

Trapit and SIRI

VOICE RECOGNITION-CHALLENGES

speaker dependence,

continuity of speech,

difficulty of identifying word boundaries - as in "youth in

Asia" and "euthanasia.”

vocabulary size

Large vocabularies cause difficulties in maintaining

accuracy, but small vocabularies restrict the speaker.

APPLE

>50,000 employees and with annual revenueapproaching $100 billion grow 60% a year

Multi-focused structure in which product,function, and geography are emphasized all atonce

Better alignment between functional and divisional goals

Simplicity is key.

It is deceptively straightforward with none of thedotted-line or matrixed responsibilities popularelsewhere in the corporate world

A corporate dictator who makes every critical decision(Steve Jobs)

APPLE

A cutting-edge startup rather than the consumer-

electronics behemoth

The attention to detail, the secrecy, the constant feedback

-- into processes

Passion for innovation and an uncompromising

commitment to bringing great products to market.

Smart technology also needs to be beautiful technology

HOW APPLE WORKS

Accountability from top on down

a series of weekly meetings

never any confusion as to who is responsible for what.

The "DRI" or directly responsible individual.

Ability to move nimbly

Ability to focus on just a few things at a time

Still a startup at heart

Most notably by putting small teams on crucial projects

Do-more-with-less mentality

HOW APPLE MANAGE

Value-driven business-model innovation

Smart technology (ipad, phone)

Voice recognition is a disruptive

technology, but they apply it as a sustaining

innovation

Acquired SIRI (2010) ability to correlate data

ability to interpret meaning

If improved upon,...

LESSONS FROM APPLE

Network Innovation

In pursuit of Simplicity

Fail Wisely

Not All Innovation is Equal

Innovation Doesn't Generate Growth. Management Does

GOOGLE’S VOICE RECOGNITION

Application

Simultaneous subtitle in video

Perspective

Translation

A supercar in Knight Rider

and Green Hornet

Searching by oral inputs

GOOGLE’S CHALLENGES

Challenges

Vocabulary

Accent

Automatic skip

Translation

MICROSOFT VOICE RECOGNITION

Windows Speech Recognition

empowers users to interact with

their computers by voice.

It was designed for people who

want to significantly limit their

use of the mouse and keyboard

while increasing their productivity.

MICROSOFT VOICE RECOGNITION

Schools-Teachers can use speech recognitions to

improve student’s second language.

Offices- People send email and do their projects

efficiency by speech recognition.

Research Center- Scientists improve

productivity by speech recognition.

Military-Commanders can control any

equipments easily and safety by speech

recognition.

MICROSOFT-FEATURES

Commanding "Say what you see" control applications and tasks,

such as formatting and saving documents; opening and

switching between applications; and opening, copying,

and deleting files; and browse the Internet by saying

the names of links.

Correction Efficiently fix incorrectly recognized words by selecting

form alternatives for the dictated phrase or word or by

spelling the word.

Interactive

tutorial

The interactive tutorial teaches people how to use

windows speech recognition and teaches system what

your voice sounds like.

Personalization The system keep adapting both your speaking style and

accent continually improves speech recognition

accuracy.

PROBLEMS AND CHALLENGES

FOR MICROSOFT

Problems-

1. Voice distinguish

2. Command’s error on system

Challenges-

1. How to develop a new smart system

2. Strengthen distinguish system

3. Operating speed.

COMPARISON

Managing Innovation

Potentially disruptive technologies used in a sustaining

innovation framework (ecosystem)

Apple

Product ecosystem- iPad

Google

Search ecosystem- Android

Microsoft

Windows ecosystem- Office Products

COMPARISON

KLINE: “SHARING THE CORPORATE

JEWELS”

"Strategic licensing is emerging against the backdrop of intensified efforts by

corporate America to maximize the return on its intellectual property assets,

which now account for 50% to 70% of the market value of all public

companies.“

“To judge from the results of such initiatives to date, the most powerful

benefits are economic. No company demonstrates this better than IBM, which

earned an astounding $1.7 billion from technology licensing in 2000 alone.

These revenues came with a 98% profit margin and accounted for roughly

20% of the company’s net income in that year.”

Imagine the possibilities Artificial Intelligence applications could have in this

regard.

THE FUTURE OF AI

Another DARPA creation, the internet, was in a similar

position, not too long ago.

Tim Berners-Lee’s World Wide Web

Netscape Browser

AI also needs the concurrent development of enabling

technologies, like: a semantically linked web, populated

with a web of things, and robotics.

Until then, this space is best doing a lot of the same as it

is doing now until such time as the disruptive technology

finds a model that can make it into a truly disruptive

innovation.