Managing Innovation Final Paper - Artificial Intelligence

7/29/2019 Managing Innovation Final Paper - Artificial Intelligence

1/27

ARTIFICIAL INTELLIGENCE, Applied:How Google and Apple are Managing Voice Recognition

Nick Timmons

Chih-Ying Lin - Jenny

Taghreed Hamdto

Cheng-Wei Fu - Josh

Ching-Wei Fang - Power

Sadullah Ozcan

University of Illinois - College of Business

BADM 514

12/12/2011


2/27

BADM 514Managing Innovation Professor Love

Team 5Artificial Intelligence Project Final Report Dec. 12, 2011

Page | - 2 -

Table of Contents

Executive Summary .................................................................................................................... - 3 -What is Artificial Intelligence? ................................................................................................... - 4 -From Idea to Innovation: Artificial Intelligence Applied ........................................................... - 9 -Voice Recognition, Google and Google Voice......................................................................... - 10 -Apple and SIRI ......................................................................................................................... - 15 -Disruptive and Sustaining Innovation... .................................................................................... - 20 -Within a Closed or Open System of Innovation ................................................................... - 22 -Conclusion ................................................................................................................................ - 26 -Resources Referenced ............................................................................................................... - 27 -


3/27



Page | - 3 -

Executive Summary

The co-founder of Google, Larry Page, said at the 2007 American Association for the

Advancement of Science conference that: We have some people at Google who are really trying

to build artificial intelligence and do it on a large scale. Its not as far off as people think.

Googles other founder, in the July 2009 MIT Technology Review article, Search Me, said:

Perfect search requires human-level artificial intelligence. Given Googles dominance of

search, when you hear its founders speak about perfect search requiring human-level artificial

intelligence and saying that Google is trying to build such a thing at a large scale, you know that

the concept is of the utmost future importance. Apple, for its part, is also in the game, having

purchased SIRI, the crown jewel of DARPAs CALO project, which at $200m stands as the

largest AI project ever undertaken to date. Given this state of affairs, it was therefore most

sensible to investigate the business case of Artificial Intelligence through the guise of a particular

application of it, called Voice Recognition, and how the worlds best internet company and the

worlds best technology company are each approaching innovation in this space. The two

companies both seem to be pushing this disruptive technology from within a sustaining

innovation paradigm, and what is most interesting is that Google and Apple are doing this in

diametrically opposed way. The former is operating under the open system of innovation,

whereas the latter is using more of a closed/open hybrid system. To round out the summary by

way of introduction to the paper, look at those first two quotes again. They might give rise to a

very salient and important question: Just what is Artificial Intelligence? In order to understand

the business case of commercializing the AI idea through a system of innovation, first we have to

deeply understand the technology itself, what it is, and what it is not.


4/27



Page | - 4 -

What is Artificial Intelligence?Ludwig Wittgenstein when asked about his Principle of Verification, said in reply,

Imagine that there is a town in which the policeman are required to obtain information from each

inhabitant, e.g. his age, where he came from, and what work he does. A record is kept of this information

and some use is made out of it. Occasionally when a policeman questions an inhabitant he discovers thatthe latter does not do any work. The policeman enters this fact on the record, because this too is a useful

piece of information about the man!

So, for us to understand Artificial Intelligence, it is imperative that we first understand just what

it is not. That might sound pointless, but what it is not tells us more about Artificial Intelligence

than anything else, because it allows us to truly relate AI to another kind of intelligence, human

intelligence. The point is to give us a deep abiding respect for the power of the human mind, and

just as importantly for the purposes of this report, how that respect of human intelligence and the

limitations of computing informs us as to ways we can use the technological innovations herein

for maximum societal benefit. Humans can better use AI technology by better understanding

how our own intelligence can be enhanced by intermingling it with AI. The best way humans

have discovered for applying technology for societys benefit is through the mechanisms of

markets. And the best way to study the specific technology in question, because it is so new, is to

analyze its most advanced application, Voice Recognition, through the lens of Apple and

Googles treatment of it. But again, this first requires understanding Artificial Intelligence as an

idea, and the history of its ideation.

The journey towards the discovery of Artificial Intelligence begins with the mathematical

investigation of infinity. Galileo once said, We are among infinites and indivisibles, the

former incomprehensible to our understanding by reason of their largeness, and the latter by their

smallness. The key here is that the greats of maths, as represented by Galileo, found the concept

of infinity, both the infinitely small and the infinitely large, to be incomprehensible. We, of finite

minds, simply cannot understand the Infinite. That fundamental idea of incommensurability, like


5/27



Page | - 5 -

that of a circle and a line, was at the heart of human thought about Infinity. And there the idea sat

for literally two and a half centuries, until Georg Cantor disrupted the world of mathematics with

his revolutionary proofs.

In short, Cantor proved that there is no greatest cardinality, through his famous diagonal

argument. Cardinality is a relatively simple math concept in set theory, and it is basically defined

as the number of numbers in a set. We if we were to define a set with a specific number of

elements, it would look like this: Set N = {0,1,2,3}, |S|= 4. The cardinality of that set is four,

because there are four numbers within Set N. So, then, a set with 7 elements would have a

greater cardinality than our Set N. Likewise with a set that

has 20 elements, or 20,124 elements. Cantor began his work

wondering about just how large infinity was? It took some

years until he made his breakthrough. To the right is his

Diagonal Argument. What he did was take the first set, and

set up a binary choice. Each element can either take on the

character of m or w. The first set is comprised of infinitely

many ms. The second is composed of infinitely many ws.

And the third is composed of an infinite rotation between the two. The fourth through eleventh

describe a pattern of how these infinite sets are each successively set up. If you continue

infinitely the pattern of sets, then it will always be possibly to make a set that is opposite to each

set element in the way described in the picture. Essentially, what this means is that, even with

infinitely many set of infinite elements, it will be possible to create a set which is comprised of a

combination which is not matched at all by any of the infinite sets. Without getting too deep, this

can be expressed thusly: || = ||. What this says is that the number of numbers


6/27



Page | - 6 -

between 0 and positive infinity is the same as the number of numbers between negative and

positive infinity. This is extremely counter-intuitive and hard to grasp because we are saying that

Infinity is infinity but infinity doesnt adequately itself. This throws up any infinite number of

contradictions.

Bertrand Russell, the British philosophical giant writer of thePrincipia Mathematica,

which was essentially about trying reduce all math to logic, felt that he had largely succeeded in

his quest, until he came to Cantor, whose discovery about the limits of math more or less crushed

the ultimate veracity of his grand work. Nevertheless, it was he who put the contradictions

thrown up into a very interesting sample paradox, called the Barber of Seville. Each man in a

small village town called Seville either shaves himself, or is shaved by the local barber if not.

The barber shaves only those who do not shave themselves. This is all fine, until he asks us the

question; Who shaves the Barber? The answer is a paradox whose genesis is in the proof that

there is no greatest cardinality. If the barber shaves himself, then he violates the second

stipulation that he only shaves those who do not shave themselves. And if he does not shave

himself, then he goes to the local barber to be shaved, who happens to be him! The mathematical

way of putting this is that we have here the class of all classes which are not members of

themselves.

This was a very difficult thing for the world of mathematics to digest, and then along

came another Austrian, Kurt Gdel, to muddy the lines even further with his Incompleteness

Theorems. The common statement of his first Incomplete Theorem, of which the second is a

corollary, is this:

Any effectively generated theory capable of expressing elementary arithmetic cannot be both consistentand complete. In particular, for any consistent, effectively generated formal theory that proves certain

basic arithmetic truths, there is an arithmetical statement that is true, but not provable in the theory.


7/27



Page | - 7 -

Put in a simpler way for technology managers, one could say that no matter how much data you

have, even infinitely many bits, you cannot prove all true statements. So, for the mathematicians

out there, this threw their worlds into flux. How could they know whether the problem they were

working on was inherently unsolvable, like Hilberts Second Problem, or simply extraordinarily

difficult, like Fermats Last Theorem? The answer was that they couldnt know.

This new reality of maths was very esoteric and abstract, but exceptionally important. To

make it more concrete though, to bring it to the level of the practical, it took Alan Turing. Turing

is the father of computing. He may well be one of the most important men of the 20th

century. He

figured how to crack the German Enigma Code during World War II, and was thus instrumental

in the Wests ultimate victory in the war. That was in 1938, and two years before he laid the

groundwork for his code breaking with an even more important discovery, the Turing Machine.

In trying to conceive ofa solution to the Halting Problem, as the mathematicians situation above

became known, Turing invented a machine. And by testing the limitations of the machine he

invented, he could better investigate Gdels and Cantors work. That is because by creating

what we today know as the computer, Turing was investigating something more concrete than

unknowability; he was investigating uncomputabilty. The Turing Machine was not intended to

be practical solution, but rather a thought experiment designed to see for certain whether or not

there was a general algorithm which will allow one to decide, in a finite number of steps, the

truth or falsity of a given purely logical assertion. In proving this to be false, Turing codified for

us the concepts of computer, algorithm, computer science and artificial intelligence. We can

know the limits of computing, of computed intelligence. If you ever want to fool a computer

trying to be intelligent simply ask it, How do you know you are not lying? The computer, no

matter how sophisticated, cannot tell you the answer with certainty.


8/27



Page | - 8 -

Now, the question on which this entire paper turns is: Why does this matter? Why do

technology managers interested in AI need to develop some understanding the history of the

techniques outlined above? Well, because every single one of us will have our lives inexorably

and profoundly changed over the coming decades by Artificial Intelligence. And to make the

best use of it, we have to understand it, first by understanding what it is not. Just like the Internet

did not turn out to be TV, only better, Artificial Intelligence is not going to be human

intelligence, only better. Artificial Intelligence will be extremely important because of the speed

and scale at which it can discover things computationally. The Blue Waters project that has

recently been revived at the National Center for Supercomputing Applications here on Illinois

campus is about the creation of a supercomputer with 300,000 cores that can 1000 trillion (1

quadrillion) calculations per second. That is like all of humanity, all seven billion of us, being

able to ~142,000 calculations a second each, and then putting them all cogently together. That is

simply astounding. During our visit with the MS-TM as a part of the Frontiers of Technology

course, we were treated to a half-dozen or so visualizations that put the supercomputers results

into a visual form that we humans can understand. One of the visualizations was of two galaxies

colliding, some 13 billion years ago. The sheer scale represented on that screen, and the ability to

compute it all, is almost unbelievable. But, there will always be something lacking in that

computers ability to understand truth value, something imbued into our consciousness by way of

intuition. This introduction to the foundations of AI was designed to give the reader a deep and

abiding respect for the power of the human mind. At the risk of sounding trite, this is lost even

on the smart minds of today. Searles Chinese Room analogy, Kurzweils Singularity, Newell

and Simons physical system hypothesis, they all side with the Dartmouth Proposal, which states,

"Every aspect of learning or any other feature of intelligence can be so precisely described that


9/27



Page | - 9 -

a machine can be made to simulate it." And now that we know the limits of computing, or

Artificial Intelligence, better than before, we can understand precisely why this is simply not

true, and then how to organize better the business case for commercialization the ideas this

understanding imparts. Ideas improperly formed, no matter how clever, wont everbe profitable.

From Idea to Innovation: Artificial Intelligence Applied

There is no greater mechanism for allowing ideas to foment and become reality than

those of the markets. And by applying the logic of economics, of social systems of human

exchange, to AI in order to bring it to bear, we will be allowing AI to develop in the most

advantageous way that we know how for human benefit. Innovation is essentially the

commercialization of ideas, and so ifwe are to study the idea of AIs long run adoption curve as

being most optimally influenced by the market, then innovation is where we must start. This is

why will look at the nature of the two dominant systems of innovation today, open and closed,

and how the most important practitioners of these systems, Google and Apple, are applying these

systems to the Voice Recognition piece of Artificial Intelligence.

In 2003, the Defense Advanced Research Projects Agency (DARPA), essentially the

R&D arm of the US military, began work on a project called the Cognitive Assistant that Learns

and Organizes (CALO). It was and is the most expensive and involved AI project ever

undertaken. Out of it came two core AI technologies that were spun out into two companies, and

this will certainly be important later when we speak to Apple, who bought SIRI. The point here

is that for the longest time AI really only developed as a philosophical idea from years after

Turings breakthrough. The hardware and computing power needed to run the algorithms of AI

simply hadnt developed yet. But, as we began to move Turings idea from Platonic essence to

the physical medium of reality, we discovered along the way that our ability to build evermore


10/27



Page | - 10 -

computing capacity doubled every 18 months, in what is known as Moores Law, after the IBM

founded who first voiced the concept. The upshot is that from the 1960s through to today, the

situation has reversed in that we now have more computing power than we have software to

optimally manage it. Merle Giles, the Director of the NCSAs Private Sector Program, told us as

much in his presentation to us. The result is that government funding, and corporate interest, is

now piqued to the need to provide more intelligent computing algorithms, and the evidence can

this is seen in things like the CALO project, and Apples interest in it.

Now that we are firmly grounded in the theory of AI, and have set the stage with the

renewed interest in developing commercial applications, we can proceed to investigating how a

particular application of AI, Voice Recognition, is the subject of innovation within the leading

tech firms in the world, Google and Apple. The Google section suffused with an explanation of

Voice Recognition itself, and then we proceed in looking at Apple, and its purchase and

integration of SIRI into its model. The resulting look at the two companies yields some very

interesting results, and it fits very neatly into a discussion of closed and open systems of

innovation.

Voice Recognition, Google and Google Voice

Perhaps the single most informative piece that we have seen on Google is a bit on CNBC

called Inside the Mind of Google. In an interview for the piece, Eric Schmidt, Googles CEO

during its mighty rise, said:

We've been trying to understandfive years from now and 10 from nowwhat does the world look like?People will be empowered in enormously new ways, because everyone will have the equivalent of

smartphones in their pockets.

I think that gives us a great insight into what Google is at its heart. It is enormously future

oriented, always questioning what the world will be like, and how they can develop tools to help


11/27



Page | - 11 -

us get there. He also says in that program that Google is likean extension of graduate school.

Google is an intensely curious place, and it began as a graduate school research project at

Stanford University. Larry Page, in doing research for a dissertation subject, came up with ten

plausible ideas for further study. His thesis supervisor, Terry Winograd, suggested that he should

look at his idea to investigate the link the structure of Tim Berners-Lees World Wide Web

creation; ostensibly akin to taking a look at the mathematical properties of the Internet. But that

was not necessarily the breakthrough. The search results were useful, but Google has become the

most profitable entity on earth, growing faster than any company in history save for Facebook,

because it married the improved search results Pages research and underlying methodologies

had wrought (called PageRank), with the economic power of truly relevant advertisements paid

for in a pay per click environment through a program called AdWords.

The genesis of Google, and its power, is in that marriage of PageRank and AdWords. The

unique idea was the former. However, the power as coming from the marriage indicates a very

important reality behind Google as a company. Andrew Hargdon, in book How Breakthroughs

Happen, speaks of this important reality in terms ofrecombinant innovation. Hargdons idea

is that many breakthroughs happen not as a result of a quasi-mythical Edison-like archetype of a

solitary genius slaving away in his or her lab inventing the next big thing, called de novo

innovation. But rather, many breakthroughs come about as a result of recombining existing

technologies in a novel arrangement. The existing technology of search, improved upon as it

was, combined with the existing concept of AdWords (which was copied from something called

IdeaLab, whose creator sued and won an undisclosed settlement from Google), was simply

magic. This idea of recombinant DNA being in the genes of Google, will become very important


12/27



Page | - 12 -

when discussing the firm in terms of its open system of innovation later in the concluding section

of the report.

With Google, its fundamental organizing concept is search. That concept is incredibly

unifying and drives Googles entry into such things as space exploration, self-driving cars, and

Google Mars. Googles executives reasoned years ago that they needed to make their entry into

mobile computing. They were finding that users on their smartphones (or what passed for

smartphones a half dozen years ago; basically we are talking phones that were internet capable)

where having trouble navigating the internet on their mobile devices, and thus having trouble

accessing Google to search for information. Given the enormous profitability Google derives

from AdWords, not delivering those search results, and ads, to end mobile users when they

wanted to search, it is easier to see why Google began to develop Android. They wanted to make

a mobile operating system built around search, essentially creating profit centers out of the

hundreds of millions of Android smartphones that have and are to come.

Android, too, is a product of recombinant innovation. Android was actually a small

startup run Andy Rubin. Google bought the company and made its product the center of their

mobile computing universe. That core unifying theme of make search easier is thus driving

Android, and this is where Voice Recognition comes into view.

Voice Recognition is, quite simply, an application to transfer an analog signal to a digital

one. Google, in its typically recombinant way, is using ideas that have existed in this space for

some time, and Google is just a company that combines the concept with its own core

competencies. The idea of AI voice recognition has been around for decades. In so many old

films, we could see that the heroes communicate with the terminal machine of a space battleship

and control the weapons directly by talking. Decades ago, using AI voice recognition to control a


13/27



Page | - 13 -

car or a battleship was just an ideal and a dream. However, today Google makes this dream real

through its platform and software. What follows is a visual demonstration of the concept of VR:

The actual transcribing of digital sound waves into words is what Voice Recognition actually

refers to. Where Artificial Intelligence comes into play is in the error checking, in applying

statistical techniques to take the mistakes made and use them to improve the future probabilities

of getting the word output to be evermore accurate. Google is perhaps better than any company

in the world at collecting big data, making sense of it, and then executing in a profitable way

on what they make sense of. For example, they are

taking what their AI has learned from doing Voice

Recognition in smartphones, and is applying it to a

new market subtitle in video, so we could read the

subtitle and simultaneously hear what the speakers

are talking about. The application of Voice

Recognition on simultaneous subtitles is really beneficial to many foreign students whose mother


14/27



Page | - 14 -

language is not English, so that they could better understand more news and TV programs.

Besides the benefit for an English learner, another amazing result of Googles voice recognition

is that through the subtitles deaf persons could clearly HEAR the message that the video needs to

convey. Googles amazing voice recognition might change the education mode for deaf students.

Googles voice recognition is definitely an innovative breakthrough because before the advent of

Googles s voice recognition, nobody is able to imagine that the subtitle could simultaneously

show up with the video.

Googles AI voice recognition could also be applied to other things within its product

suite besides search and transcription, like with translation. Currently we are majorly using the

keyboard to input key words to find the destination in Google Map, and to translate some words

in Google Translation. In the future, we might get the answer in Google Map and Translation just

by speaking. Besides, we might also buy the super car in Knight Rider and control it by oral

conversation.

Although Googles voice recognition is definitely a competitive product to Apples SIRI,

which well detail in a moment, the developing team still needs to solve some challenging

barriers, namely: the vocabulary, accent, judgment, and sound quality. How will Googles sound

recognition automatically identify new vocabularies? How will the system smartly correct

speakers wrong words to the right ones? How will the system still show the same words even if

the speakers with different accents say identical words? How will the system purposely skip

some words in the cartoon-South Park when those 4 children say something filthy? How will the

system normally operate if the noise signal in the video is too strong? Googles developing team

need to face the challenges above and overcome them. They will do by leveraging their internal

competency in Artificial Intelligence that they have developed with search. As we saw Googles


15/27



Page | - 15 -

founders acknowledge earlier, AI-Complete (human-level artificial intelligence) is the holy grail

of search; Being the best search firm in the world means that Google can build adaptive software

that helps its AI technology learn through an iterative process. Millions and millions of users

using Google Voice in Android, providing haptic and verbal and written feedback as to the VRs

accuracy, will help the transcription program more nearly turn my analog voice signal into digital

letters. And, as always, the end goal is to make search easier. How much easier could inputting

information into a computational agent get?

From here we will proceed with an explication of Apple as a company and its foray into

AI and Voice Recognition.

Apple and SIRI

Apple Computer, incorporated on January 1977, has been considered a leading designer and

integrator of computer hardware and software. Apple is good at innovating design and has

introduced many innovative products. The Macintosh, iMac, OS X, PowerBook 100, Mac Mini,

iTunes, iPod, and iPad are some of Apples innovative products. The success of this product suite

has catapulted them to the top of the technology world, even during one trading week this year

briefly surpassing Exxon Mobil at the worlds most

valuable company. Apple has entered multimedia and

communication market in 2001 by introducing iPod, a

digital music player. Apple completely changed the

music industry with the release of the iPod, and the

iTunes music store. iPhone which is a multimedia and

Internet-enabled quad-band GSM EDGE-supported

mobile phone designed and marketed by Apple was


16/27



Page | - 16 -

announced on January 9, 2007. Finally, SIRI was acquired by Apple in April 28, 2010 because of

its DARPA credentials and massive future potential.

Apple is a multi-focused company emphasizing functionality, product and geography. In

this structure, as it can be seen from Exhibit-1, it is centralized in decision making in which a

corporate dictator makes every critical decision on the executive level. In this role, Steve Jobs

was the visionary who sought to change the world through technology. He is the solitary

genius in Apples de novo view of innovation. He is, as the saying goes, the genius with a

thousand helpers. Steve made it Apples mission to bring an easy-to-use computer to every man,

woman, and child. He changed the organizational structure from functional to multi -focused

structure, since he realized that a functional design hinders a firms ability to respond quickly to

a changing environment. Apple was split up into three geographic regions: Apple Americas,

Apple Europe, and Apple Pacific. This orientation led to the efficient allotment of resources to

each specific region so that each could attain and monitor its own particular goals. A fourth

division was Apple Products, which was further broken down into Retail, Software, and Mac

divisions. Recently, two new divisions were added: iPod and iPhone. This organizational

refinement was initiated by Jobs to place more emphasis on the product development at Apple.

Shifting the majority of companys focus into product divisions, innovations in marketing,

outsourcing manufacturing, and creating alliances led Apple to align its functional and divisional

goals and have ability to properly develop and innovate.

Apple is perceived by the public as an exciting place to work, and a visionary company

which is creating the future. The atmosphere was casual, reflecting highly technology companies.

Besides, Apples management style was relatively informal that has very few polices, systems, or

controls. In addition, Apple was dominated by personality. Management by coercion did not


17/27



Page | - 17 -

work in this company.

Apple was not the first to invent the laptop or first computer using Graphical User

Interface, but Apple changed the way the world uses computers or phones or other devices

forever. Apple played the role of a technology integrator, and took innovations that had been

lying around and used them as a way to bring publishing to the masses. It for this reason that we

think the closed system of innovation that Apple is lauded, and lambasted for, in not quite an

accurate term. And de novo innovation isnt quite enough to describe them either. Apple looks

today like more of a closed/open hybrid, which we will delve into in the concluding section.

They tried to do the same things making it easier- for every kind of products or software.

Apples success was not just the result of clever strategic moves or an innate sense of market

timing. It came from a deep commitment to understanding how people used computing devices

and a desire to develop insanely great products. The company often defied conventional

business logic and was not afraid to experiment outside its core markets. It built retail stores

when competitors were moving to direct sales and distribution modes, and its products were

rarely first to market. There was, however, a surprising consistency in the way the company

worked. Simply put, the Apple Way was a set of principles with a deep commitment to great

products and services at its core: design thinking, clear development strategy and execution, its

CEO as chief innovator, and the rational courage to conduct bold business experiments Apple has

prospered by keeping just ahead of the times from its first computer (Apple II) in 1977 to the

iPhone in 2007. These are the major innovations of Apple:


18/27



Page | - 18 -

Apple was a technical innovator rather than a business model innovator until the mid

'80s. Apple always used to come up with technically cutting-edge products well ahead of its

competitors. Since Apple failed to penetrate the market because of the lack of a good business

model, Apple has changed its business model which started with the commercialization of iTunes

and iPod. Apple's decision to start retail outlets in 2001 is another bold strategy that has helped

them to reach the customers effectively and build a better brand name for the company.

Apples approach to innovation has been more complex than just designing exciting

products: its streamlined product portfolio and extensive reuse within product families suggests

that Apple has a clear platform strategy. The OSX operating system, for example, is used in all of

Apples computers as well as in the iPhone. This strategy offers big advantages and benefits to

the company, its suppliers and the customers. Apple, who put a premium on design, resources

and time invested into initial product is leveraged across derivative products, which are built on

and made use of design elements in the platform. Apple also insists on integrating customers

experience into its design and development processes.

Apple is historically an ambidextrous company which can implement both incremental

and revolutionary change. It has succeeded both dominating market such as PC and software,

and looking for revolutionary products and new market for new growth for years. Another thing

in which Apple is actually good at is the recombination. Innovation is a process of taking apart

and reassembling the current technologies in new combinations. As an example, Apple

recombined all the features and technologies together which are existed in many current

available cell phones in the market in Apples way and make iPhone such an innovative product.

In addition, Apple has a lot of alliances who provide supports in many different aspects in

todays technology network society. While Toshiba provides the storage technology, Sony


19/27



Page | - 19 -

provides battery parts, and Samsung provides CPU for Apple, etc. Apple uses the Joint Ventures

and Alliances to increase the value it creates and delivers to customers. Apple is successful in

using a corporate entrepreneurship model, and used it to reintegrate iPod to Apples main

business, computer and software. Steve Jobs assigned a team directly to the work, and the team

succeeded in taking advantage of existing resource to launch the product in less than a year.

When Apple decided to develop voice recognition on a smart phone, Apple had to make

sure how to strengthen their voice recognition technology and apply it to real world on

customers necessities. Then, Apple acquired SIRI on April 28, 2010, a start-up company

developing voice recognition application. It helped Apple to raise its smart phone abilities; and

give them a certain direction for innovation and development.

Since being released to much aplomb in the iPhone Application Store in February, the

SIRI personal Assistant has caught a lot of attention. SIRI's free app is connected to a whole

ecosystem of Web services and programming interfaces, and has the ability to activate other

applications that reside on a smartphone. SIRI has two essential parts. First part is the voice

recognition, and the second part is that uses artificial intelligence to understand the context of a

question.

Apple has done a fantastic job of integrating SIRI with other applications such as

calendar, GPS and reminders. In addition to the SIRI assistant, Apple is using its new voice

recognition chops to offer a "beta" version of speech-to-text dictation functionality. Initial

languages include English, French, and German. Apple also wants to keep developing more

language supports for SIRI, such as Chinese, Korea, and Japanese, and strengthen voice

recognitions sensitivity.

Apple tried to strengthen SIRIs ability by the cloud technology; and cooperated with


20/27



Page | - 20 -

some telecommunication businesses in this regard. For instance, when a user searches a

restaurant, or information, SIRI doesn't just use voice recognition to deal with peoples

questions; SIRI sends the question to the cloud, where a powerful artificial intelligence system

can analyze the wording, figure out what peoples want, and give the answer back to peoples

phones.

With SIRI, Apple has lowered the friction on search and turned it into a mellifluous

experience. But to take it to the next level, Apple is going to need much tighter integration with

web search. Building a search engine would take too much time and there aren't many good

options for Apple to partner with in search, so the most likely scenario is that Apple will buy a

smaller player and integrate it into SIRI. SIRI clearly has tremendous future potential for Apple

across its entire product line. By the end of 2013, it is expected to see SIRI on most iOS devices

and Macintosh machines. SIRI would be the revolutionary interface (VUI -vocal user interface)

that Steve Jobs wanted to bring to television sets.

In comparing these two companies, especially in regards to how they are doing Voice

Recognition powered by AI, some striking similarities emerge, and some very instructive

theoretical differences, as well.

Disruptive and Sustaining Innovation...

It is obvious that Apple and Google are two of the most radically-innovative corporations


21/27



Page | - 21 -

in todays modern world of technological advancement. The firms have continued to pump out

technical innovations, one after the other, and have developed excellent relationships with their

customers. As for the voice recognition which is based on artificial intelligence, the situation is

little different. The idea of artificial intelligence has been around more than thirty years. Since

the hardware does not improve as fast as software, it will certainly take time to be

commercialized. But SIRI and Googles AI developed from search have made the idea of voice

recognition come true. From the technological view, it can be said that voice recognition is a

disruptive technology. The following is a graph of the model of sustaining versus disruptive

technologies: Because thetechnology is not mature; performance is well below the expectations. The AI powering the

Voice Recognition needs billions more iterations before it can begin develop a proper database in

order to make the output sufficiently accurate.. For Apple, the voice recognition was utilized in a

sustaining way of innovation. Apple is known to use smart technology to create smart devices

such as iPhone, iPad, iPod etc. Apple has been trying to integrate voice recognition into its core

businesses and devices. The first step was the iPhone. Apple wants to use this voice recognition

concept in wider sense. Apple plans to develop VUI based on voice recognition concept, and

then use it in all devices from computers to iPhones, from iPods to Apple TVs. If that happens

this could be definitely disruptive innovation in terms of how we interact with and use these


22/27



Page | - 22 -

devices. Google, too, is using Voice Recognition in a Sustaining way. They are integrating their

technology in this space also within an existing product ecosystem, to give it support and some

room for error by making it a value added feature to make search a little easier.

It is certainly striking how Google and Apple are both approaching the management of

innovation within the Voice Recognition powered by Artificial Intelligence space. They are both

creating ecosystems, Apple with primarily a product ecosystem (though with OS X, iTunes and

such, they could be said have a software ecosystem as well), and Google with a software

ecosystem. However, where they differ significantly is in the System of Innovation Model that

each firm uses.

Within a Closed or Open System of Innovation

We have moved from a world dominated by what is known Closed Innovation to Open

Innovation. This shift has involved rethinking how to bring ideas to market as a firm. There is a

fundamental shift taking place in how companies generate ideas and bring them to market. In

America today, Kline mentions in his important paper, Sharing the Corporate Crown Jewels

anywhere from 50 to 70 percent of the value of public companies comes from its intellectual

property assets. These crown jewel

technologies as they are called, must have their

stored value maximized. In order to understand

how to do this, we have to proceed first with an

understanding of what Closed and Open Models

of Innovation are like, and why we are seeing the underlying shift from the former to the latter.

The older model of Closed Innovation is best described as innovation through total

control. The logic, as it unfurls, has been tacitly taken over the years as self-evident, which is


23/27



Page | - 23 -

potentially a huge mistake and the genesis of such organizational negatives as the status quo bias.

The hope of Closed Innovation was that based on a set of assumptions, a firm could create a

virtuous cycle of innovation. The idea is that firms would invest heavily in R&D, hire the best

and the brightest, take for granted that a market will always be found for a discovery, and that

first mover advantage confers some kind of absolute competitive advantage. Winning was felt to

be inevitable, as long as the process was followed. The Closed Innovation Model can be summed

like this:

Apple, with its famously involved founder, tended to look like that. Their Draconian policies on

approving and denying applications for the iTunes store, their leading the line of the Digital

Rights Movement, and in the bygone era, their steadfast refusal to make Macs function better

with PC output, can all sum to make Apple seem like a Closed Innovation company. However,

we have seen in our analysis is that Apple is actually more like Closed/Open hybrid, because

they do some things that also resemble the tactics of an Open Innovation Model.

The Open Model of Innovation, as Chesbrough describes in his article The Era of Open

Innovation, has been enabled by chief forces, amongst many other smaller ones, as well. The

first, and probably most important, has been the rise in the number and mobility of knowledge

workers. This has made the total control of proprietary information paradigm that held under the

Closed Model obsolete. People have access to tools to today to instantaneously search the entire

compendium of human knowledge. But, that is really not enough in and of itself to disrupt an

entire century of closed innovation modeling. That knowledge must have the means to be

actualized, which in economic terms, means that new knowledge needs access to capital. Big

conglomerates have, as we saw, very clear and well defined mechanisms for making that happen.

And in the marketplace of ideas, their ideas had less competition, because other ideas sourced


24/27



Page | - 24 -

from the long tail couldnt be actualized. But, with the rise of Venture Capital, in the form of

angels, SBICs, venture funds, and the like, new ideas from anywhere could get funded. This

convergence of the rise of the knowledge worker and the rise of Venture Capital mechanisms

was so powerful that it overthrew the powerfully entrenched self-evident thinking of the old

model. As Chesbrough states in the aforementioned article:

Thus, the virtuous cycle of innovation was shattered: The company that originally funded a breakthroughdid not profit from the investment, and the firm that did reap the benefits did not reinvest its proceeds to

finance the next generation of discoveries.

The shattering of the old model led to the creation of the new Open Model, which can be

summed like this:

That depiction, from Professor Echambadis New Product Development class, looks radically

different than the one we saw earlier. We see that research projects come not just from within,

but from without. That openness can describe both Apple and Google in a lot of ways in this

space.

We find the depiction of different targets also to be instructive. To us, that indicates that

there are more ways to bring an idea to market than internal handling; companies can open up

extremely profitable new revenue streams if they license their IP. On the flip side though, there is


25/27



Page | - 25 -

certainly the main risk of market share loss. Any time a company releases information which is

fundamental to core IP, that selfsame IP becomes less secure, and can be more nearly copied and

manipulated by the market. So, like in all things business, it is a tradeoff that must be managed.

How much do we protect our IP and our existing share, versus how much to we allow ourselves

to look outside of ourselves to partnerships and licensing? The bottom line, as Kline says, is

that strategic licensing, if done properly, can spur a company to become more innovative and

competitive in all sorts of ways. That is certainly in huge contrast to the Not in My House

(NIH) Syndrome which Chesbrough mentions as the dominant thought process for Closed

systems of Innovation.

Being open to this new methodology behind actualizing ideas and bringing them to

market can be extraordinarily profitable. Consider Klines example of IBM, who in 2000 alone

did 1.7 billion in revenue from licensing fees, at an almost too staggering to believe 98% percent

profit margin. Those fees now make up 20% of the firms profit as a whole. It is easy to see why

this excites shareholders, VCs, employees, C-suite executives and everyone in between.

Generating this kind of IP return in other firms requires never forgetting that innovation happens

everywhere, but there is simply more elsewhere than here. Companies need to thrive on sourcing

internally and from the long tail of ideas. Likewise, we have to harness the power of smart

people everywhere, as all of us are smarter than none of us, thanks to the Central Limit Theorem

in statistics. When done right, it can lead to the kind of definition of competitive advantage

described here by a P&G executive: Ive got it and youve got it, and I make money when I sell

it, but I also make money when you sell it. By harnessing the power of the Open Model of

Innovation, or a Closed/Open hybrid Apple and Google can literally set the standard for entire

new emerging markets and industries, and make incredible amounts of profit in the process.


26/27



Page | - 26 -

Conclusion

Another DARPA creation, the Internet, was in the same position as the Artificial

Intelligence movement is today. The Internet was a fantastic technology that took some time to

gain significant world-changing traction. The Internet needed such things as Tim Berners-Lees

World Wide Web and Netscapes browser to really becoming the productivity and vital life-

enhancing too that it is today. Artificial Intelligence also needs the concurrent development of

enabling technologies, like: a semantically-enabled Web, populated by a Web of Things,

robotics, and, specifically as regards the Voice Recognition application, the continued increase in

power and performance of smartphones. Until those enabling technologies are themselves

strongly in place, Google and Apple are best served doing as they are now with the disruptive

technology of Voice Recognition powered by Artificial Intelligence: treating it within a

sustaining framework and embedded in a currently powerful product or software ecosystem.

Though Apple and Google differ in their Innovation system, they are much more alike than they

are different, especially as regards to the type of recombinant innovation they both use to source

and develop ideas to commercialize through their Innovation System/Model. Apple is moving

more towards an open system of innovation, but we are all products of our environment. Google,

as a new firm, is fully ensconced in the new model, whereas Apple still carries with it vestiges of

the Closed Innovation System that it operated under, along with most other industries and

companies in that era. Nevertheless, Google and Apple have experienced some solid success, but

still face a great many challenges in this space. We are excited to see how Voice Recognition,

powered by Artificial Intelligence, develops within these two important technology titans in the

future.


27/27



Resources Referenced

Apple Inc. Website, http://www.apple.com.

Arora, N. November 15, 2011, Can Google catch Apple's SIRI?

Vhttp://seekingalpha.com/article/308145-can-google-catch-apple-s-siri>.

Chen, Brian. October 11, 2011, With SIRI, the iPhoneFinds Its Voice.

.

Chesbrough, H.W., 2003, The Era of Open Innovation, MIT Sloan Management Review.

Google Inc. Website, Company History

.

Hargdon, Andrew. How Breakthroughs Happen: The Surprising Truth About How CompaniesInnovate. Harvard Business Review Press, 2009.

Hiner, J. November 30, 2011, Between the lines/SIRI: Why Apple will build, buy, or partner on

a search engine, .

Inside the Mind of Google. DVD. CNBC, 2009.

Kline, D. 2003 Sharing the Corporate Crown Jewels, MIT Sloan Management Review.

Lashinsky, A. August 25, 2011, How Apple works: Inside the world's biggest startup, FortuneMagazine.

National Center for Supercomputing Applications Website, FAQs

.

Scoble, R. April 28, 2010, Breaking News : SIRI bought by Apple,

.

Thomke, S. & Fainberg, B. March 4, 2010, Case Study: Design Thinking and Innovation at

Apple, Harvard Business School.

Walker, Genevieve. May 7, 2011, Can Google Stay on Top?,

Yoffie, D. & Slind, M. May 30, 2007, Case Study: Apple Computer, 2006, Harvard Business

School.
http://www.apple.com/http://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://www.wired.com/reviews/2011/10/iphone4s/all/1http://www.google.com/about/corporate/company/history.htmlhttp://www.zdnet.com/blog/btl/201111http://www.ncsa.illinois.edu/News/faq.htmlhttp://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://www.salon.com/2011/05/07/in_the_plex_interview/http://www.salon.com/2011/05/07/in_the_plex_interview/http://scobleizer.com/2010/04/28/breaking-news-siri-bought-by-apple/http://www.ncsa.illinois.edu/News/faq.htmlhttp://www.zdnet.com/blog/btl/201111http://www.google.com/about/corporate/company/history.htmlhttp://www.wired.com/reviews/2011/10/iphone4s/all/1http://seekingalpha.com/article/308145-can-google-catch-apple-s-sirihttp://www.apple.com/

Documents

Managing Innovation Final Paper - Artificial Intelligence