What's left to know? by Orange Silicon Valley

research in a total-connect world conversations about Tech Research Futures

Editorial: Talking about Talent This is about a set of conversations.

Indeed, a conversation that started in

February 2011 as an introspection about the balance between academic and commercial research â&#x20AC;&#x201C; where was the important research in IT and telecoms being done? Who was investing in it? To whom and for what is the long-term R&D world even relevant anymore? Those conversations continued and started involving others, including the author of this remarkable set of interviews. Things got pretty transgressive: what if what we see before us really is it for the next 20 years? What if most of the important tools and methods we utilize for the next few decades are the cutting-edge resources of today? If so, we are just exiting a period of radical transformation, and entering a massively incremental mode. To explore where research is going, you have to talk to practitioners. And, you have to speak in their language, understand their issues, and know the canon. We were able to find that interlocutor in the person of Lee Gomes. Known to many in Silicon Valley for his reporting on behalf of national publications such as the Wall Street Journal and Forbes, Lee was the perfect entry-point into a wider discussion. The result is what you have here --- a rich set of discussions with some of the companies and universities responsible for the future of high-tech advanced research. Those interviews plus our own first hand observations and interactions with peers and major customers formed the basis for this report. We at Orange share these findings in the spirit of exchange and the idea of innovation as open and public. While what follows is ostensibly about research, we recognize that it is fundamentally about the Talent that drives innovative research. The concentration of Talent in Silicon Valley is unique in the world â&#x20AC;&#x201C; and highly sought after. Respect for Talent, recognition that Talent is highly mobile and votes with its feet -- this is what drives the questions posed here. Is that PhD as important as that startup? Is munging some ugly public data set as rewarding as working on the Facebook graph? These are not questions about technology, but about where Talent wants to go and what it wants to accomplish. Letâ&#x20AC;&#x2122;s add to that: when it wants to accomplish it. - Georges Nahon CEO -Mark Plakias VP Orange Silicon Valley

This is happening everywhere, including the deepest recesses of corporate R&D, where cycles of investment and divestment are getting shorter. of corporate trust for

What’s left to know?

research is

The deterioration probably based on

management impatience with too-long research cycles, squeezed by more and more competitive scenarios with barbarians coming from all over the place creating new, hugely successful products from well-funded disruptors such

At Orange Silicon Valley, we are actively engaged in most of the topics cited in these discussions with researchers in

as eBay, Amazon, Google, Zynga, Facebook, Yahoo, etc. In this atmosphere,

R&D doesn’t seem to be

the IT, communications, and online media and commerce

producing anything competitive with what the barbarians

industries. In the course of this ongoing collaboration the

produce and deliver. A condescending view is that Corporate

voices from both industry and academia have spoken and

R&D projects may be taken by surprise by the agility and

their message seems clear: life in the “Labs” -- and beyond --

audacity of the barbarians -- who have no faith and no

is never going to be the same. Almost daily we can observe

respect for the laws or rules governing the establishments

a significant number of impactful innovations manifesting

(if they ever even knew them), or indeed for any legacy.

themselves in commercial products and services that are

For them, risk is the new normal. Risk seems to not carry

the fruits of smart people working outside of the corporate

the perception of threat, as they have nothing that can be

or academic R&D sphere. Who are these smart people?

threatened

They’re not wearing white coats, nor do they always

But is this just attitude, or is it data-driven? The

publish papers. From the corporate R&D establishment’s

idea that analytics and pattern-recognition of very large data

perspective, they look like barbarians, or something alien.

sets are both basic research and a model for how research

The facts of the matter are clear from our perspective:

gets done is an important topic in these discussions. As

things are running very fast in a digital and networked world,

Facebook’s Cameron Marlow puts it in his interview: “The

and what research does and how it is done probably needs

social interactions on the Internet, and on Facebook in

to be revisited. The title of this report phrases the current

particular, are at a level of detail and scale that haven’t

state of affairs in information and tech research as a question

existed before. They allow us to answer questions about

in epistemology, but ‘what’s left to know?’ is also a question

social interaction and forces that we’ve never been able to

about tempo and scale. We know big corporations spend

answer...” Although SRI’s Winarsky does not see Zynga’s

most of their time protecting the most profitable part of their

“new type of business proposition” as anything resembling

business now, but digital platforms are impacting these

research, he does describe it as “even more valuable than

centers so quickly that further R&D in these disrupted and

technology.” Google’s Peter Norvig sees the availability of

discarded areas seems somehow suspect.

these data sets as unique to industry, and a reason to migrate

...things are running very fast in a digital and networked world, and what research does and how it is done probably needs to be revisited.

This seems to be forcing management to succumb to the temptation to kill years of effort, with the possible exception of some patents that can be monetized.

there: “...there are some things you can’t do in universities,

tempted today with some new and exciting technologies

and that’s one reason why I am not in the university now.”

rather than finishing their PhDs, so they decide to go and start

It was not always this way. In the past, game-changing

a company.”

companies were fewer in number, therefore movements of

The friction of corporate distrust of what’s happening

the industry were calibrated by other incumbents’ R&D labs

internally in R&D is discussed at various points in these

performance in a

pages as management seeing all this money and time spent

importantly, everyone was staying in their own business

developing new innovative products, but getting beat to

territory -- until digital changed everything and made every

market by barbarians. This seems to be forcing management

company look like it was playing in the other guy’s garden.

to succumb to the temptation to kill years of effort, with the

The tacit rules of mutual control -- “do not come into my

possible exception of some patents that can be monetized.

territory and I will not get into yours” -- are over because of

In this oft-repeated scenario private R&D seems more and

all things going to digital.

more like a defensive move (get more and more patents filed

time-scale equal for all players.

What are the larger ecosystem implications of this

and registered) than an attacking one.

shift? For one thing, important, viable research work at the

More recently, events such as the HP’s acquisition of

core of computing and communications seems somehow

PALM and its coffer of patents , the acquisition of Nortel’s

not as visible or compelling as it used to be. While this is

patent portfolio by a consortium of IT companies and the

a contestable statement, and there are rich discussions

Google/Motorola multi-billion dollar patent portfolio grabs

about this point inside these pages, one incontestable fact

have thrown this strategy into a new light: one where the best

is that innovation is redistributed and shared with start ups

defense is a good offense. In this new competitive scenario,

-- and some of these startups come from academic projects,

where intellectual property becomes an offensive weapon,

now encouraged by private investors.

UC Berkeley’s

hundreds of man-years of corporate R&D can be used to

David Patterson recognizes this trend, which he views as

drive licensing claims which add $5 to the cost of a mobile

manageable: “What’s happening is that our students are more

phone.

Whether this creates innovation or just lawyers’

fees is open to debate, and is just one of the many ways in which the discussion about how innovation and research interact continues to evolve. It is a moving train. And it may

The tacit rules of mutual control -- “do not come into my territory and I will not get into yours” -are over because of all things going to digital. 6

be that this new model is going to forever complement (and better) other more traditional forms of R&D that may survive in the fields of IT, communications, and online media and commerce. At Orange Silicon Valley our conviction is that we cannot understand alone what’s inside a moving train by watching it from the platform. We need to be in the train ourselves along with others to address the question, “What’s new to know now?”

by Lee Gomes History has not been kind to those who managed to become associated with the idea that everything that can be invented already has been.

ost have heard the story of the woeful idiot who happened to be U.S. director of patents in 1899, and who urged that his office be closed because there was nothing remaining to invent. In fact, that tale is an urban legend with no basis in fact; Charles H. Duell, who held the post at the time, far from being pessimistic about future discoveries, was actually a booster when it came to what Yankee ingenuity would make possible, akin to “You ain’t seen nothing yet.” (Quotes suggesting the opposite have been proven by scholars to be fabrications). But the fact that someone, somewhere, even bothered to create the historical falsification in the first place can be taken as a warning of the dangers involved when a given generation becomes so engrossed in its own repertoire of massive inventions that it devalues longer-term perspectives. But - and to use another problematic formulation - what if this time, it’s different? What if this time, they’re right, that the moment we’re in dwarfs everything up until now by comparison, and requires our full attention and ingenuity? To be clear, we are not talking here about the totality of science and technology, but instead, a subsection of it, in the enormously important world of IT, especially as it involves data and data sciences. What if the fundamental data-intensive infrastructure of computers - Moore’s Law, new data base tools and

ubiquitous mobile devices - is now in place, the way the basics of the automobile were in place once the modern internal combustion engine was realized? What if developments in IT and data from this point on are all incremental? This, of course, does not imply that there won’t be any major technology improvements, or shifts in corporate fortunes, in coming years and decades. After all, both cars and car companies look drastically different today than they did 50 or even 25 years ago, despite having the same technological foundation. But the changes were essential, gradual and incremental, rather than being earth-shaking and revolutionary, as they were in Henry Ford’s time. To understand why we are even raising the question of the future of data and IT, let’s first consider the classic view of the subject - with a bow to particle physics, we can almost call it the “Standard Model” of Silicon Valley. In this telling of history, most IT research was done at one of two locales: inside academia, under the sponsorship of the U.S. government, and at select groups of large companies with dominant market positions and the healthy profit margins that accompany them. The research-to-product transition followed a traditional path, beginning in a lab somewhere and then making its way to the marketplace, perhaps pausing along the way to accumulate some venture capital funding. How little that looks like today’s world. For one, federal funding for research has diminished or been reallocated.

Second, the great standalone corporate research labs of the post-war era, with AT&T’s Bell Labs (now AlcatelLucent Bell Labs) being the preeminent example, have been repurposed, if they even exist at all. Perhaps most significantly, technologies that not too many decades ago were but fledgling research ideas have today become robust, even commodity, product categories - notably highly integrated semiconductors, high-capacity storage devices, extremely sophisticated software and robust ubiquitous networks capable of high-capacity digital communications. The result is on display everywhere in Silicon Valley. Dense chips, cheap storage and ubiquitous networking have created the world of “Big Data,” in which hundreds of millions of computers and mobile devices are creating staggering amounts of information. Rather than the clock-like migration of technologies from research labs to companies, what we see instead is the steady ascent of what might be called the “research giants” - the best example, of course, is Google. These companies, arguably, are the only institutions with the resources, both capital and human, to handle data at the levels it is being created. It follows that they have privileged access to the massive data sets that enable the type of analytics and research about human behavior that is creating the wealth of the 21st Century. To be sure, part of

the innovation of these new giants is ecosystem-specific: Google and others share, via open source, the tools used for managing and learning from Big Data, and actively encourage these open source resources adoption by individuals and entrepreneurs. But the new reality is that the best, and most massive, data is in private hands. Far from being content, almost passive, “end-users” of academic research, as they might have been in the past, the big Silicon Valley companies of today are arguably doing most of the heavy lifting in IT research in the first place. In effect, is it perhaps the case that the task has fallen to the Google’s of the world, rather than any traditional “research” operations, of providing whatever incremental improvements remain to be made in the art and science of data? In this document you will hear from thoughtful practitioners on both sides of this question. By contrast, academic computer science departments find themselves doing a severely resource-constrained imitation of the commercial efforts underway at the big Silicon Valley companies. To ameliorate this, collaboration is necessary, and indeed happening: companies such as Google, SAP, Amazon, and Huawei are supporting long-term university research efforts such as University of California Berkeley’s AMP Lab. Still, the big picture seems weighted towards

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Put in its most stark fashion, as far as data-related IT goes, does traditional research even matter any more? That question is at the core subject of this report.

immediate engagement in a commercial context: these companies are so wealthy that they regularly poach some of academia’s most talented faculty members and students, further depleting academic research efforts. If you are interested in exploring some aspect of the “social graph,” where would you rather be: at even the best-funded academic department, or at Facebook, where you would have access to a 25-petabyte Hadoop cluster? And from which do you think the most interesting insights will spring into how people use “social media?” Put in its most stark fashion, as far as datarelated IT goes, does traditional research even matter any more? That question is at the core subject of this report. This idea for this project began when a small group of us, sitting together at a table, made a simple assumption: Everything else about the world has changed on account of the Internet; why should the practice of research

If you are interested in exploring some aspect of the “social graph,” where would you rather be: at even the best-funded academic department, or at Facebook, where you would have access to a 25-petabyte Hadoop cluster? be any exception? We interviewed researchers, research managers, entrepreneurs and other deep thinkers who spend their careers in Silicon Valley. The questions were all designed as variations on the same theme: How should technology companies, in an age of ubiquitous mobile computing, “big data,” shifting business plans, shortened investment horizons, be thinking about “research?” The bulk of this report is devoted to those interviews.

In one sense, there is nothing particularly shocking about suggesting that parts of the IT industry have become so mature that changes from here out will be incremental. It has happened consistently over the last two centuries, in everything from steam power to electricity to radiography to telephones and televisions. All went from being a newlydiscovered phenomenon of nature, the domain of researchers and scientists, to being the basis of large commercial enterprises, the domain of business people - with the occasional assist from engineers. Even in science itself, research can reach a mature phase. Isaac Newton did a fairly complete job of describing the movement of everyday objects in the everyday lives of human beings, from apples to planets. Early in the 20th Century, we discovered that Newton’s Laws didn’t hold for the very small or the very fast. But quantum mechanics and relativity don’t repudiate Newton, but instead modified him for new domains but leaving unchanged the many technologies built on Newtonian principles. We hope readers appreciate that when we ask “Does IT research still matter?” we are asking it not because we view the issue as settled, but instead, in an attempt to provoke thoughtful discussion. Some readers might be shocked that anyone would question the value of research. (In this report, “research” means basic, unstructured research, with no obvious short-or mid-term connection with a company’s existing product lines). But in actuality, there has always been a surprising lack of consensus about the economic value of research, at least when it is performed by an individual company. (Few doubt that federal dollars on even the most basic, untested forms of research are well spent). Indeed, one

Experimental modes of transistors, 1953

Bell Labs is an excellent case study in the difficulties of knowing what sort of value to assign to in-house research.

writer said that as far as companies are concerned, research might best be defined as a “faith-based initiative.” Consider the contradictory conclusions reached on the matter by two different groups of professionals: business school professors and business consultants on one hand, and academic economists on the other. Representative of the former category is a series of annual reports by Booz & Co. that began in 2005 and have continued since. Analysts at the firm say they have been able to find no correlation between R&D spending with just about anything most companies care about, such as sales growth, profits and market cap. (Though the report noted that the bottom 10% of R&D spenders tended to underperform in other areas as well). The report did not sit well with

many academic economists, who caution against attempting to draw any conclusions at all from publiclyreported accounting data, since the law allows companies considerable latitude in what they report as “research.” One paper by a trio of economists, with more stridency than is usually associated with academic writing, called the report “extremely misleading,” saying that in ignoring decades of prior literature, it “mixes incorrect conclusions obtained from an uninformed and simplistic analysis with some common sense advice” analogous, to telling people, “It is better to be rich and healthy than poor and sick.”1 There are certain questions about research that one doesn’t need to be a trained economist to raise. For one, there is plenty of anecdotal evidence to suggest that large research operations

There is, of course, no doubt that the Labs contributed enormously to human knowledge during its heyday in the years before the break-up of AT&T, probably more so than any single institution on the planet. 1956

often offer little protection to their companies in anticipating and responding to new business challenges. Sometimes, this is hardly the fault of researchers, as in the “innovator’s dilemma” situations where management simply can’t bring itself to undergo what might well be the wrenching business model changes necessary to adjust to shifting technologies. But what do we make of Microsoft’s seeming lack of ability to anticipate or out-maneuver Google, or Google’s current difficulties in keeping up with Facebook?” The “research skeptic” would also note the enormous values attached to companies that seemed to be based on no research at all, but instead on a entrepreneurial insight that was perfectly executed. Facebook, Twitter and Groupon all come to mind. Bell Labs is an excellent case study in the difficulties of knowing what sort of value to assign to in-house research. There is, of course, no doubt that the Labs contributed enormously 12

to human knowledge during its heyday in the years before the break-up of AT&T, probably more so than any single institution on the planet. (Transistors, evidence of the Big Bang, Unix and C; the laser; quantum computing breakthroughs: the list goes on and on). But how about AT&T shareholders; from their admittedly provincial point of view, did they get their money’s worth? Answering that question is probably impossible, as it involves unraveling a tangle of hypotheticals and counterfactuals, and nearly everyone we asked had a different answer. Most, in fact, expressed agnosticism. The debate about the value of corporate research strongly resembles the debate among economics about the value of “free trade.” Is the “engine” of prosperity, or merely it “handmaiden?” Put differently, does free trade cause fundamental economic growth in the first place, or does it simply accompany it after the fact, like an attendant in a bridal party? The best

evidence for the latter hypothesis is that nearly all countries, the U.S. included, take a protectionist approach to their nascent industries. Rephrased to deal with the research issue, the question becomes, “Does research make companies rich, or can companies do research only if they are rich in the first place?” Now that we have advanced our critique of the “Standard Model” of research, and suggested why much of Silicon Valley is perhaps unknowingly in a “post-research” phase in its history, we are obliged to challenge what we ourselves have been arguing. First, we are required to point out is that when trying to figure out a given company’s approach to research, the least reliable source of information is often the company itself. For one, accounting rules about research are so ill-defined that no two companies are reporting the same activities when they report on their “research” budgets. (Note that the authoritative reports by the National Science Foundation about corporate and government R&D spending do not rely on public accounting data, but instead on confidential, anonymized information shared with government by industry). Companies will also adjust their

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Does research make companies rich, or can companies do research only if they are rich in the first place?

characterizations of their research efforts depending on the audience. With Wall Street, they might emphasize its leanness and its tight connection with product groups and quick commercialization. With prospective employees in graduate schools, they are likely to give the impression that new hires are able to pursue their field’s deepest problems - without being distracted by any noise from the grinding wheels of commerce. An additional issue is that many people in Silicon Valley are unaware of the area’s actual history, especially as it involves the relationship between basic research and corporate success. Most people acknowledge obvious well-known facts, like the role that DARPA played in the creation of the Internet. But the pervasiveness of federal involvement in creation of the IT industry is often underappreciated. At nearly every step of the way, federal funding was involved with major Silicon Valley developments. In the 1960s, the first customers of semiconductor products were the military, who displayed ample patience as chip companies worked out the bugs in their earliest efforts at fabbing chips. It was just as true in the 1990s at the creation of Google, since

Larry Page and Sergey Brin did their work on the “Page Rank” algorithm while being funded from a grant from the NSF. Another problem is that “breakthroughs” are almost never as simple as they seem, and rarely occur in isolation. At the same time Brin and Page were doing their work, two other research groups had essentially the same insight involving how a page’s link structure could be mined for crucial information about the page’s reliability. Later, as Google engineers were scrambling to adjust to their company’s astonishing growth, their seeming improvisations occurred inside a considerable ecosystem of existing ideas. One of many examples is the Paxos Algorithm, developed in 1990 by Leslie Lamport, then a DEC researcher, which provides a way of dealing with results provided by potential unreliable computers, a clear problem in a massively parallel data system like the one Google’s engineers were building. (Incidentally, while many fans

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it may be problematic to assume that Silicon Valley operated one way in the last era and an entirely different way today. of Google think the company emerged fully-formed from the heads of its two founders, the company itself is the first to acknowledge the extent to which its own considerable engineering efforts relied on earlier work by others). The point of all this is that it may be problematic to assume that Silicon Valley operated one way in the last era and an entirely different way today. Descriptions of each era are highly anecdotal; for every example of one pattern for the path that research might take going from lab benches to store shelves, it’s possible to come up with a competing narrative. Consider storage. Much of the pioneering work on the modern magnetic disk drive was done at IBM during the 1950s, and companies have been responsible for the most of the subsequent research responsible for the continuing increases in areal density - the storage equivalent of Moore’s Law. (The cost of storing a unit of information on a disk drive is now 122 million times cheaper than it was in the 1950s). But dramatic disk drive innovations have also occurred in academia, such as the breakthrough notion of RAID storage, developed at UC Berkeley in the 1980s as a way to get highly fault-tolerant storage even while using low-cost, commodity disk drives.

Another critique of our dataoriented hypothesis is that it might unknowingly be a symptom of what has been described as the tech world’s current data fetishism. In many areas, such as language translation and speech recognition, the massive amounts of data available today are allowing companies to fully implement the statistical “machine learning” techniques developed in the 1980s, following the failure of traditional “rulebased” AI. Google Translate is the preeminent example here; while far

& from perfect, its ability to allow a basic understanding of almost any text in any language is astonishing. But the current enthusiasm for data goes beyond implementing machine learning algorithms. Especially in e-commerce, it is assumed that the vast amounts of data we leave behind via our mobile phones and computers have some secret key to our future behavior. The middling success that companies like Amazon and Netflix have with their recommendation systems suggest that much work remains to be done in this

field (much of which will no doubt occur in the academy). Further, it’s possible that we will discover that as long as human beings are involved, past results are no indicator of future performance, no matter how much data one has. All of which are reasons that many people view with alarm any attempt to minimize the importance of research. Companies, this school of thought holds, have a natural tendency to be “free-riders;” to not want to pay for things that don’t obviously and immediately benefit them. Basic research, which even its most traditional supporters say is unpredictable in its distribution of benefits, is precisely the sort of thing that companies in the current investor climate are likely to avoid. Those concerned about the overall state of research today worry that at the very moment that market pressures are forcing firms to pull back on R&D, the government is under economic pressure of its own, and is not able to play its familiar role and take up the slack. Thus, the basic view is that by ignoring research, we won’t be creating the ecosystem that will allow the next Google to be formed. In a similar vein, these people would have a different interpretation of current events than those offered by critics of the Standard Model. For example, it’s common now to hear the

observation that academic computer science has been “overtaken” by data science that can be done better by the big tech companies; that academic computer science departments seem to be lagging, not leading, in innovative ideas. One explanation of this apparent phenomenon involves our hypothesis that all the basic work has already been done, which is why academic research seems to so closely resemble commercial research. But another interpretation is that universities are faced with a decline in federal research dollars, and so to attract corporate sponsors, they must essentially pander to what they assume to be the current preoccupation of potential funders. We must also be careful about assuming that the yawning gap that now exists between a Google and virtually any other company or academic department will remain forever. In fact, several forces are at work to narrow it. Improvements in disk storage continue apace; a petabyte 3.5 inch drive should cost $250 or so within the decade. In addition, there are many efforts underway to turn the building and running of a giant data center into a commodity undertaking, no more difficult than setting up a corporate LAN. These efforts are occurring in academia as well as in a new breed of Silicon Valley startups dedicated,

Those concerned about the overall state of research today worry that at the very moment that market pressures are forcing firms to pull back on R&D, the government is under economic pressure of its own, and is not able to play its familiar role and take up the slack. 15

undertaking, where the investment calculus is entirely different - VCs say that their ideal remains research whose commercial appeal is demonstratively obvious. Or, as a spokesman for Sequoia Capital, currently one of the most successful of the fabled venture firms along Palo Alto’s Sand Hill Road, “In our little corner of the world, we get involved in the “D” part of R&D. We leave it to the very creative and very capable talents at universities, government labs and corporate centers to dream up a world of new possibilities.” In closing, there is no doubt that the massive scalability of Internet-based businesses has changed the way we think about research. The urgency created by these scale effects is based on the sheer amount of data available: which poses not just monetization but research opportunities that are here and now. The world has changed, and in the following section we summarize the contrasts in that journey from then to now.

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We must also be careful about assuming that the yawning gap that now exists between a Google and virtually any other company or academic department will remain forever. In fact, several forces are at work to narrow it. Improvements in disk storage continue apace; a petabyte 3.5 inch drive should cost $250 or so within the decade.

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for example, to providing versions of Hadoop and its related tools that an average IT shop can use. It need be noted that even we, in our deliberately provocative role questioning assumptions about research, would have to agree that there are potentially revolutionary breakthroughs on the horizon. An obvious one involves quantum computing. Computer scientists disagree about the repertoire of problems that a quantum computer could effectively take on. But in the very least, they will force us to rethink the encryption systems currently responsible for all Web commerce. Another potential breakthrough involves a fundamental algorithmic advance in learning how to parallelize computing problems. Microprocessor companies have long since given up on making a single chip that runs ever-faster; chips today ship with four or eight (or even 64) “cores,” each of equal power. But just as it takes nine months to make a baby, most software problems need to be solved in order, one step at a time. A fundamental algorithm to change that - not that anyone has any idea of what it might look like - is inevitable . Finally, we’d also like to point out that even in a world of constant change, some things endure. One is the role played by venture capitalists. VCs have never seen themselves in the business of funding basic research, and certainly don’t these days. Outside of biotechnology - an entirely different

Services

Software B - 1975 Digital Equipment Corp initiates development of a new operating system, code-named Starlet, which will become the widely-used multi-user operating system known as VMS.

B - 1991 The world’s first website is created at CERN, the employer of Tim Berners-Lee, credited with marrying hypertext to IP protocols.

A -1969

UNIX operating system developed at AT&T’s Bell Labs, offering multi-user, multi-tasking features. Today’s Mac OS X is a descendent.

A - 1985

Stewart Brand and Larry Brilliant start a dial-up BBS called The Well, which becomes the first online virtual community and one of the first commercial dial-up ISPs.

Milestones in Technology R&D

First SMS from phone-to-phone sent in Finland.

C - 1993

Salesforce.com the world’s first softwareas-a-service (SaaS) company founded by ex-Oracle execs.

D - 1999

Leslie Lamport at DEC develops the Paxos algorithm, later used by Google.

D - 1990

D B

E C

W3C releases first public draft of its Web Services Architecture which shows interoperable software systems communicating and described via XML.

E - 2002

F - 2008

Mark Zuckerberg launches facebok.com website.

F - 2004

G - 2010

Y-Combinator cloud storage startup Dropbox is founded, five years larter ios being valued at $5 billion.

G - 2007

Apple’s AppStore opens in July as an update to iTunes, iPhone 3G ships the next day with it preloaded.

H - 2008

Yahoo! announces it has launched the largest instance of Hadoop data managemnent software running in a cluster of 10,000 Linux processor cores.

H - 2008

HP announces development of a Memristor based on titanium dioxide film.

2005

Google, Motorola, HTC and others form Open Mobile Alliance to promote Android ecosytem.

G - 2007

Google introduces a software framework for managing large data sets across distributed computer centers called Map Reduce.

G - 2004

HP announces development of a Memristor based on titanium dioxide film.

VMWare is founded and patents its hypervisor virtualization tools.

F - 1998

Bell Labs introduces the first megabit memory chip.

E - 1984

Veteran entrepreneur Paul Graham co-founds Y-Conmbinator, which becomes the one of the most powerful startup incubators of modern times.

LINUX operating system devceloped by Linus Torvald, built on open software licensing By June of 2010, LINUX was the OS for the 10 fastest supercomputers on the planet.

E - 1991

D - 1980 Sony and Philips collaborate to standardize Compact Disc audio format.

C - 1971 Leon Chua publishes a paper describing basic principles of a Memristor

F - 2005

2000

Apache Software Foundation is formed to support Apache web server software.

1995

E - 1999

1990

Famous Silicon Valley networking organization Chruchill Club holds first meeting, with keynote by Robert Noyce, inventor of the integrated circuit.

D - 1985

Insignia Solutions introduces SoftPC Windows emulator for Sun workstations, ushering in desktop virtualization.

C - 1970 SRI International founded as a separate research institute from its parent, Stanford University. PARC founded as research arm of Xerox Corp.

1985

C - 1988

Gordon Moore publishes article in Electronics claiming density of components on an integrated circuits doubles annually.

B - 1965

A - 1947

IBM Research (The Watson Scientific Computing Laboratory was founded at Columbia University in New York)

John Bardeen and Walter Brattain, Bell Labs invents transistor

B - 1945

A - 1925

1980

Western Electric Laboratories and an engineering department of the American Telephone & Telegraph company consolidated to form Bell Telephone Laboratories, Inc.

1960

The Researcher’s Journey:

Hardware

Organizations

1940

Work begins on UnQL, Unstructured Query Language, result of NoSQL movement.

I - 2011

2010

Voices from Silicon Valley Peter Lee Microsoft

How a traditionally-organized research division keeps up with new trends in research.

Joel West

You thought it was just a bunch of dorm room hackers, but more and more scientists are hanging out shingles at Facebook.

Mendel Rosenblum

If you’re a company thinking you can invest your way into some cheap Silicon Valley research, prepare to have your pockets picked.

Peter Norvig Google

There are lots of smart people at Google, but they don’t do much “blue sky” open-ended research. Except when they do.

Stanford, VMware

Rich Friedrich HP

The path from basic research to a big company is circuitous, which is why it is so seldom-traveled.

David Patterson

Robert Ackerman Allegis Capital

“Open Innovation” is an exciting new way to think about research, assuming it’s not just a fancy way of cutting the R&D budget.

Facebook

Entrepreneur

It’s very hard for companies to think long-term enough to invest in research. But they need to anyway.

Keck Graduate Institute

Cameron Marlow

Judy Estrin

UC Berkeley

The great American research system has produced many successes, and we tamper with it at our peril.

It may not be like the old days when Bill and Dave were still around, but basic research continues at the company they founded.

Norman Winarsky SRI International

Internal R&D is over-rated, and often capable of doing more harm than good.

Peter Lee Microsoft A Proud R&D Traditionalist

As new managing director of Microsoft Research Redmond, Lee heads up one of the computer industryâ&#x20AC;&#x2122;s few remaining research operations patterned after the labs of an earlier era - autonomous and setting its own lab direction.

orange: People often compare Microsoft Research to the Bell Labs of old. What do you think of that comparison?

peter lee:

There are some valid comparisons. We are an

independent organization, so the business groups don’t tell us what to do. Culturally, our researchers are motivated differently, maybe in ways that weren’t as true at Bell Labs. They’re highly motivated to get their research ideas onto every desktop and into every data center in the world. Even in the short time I’ve been here, I’ve been astounded at the ambition level

How is it organized? Research areas are like departments in that they have twentyfive to fifty researchers and research engineers. And the research areas are organized around a broad, major direction in computing. For example, machine learning, visualization and user experience, and large scale data and analytics. What do you think of some of the newer ideas that people are talking about - things like prizes or crowd sourcing or open innovation, etc?

that researchers have when they think they have a good and

Oh, I think it’s incredibly interesting. The potential for what

useful research result.

can be learned through these kinds of experiments is really,

I talk a lot of about three lanes of basic research. One

really strong and, furthermore, it’s a way to really engage a

lane being a kind of mission-focused research where we’re

much broader community and increase the idea flow in ways

reacting to known problems. The second lane being blue

that are pretty important. And so today in Microsoft Research,

sky research, often in concert with the academic community.

for example, we’re studying research ideas really closely

And then the third lane being the uncomfortable search for

and they’re very likely to affect a lot of things that we do.

disruptions. We try to have equal rewards for all three lanes

For example, we’re watching very closely the huge amount

of research here, but also demand that we get good impact

of activity in both the academic and enthusiast communities

in all three.

around Kinect hacks. That is an example of something that just kind of spontaneously grew up on its own but is a tremendous

You say you demand returns. How do you measure them?

potential source of new, innovative ideas.

Each department or each division is expected to show

Would you say the trend is good or bad?

impact; to show scholarly impact and leadership impact in the academic community. Show impact on our product groups,

I don’t see it as either/or. The things that Microsoft Research

and show impact in terms of progress towards developing

does for Microsoft, couldn’t be done any other way. We’re a

really disruptive new technology.

teeny, tiny part of Microsoft, but our impact on every single Microsoft product is really significant, and the visibility that we have within the company is really amazing.

to show scholarly impact and leadership impact in the academic community. Show impact on our product groups, and show impact in terms of...really disruptive new technology.

“

Each department or each division is expected to show impact;

done any other way... our impact on every single Microsoft product is really significant, and the visibility that we have within the company is really amazing.

Examples? So the huge amount of the innovation in Bing is a direct result of our partnership with the Bing group. A huge number of the underlying algorithms that power Microsoft Office. All the machine translation products. All the cloud services - Azure, SQL server, Hotmail - have their origins in Microsoft Research. And we provide services for predictive analytics of software defects in a huge range of software development projects. It’s hard to imagine crowd-sourcing those sorts of things. Having said that, crowd-sourcing and mass globalization

“

The things that Microsoft Research does for Microsoft, couldn’t be

Why do you think basic research has the reputation that you can’t measure its ROI? What is it that the people are not seeing, or are forgetting, when they have that perspective on basic research? There’s probably a cyclical nature to this. Within the company right now, the perspective on Microsoft Research and the value of Microsoft Research are possibly at an all-time high. And so it’s a very good time. But I’m a realist also. I understand that these things come in cycles.

concepts are extremely interesting, and we believe they are potentially a great source of innovative ideas. There’s a pretty strong correlation between how profitable a company is and how much it spends on research. Do you worry about funding from Microsoft Research being cut in the event company profits decline?

The take-aways

We’re such a small part of the company cost-wise and I think, at least the attitude right now is that, in fact, our positive impact on the company relative to our size is pretty enormous. And so viewed like that it doesn’t seem like there’s much to worry about. Of course, we want the company to be very successful and be more successful every day, but objectively I don’t think there’s an issue about our security here. Except that, and this is something I also learned at DARPA, people doing basic research everywhere in this country have certain anxieties about society’s understanding and tolerance about basic research. And so our researchers here aren’t immune to that.

Even when you’re at a company with a long-term commitment to research, it’s nice to have the occasional hit on your hands to keep the top bosses happy.

Joel West Keck Graduate Institute of Applied Life Sciences “Open Innovation” and Its Discontents

There is no issue related to the management of R&D more popular at the moment than “Open Innovation.” Joel West knows as much about it as anyone, making his commentary on its occassional misuse worth nothing. A consultant and business professor at the Keck Graduate Institute, he is also co-editor of Open Innovation:

Researching a New Paradigm from Oxford University Press.

orange: As far as big ideas in business, Open Innovation seems

A lot of companies are cutting research budgets these days, and one

in fashion, a kind of This Year’s Model.

can imagine Open Innovation appealing to them as a way of getting research on the cheap. To what extent is that part of the allure of it?

joel west:

Academia has its own fashions, and this is a

particularly hot area, in the way that the “Resource-Based View of the firm” was hot 20 years ago. If you look up “Open Innovation” on Google Scholar, you see that there are thousands of papers. It’s come from nothing in 2003 to where it is today. What is new about the idea? Or is it just a useful name for something people were already doing?

That has certainly contributed to the interest in Open Innovation. When I go and talk to people out there, a lot of the interest is from companies who either A) want to get rid of their R&D people or B) just gutted their R&D department and want to know what they should do next. Do you think the phrase is being overused? We don’t have a term for it, but there is an Open Innovation

Some people call it the “Old wine in new bottles issue.” Some

equivalent of “greenwashing.” Greenwashing is where people

people say this is a practice that’s been going on, and it’s just

wrap themselves in claims of environmental-friendliness, but

been given a new name. Certainly, what’s true is that much of

don’t change their actual practices to make their products

this was already going on.

more marketable.

But there are major differences from the past. One is that

When I use Google to see how corporations use “Open

in the Open Innovation approach, the firm is agnostic to the

Innovation,” I’d say only about a third of it is really legitimate;

sources of innovation.

“

...the firm is agnostic to the sources of innovation. To be neutral about whether the technology comes from inside or outside is a culture shift for any large, multinational corporation.

To be neutral about whether the technology comes from

the rest of it is just people want a buzzword to make

inside or outside is a culture shift for any large, multinational

themselves seem more innovative and more trendy.

corporation. In the past there’s been an arrogance at many

large industrial corporations, in which they assume they know

Innovation, there is an attitude change and they really are

better than anybody in the world. Open Innovation forces

being more collaborative. At other times, it’s just a new name

firms to consider outside technologies, rather than saying,

for something they’ve always done, and they’re just calling it

“We have to invent it if it’s going to be something great in the

something else.

market.”

A related issue is the recognition by a company that

not all the smart people in the world work for them. That recognition, I think, is new.

Once upon a time, you could have said that the smartest

people in computing worked at IBM.

But then came the fragmentation of the computer

industry with the PC revolution. You saw manufacturing and product development going offshore and the Internet’s dissemination of information, and open source software. And all of a sudden, people realized that the idea that any

In many cases, when they appoint a VP for Open

Like sponsoring research at universities? They could have a universities relations arm. They could have ecosystem management or technology sourcing or technology IP procurement. They could have, on the other side, a patent licensing office. Normally, the Open Innovation Officer, VP or Senior VP or whatever, the Director of Open Innovations, is the person bringing innovations into the firm. They usually don’t give that title to somebody who’s trying to find markets for existing technology.

company - even the greatest company in the world - could have a monopoly or a preponderance of knowledge in an area just isn’t plausible.

“

The fundamental argument of Open Innovation is that your R&D operation needs to have competition the same way that any other

aspect of your company needs to have competition. Apple makes some have the scale or the technology.

“

of its own parts, but it also sources things outside where it doesn’t

Do you think Open Innovation is a good idea, in and of itself, or is it just something that companies in an era of diminished budgets are forced to resort to out of necessity or expediency? The fundamental argument of Open Innovation is that your R&D operation needs to have competition the same way that any other aspect of your company needs to have competition. The vertically-integrated company - where everything is done

The take-aways

in-house and we always use our in-house janitor, our inhouse printing press, our in-house HR manager - that is not the way business is done today. Apple sells things through its stores, but it also sells things through other stores. Apple makes some of its own parts, but it also sources things outside where it doesn’t have the scale or the technology.

Like many things in business, Open Innovation is

Really, what Open Innovation is saying is that firms ought

to be aware of what the best technology is for anything relevant to their line of business. They shouldn’t automatically assume that they do it in-house, nor should they automatically assume

part-real, part-hype. The real

that they do it outside. Instead, they do need to monitor the

opportunity from Open Innova-

able to say when necessary, “Look, this part of our technology

tion is when a company is open to all good sources of ideas. The hype comes with companies that hide behind the term as a euphemism for cutting research budgets.

state of the art of what’s going on outside the company, to be is just not state-of-the-art.”

Cameron Marlow Facebook

A Hot Start-up Begins Its R&D Rite of Passage

The only â&#x20AC;&#x153;research problemâ&#x20AC;? most people associate with Facebook is figuring out how to add enough servers to keep up with its user base. But Facebook is starting to learn the lesson of many tech companies; that if you are in it for the long haul, youâ&#x20AC;&#x2122;ve got to start planning for it.

orange:

So why exactly does Facebook need researchers?

Don’t you guys just sit around and keep growing?

How do you distinguish research from engineering? Couldn’t someone be listening to everything you’re saying and say, “That’s not research.”

cameron marlow: I wouldn’t say that we’re “Facebook Research,” with proper nouns, but Facebook does a lot of research. We’ve hired a number of people and published a

The types of questions we’re answering are as fundamental as any academic question could ever be.

number of papers. A lot of researchers coming out of graduate school, especially those interested in corporate research labs, want to do great work, but also want to have an impact on people’s experience. The image I’ve tried to present for research at Facebook is one where we work as closely with the product as possible, because the problems we face are some of the most interesting problems that exist. How often are people surprised when they hear about Facebook doing research-research as opposed to engineering? I guess I may be a little biased, but I don’t think anyone’s surprised that I’m doing research, or the people that I work

The social interactions on the Internet, and on Facebook in particular, are at a level of detail and scale that haven’t existed before. They allow us to answer questions about social interaction and social forces that we’ve never

with are doing research.

been able to answer...

We all come from like a very Internet-friendly research background, and it’s kind of

expected that if we came to

to answer, even though some of these questions are as old

Facebook, we’d be doing some

questions exist doesn’t mean we’re going to answer all of

kind of research.

the day of a typical engineer, we need to answer questions like,

as the discipline of sociology. Of course, the fact that these them; there isn’t perfect alignment in everything we do. But in “What is the average size of a person’s personal network?” or

We all come from like a very Internet-friendly research

“How does that affect the way they use the product?”

background, and it’s kind of expected that if we came to Facebook, we’d be doing some kind of research. The

Can you give me an example of work you’re doing at Facebook that

publishing model here is a little different than some other

someone in the academy would look at and say, “Yeah, that would

companies. In other research operations, there is an emphasis

be legitimate computer science research if it were happening in my

on the number of papers researchers publish, and the talks

department.”

they give. Whereas here, the papers and talks are the gravy. Your real work is working on problems. So there is a bit of a different incentive here. People really want to make users more happy. I think it attracts a different type of researcher.

I could go on for an hour. We have a lot of interesting work that’s being done with taking our code base and compiling it into C. The compiler community is very interested in HipHop (Facebook’s internally-developed compiler). The issues that we have with data center usage put us among a very small number of companies facing issues that are central to the future of computing. We work a lot with academics on these problems. And not just from computer science, but also the social sciences.

How would a traditional researcher find working at Facebook? I think in a traditional research lab, I would build the prototype, and then I would show that prototype to a product team, and then over the course of months, I’d report to them on my progress at developing my idea into a real product.

everyone. You have your sandbox to work in, so

instead of working on a prototype, you’re working on a prototype that’s actually connected with the product.

“

Here at Facebook, the code base is available to

Here at Facebook, the code base is available to everyone. Do you think people pay more attention to your work

You have your sandbox to work in, so instead of working on

simply because you’re at Facebook?

a prototype, you’re working on a prototype that’s actually connected with the product. When you’re done and people

We have a PR department here that likes to put us in front of

have seen it and they give you the thumbs-up, you commit

reporters, and even though the types of things we generate

your code. You don’t wait around for some product team to

are on the academic side of things, they tend to be of

give you a blessing and build it themselves. If you know how

great interest to the world. So almost every paper that we

to do it, just do it yourself. People at Facebook are actually

publish is turned into a much bigger communication about

making changes to the core product, which may not be part

Facebook than just the simple record of the fact that we

of the DNA of other companies.

published a paper.

What do you think of the way research used to be done at big technology companies? The model I used to think about the standard corporate research labs is that the company was like a planet, with the

The take-aways

lab being in orbit spinning around the planet, and in case the planet implodes, there’s some chance that this other heavenly body would spin off and allow the company to continue on. But I don’t think that actually ever happened. I can’t think of a time when an AT&T Labs or a Xerox Park fundamentally changed the way that the core company operated.

nies have many advantages, not the least of which is that

I can’t think of a time when an

researchers can get an idea

AT&T Labs or a Xerox Park

into the hands of millions

fundamentally changed the way that the core company operated.

“

Successful young compa-

of users in not much longer than it takes to test the code. 27

Mendel Rosenblum VMware, Stanford On Being A Basic Research Poster Boy

Rosenblum, as an associate professor at Stanford University, did the original theoretical work that led to VMware, making him one of the handful of Silicon Valleyâ&#x20AC;&#x2122;s rare entrepreneurs who was able to grow some basic research into an enormously important company.

orange:

First off, do you even agree that the work you did on

virtualization would qualify as basic research?

mendel rosenblum:

I was involved with a group of

people trying to build a super computer, a very, very, large machine. But I wasn’t really interested in scientific computing, so I was trying to find out if we could use it for something else, like running a whole enterprise’s worth of computation. That’s how we stumbled on the idea. If you look at the original papers, we were talking about running a bunch of virtual machines with modern computing environments on a single machine. We didn’t know it at the time, but the vision turned out to be the right one.

“

I was trying to find out if we could use it for something else, like running a whole enterprise’s worth of computation. That’s how we stumbled on the idea.

In what sense was that unfamiliar terrain back then? The idea of virtual machine monitors was actually invented by IBM in the late 1950s and early 1960s. But as PCs became more common, it pretty much died as a research idea. I’m an experimental system builder, and so I propose systems, and when I demonstrate them, I try to build prototypes of them. In the original paper, I re-launched virtualization. It was a mixture of old and new ideas. Some of the newer stuff, like the transparent memory sharing, hadn’t been done before, Did you have anything commercial in mind at first?

So why the PC? The nice thing about trying to do it for the PC was it was pretty clear we didn’t depend on anybody. The PC was opening up, and we knew what the hardware did, so it made it more of a tractable problem to do it as an outside company. Who pushed you to do the company? I had two graduate students, and they’re actually the two graduate students who have helped found VMware, Edouard Bugnion and Scott Devine. They’d been sitting around

We were going to do a virtual machine monitor for one of

watching the Yahoo guys, David Filo and Jerry Yang, take

the big servers like Digital Equipment or HP. That’s what our

off and become famous. So they immediately said, “Can we

research was on: building software for the big servers. And

commercialize it?” It wasn’t an ideal time for me, because I

so we went and talked to the companies making them, and

was coming up for tenure. But I talked to (Stanford University

the first one said, “Why don’t you just come and join us and

president) John Hennessy about it, and he told me he had

do it as an employee?” But that didn’t sound very interesting

started MIPS when he was coming up for tenure, so he didn’t

to me.

see a problem.

Why not? Oh, I don’t know. I guess we had the idea that you’re not going to get like rich and famous building up a big company if you do it as a team inside a big corporation. I remember talking to a vice president at Digital Equipment Corporation, and he named these examples of projects that they had nurtured inside DEC and then spun out. As far as I could tell, they were all disasters.

Okay. Fast forward to the world today. Do you think research is sufficiently appreciated at tech companies in Silicon Valley? The problem is companies are focused on how something is going to return to the bottom line. Basic research is getting pretty rare. People have to get funding from product groups. That means you have to convince a product group that what you’re doing will help them at some point in time.

to the bottom line. Basic research is getting pretty rare.

“

The problem is companies are focused on how something is going to return

How research-friendly was VMware in the days when you had something to say about it? Well, VMware viewed itself as an innovative company, and one of the ways we hoped to stay ahead of the competition was to out-innovate them. So there was a focus on trying to keep innovation going. But basic research - research where it’s not obvious how it’s going to apply or benefit - that just wasn’t done. Some people might say you weren’t living up to your own ideals. It’s definitely true that when you’re in a position at a company, and you’re looking at where to spend your money, everything is focused on the short-term of the company. With research,

The take-aways

the hardest thing for people is that you don’t really know how you’re going to benefit from it. So if you can’t really figure out what it’s going to do, chances of it being funded aren’t going to be very promising.

motivated by many things, including reading about how rich and famous other graduate students have become. Academics who hope to also

“

It’s definitely true that when you’re

in a position at a company, and you’re looking at where to spend your money, everything is focused on the short-term of the company. With

do well in the marketplace

research, the hardest thing for people

would be wise to surround

is that you don’t really know how

themselves with them. 30

you’re going to benefit from it.

“

Graduate students are

David Patterson UC Berkeley The Best Days of Traditional Research Still Lie Ahead

Dave Patterson is an embodiment of the elite of traditional academic computer research. He is a professor at UC Berkeley, known for his microprocessor architecture work with Stanfordâ&#x20AC;&#x2122;s John Hennesey, and recipient of numerous prizes and recent president of the ACM.

orange:

There are people who think that computers and IT

have gotten so mature that we can now leave it to private industry

What are some examples of research that don’t just cure headaches but open up new possibilities??

to fund R&D the way we once did with telegraphs or radios or TV. What do you think?

Well, kind of a nerdy thing is the Parallel Computing Challenge. Easy-to-program parallel computing is the hardest

david patterson: That’s just crazy. We’ve just scratched

problem computer science has faced. We’ve been working

the surface of information technology. In my career, I can look back to the things I learned when I was a student that my own students laugh at when I tell them.

on it continuously for 50 years. We’ve been trying to work on

finally going to solve it.

It’s going to be the same way when they’re older. One

making progress on it. Everything that Intel ships has parallel cores in it. The whole industry has bet its future that we’re

example involves all the security problems we have with the

technology we invented. If we have solved those problems,

technology stack to make parallelism a first class citizen.

why is there WikiLeaks? The weakness of our technology is a

It’s up to programmers to deliver on Moore’s Law now. We

major security threat to this country. It’s embarrassing that it’s

can put more transistors into chips, but we can’t turn it into

so vulnerable. People are relying on programs like Windows

performance unless we solve one of the hardest problems

NT for safety and control of critical systems. Those of us who

computer science has ever faced.

have been in this field for a while are embarrassed by it.

Technology is amazingly cheap and amazingly fast. But

companies have tried and failed with the bet that they could

there are still real big holes. You might call this the “headache

finally make easy-to-write parallel programs. There’s a Dead

model” of funding research.

Parallel Computer Society filled with names of companies

So we are forced to transform the whole information

It’s not a controversial statement. Lots of start-up

funded by venture capitalists.

Technology is amazingly cheap

How much of the research now being done at Berkeley can only be

and amazingly fast. But there

the industry?

are still real big holes. You might

So what are the advantages that we in academia have? We

call this the “headache model”

things can’t be done. The U.S. university system is the best

of funding research.

done in academia, and how much of it could be done someplace in

get brilliant people from all over the world who don’t know that in the world. If you ranked the top ten universities, probably eight of them would be here.

So why in the world would you want to leave out a really

bunch of brilliant people? Sure, industry does a lot, but industry often, especially today, has a shorter term focus. We can take this longer term. And we also have an extremely valuable by-product, in that we produce the next generation of leaders.

Of course, what’s happening is that start-ups play a more

important role in the field than when I got here. But start-ups aren’t supposed to be doing research. If a venture capitalist thinks a startup is proposing to do research they back off.

“

It’s up to programmers to deliver on Moore’s Law now. We can put more transistors into chips, but we can’t turn it into performance unless we solve one of the hardest problems computer science has ever faced.

“

There are also good reasons to work with industry,

We get brilliant people from all

aren’t there?

over the world who don’t know

Yes. It’s easy in academia to pick problems that most people

that things can’t be done. The U.S.

industry. Pasteur invented pasteurization so he could drink

university system is the best in the

also solved a problem. When we interact with industry, we

don’t care about. And that’s an advantage of interacting with milk. He made a fundamental contribution to science, but

world. If you ranked the top ten

understand the problems more like eight or ten years down

universities, probably eight of them

later, we have something that can be impactful.

would be here... Of course, what’s

What are some other favorite unsolved problems, where we still need

happening is that start-ups play a more important role in the field than

the road. We start working on them so that five or six years

deep, basic innovation? We’re actually making advances through statistics and machine learning on what might be called “augmented

when I got here. But start-ups aren’t

intelligence” instead of “artificial intelligence.” Like cars that

supposed to be doing research. If a

difficult for cars to crash, the savings in lives, in medical bills,

“

venture capitalist thinks we’re doing research, they back off.

couldn’t crash. If we were to set a national program to make it in dollars would be just phenomenal. There have been enough advances in a lot of the fields that it is not a ridiculous goal to have a national program to dramatically reduce traffic deaths and traffic accidents. We have lots of pieces of the technology to make this real, not science fiction.

When did the start-ups begin playing more of a role? Well I should say today graduate students are more tempted today with some new and exciting technologies rather than finishing their PhDs, so they decide to go and maybe start a company.

...today graduate students are more tempted today with some new and exciting technologies rather than finishing their PhDs, so they decide to go and maybe start a company. It seems that there could be a lot of downside to that. If this was happening all the time it’d be hard for the university. If 75% of project stopped, it would be hard to be able to complete research projects at universities. But it’s not that common. It happens, but it’s manageable.

The take-aways Patterson is a strong advocate for the old-fashioned idea of basic research as an endless frontier, where the answers to today’s questions give rise to a new set of queries that lay the groundwork for the next generation of inquiry. 33

Judy Estrin Entrepreneur The Dangers of Taking Research For Granted

Estrin has been an entrepreneur, (Bridge Communications) the CTO of a big tech company (Cisco), a board member for several major corporations (Disney, FedEx, Sun and Rockwell ) and has written about research (Closing The Innovation Gap).

orange:

You’ve been on many boards of directors. What have

you learned from that experience about corporate research?

The major problem with research only being in academia

is that you can only go so far in a university lab. The labs are relatively small. We’ve gotten a little spoiled because

judy estrin: The average term of the CEO is three to four

in the software industry you can go directly from academia

years. But basic research happens on a five- to ten- to 15-year

to a venture financial company - Google, Yahoo - because

time frame. And so if you’re incentivizing your management

they’re based on an algorithm. But if you’re looking at things

on a two- to five-year time frame, you’re not going to get basic

like systems - clean tech, biotech, complicated hardware - it’s

research. At best you’ll get applied research, or advanced

tougher. There is a gap in between academic discovery and

technology. So one after one - and there are few exceptions

what a venture capitalist will fund. It’s what I call the “lab gap.”

- companies have pretty much taken what they called their “research” and made it more applied.

What they have said in their defense is, “We’re connecting

our research closer to the customer, so that we will get more benefit from it.” And it really is a benefit not having labs isolated, so researchers are more connected and can produce things that the company can profit from. The disadvantage is if you are focused on connecting to today’s customers, you won’t get a very disruptive technology. The customer doesn’t

But if you’re looking at things like systems - clean tech, biotech, complicated hardware - it’s tougher. There is a gap in between

know what they might need ten years from now.

academic discovery and what a

What can companies do?

venture capitalist will fund. It’s

I don’t think they can afford to do what the corporations of the

what I call the “lab gap.”

past did, meaning build big labs. I’m not even sure that works anymore. But I think that they can afford to do a few things. Intel tried for a while what they called Lablets. These were

So what is wrong about research moving to the academy?

groups of researchers that were co-located with academic researchers. They had this very tight relationship with a couple

As a result, the responsibility of research has more and more

of universities and then it actually was a very interesting

fallen to academia. Now, unfortunately, what has happened in

model for leveraging their resources with academic resources

academia is that while there is some great research going on,

to further research.

but it is not getting enough funding. The scarcity of funding causes researchers to be more risk-adverse, because they want to submit grants that are more likely to get funded. So we miss the wild and crazy ideas, the ones that you want to have happen, even if they’re going to fail, because in the research environment you learn from failure. Look at the opportunities that are out there on the intersection of IT and nanotechnology and biotechnology, or look at our ability to start understanding neuroscience better because we now have the tools. The stuff isn’t getting funded.

is some great research going on, but it is not getting enough funding. The scarcity of funding causes researchers to be more risk-adverse...

“

...unfortunately, what has happened in academia is that while there

the success over the long term...I have this fundamental belief that a leader in an industry needs to have some component of this longer term thinking.

“

Research has nothing to do with the success of today. Research has to do with

have some component of this longer term thinking. And again at least when I was there, which was the peak of the bubble, Let me ask you a question about Cisco. They are pretty well known for their sort of acquisition model of research - meaning they tend to

everything was about time to market, taking advantage of the market.

buy things rather than develop them internally. Do you think that’s a

There are people who say, well, Groupon isn’t doing research,

good strategy?

Facebook isn’t doing research, Zynga isn’t doing research. Doesn’t

Cisco used acquisitions for advanced technology and for furthering innovation. There’s no research in that equation.

the success of these companies show that researchers are decreasingly necessary?

When I was there, Cisco did no research. There was no focus

Research has nothing to do with the success of today.

at all on the basic research or the longer term stuff. They did

Research has to do with the success over the long term.

some funding of people in academia, and did some donations

So you have no idea where Facebook is going to be five or

to networking groups at different universities. But it was

ten years from now. I would point to Google as an example

generally not basic research. And I think they have changed

that has always had a little bit more of a commitment to, not

some, because after the bubble burst, they realized that

necessarily basic research, but advanced technology. They’ve

maybe there weren’t always going to be companies out there

always spent some of their money on stuff that isn’t about

to acquire, and that were some areas where they needed to do

today. I think it’s the reason why Google has continued to be

more of their own research. TelePresence is a good example

able to grow.

of stuff that they did more internally, although it started with an

acquisition. One of the disconnects when I was there, I have

these companies are based on research that was done 20 or

this fundamental belief that a leader in an industry needs to

30 years ago. If we hadn’t built the Internet, if Tim Berners-Lee

I will point out that Facebook and Groupon and all of

hadn’t built the Web, if he hadn’t, you know, done some of the algorithmic stuff, Facebook wouldn’t exist. Any ecosystem of innovation has three pieces to it. It has

The take-aways

research, development and applications, and you can innovate in any one of those communities. And they all feed off of each other. But they have to be in balance. If you cut off research ultimately innovation in development and application will die. It may take 20 years, but it will ultimately die.

Estrin is one of a breed of

I will point out that Facebook and

business leaders who have

Groupon and all of these companies

become alarmed at the cur-

are based on research that was done

rent lack of regard for basic

20 or 30 years ago. If we hadn’t built

research, and are using their positions of influence to call attention to the issue. 36

the Internet, if Tim Berners-Lee hadn’t built the Web, if he hadn’t, you know, done some of the algorithmic stuff, Facebook wouldn’t exist.

Robert Ackerman Allegis Capital What VCs Wonâ&#x20AC;&#x2122;t Tell You About Silicon Valley R&D

Ackerman is a venture capitalist, but more specifically, one associated with the International Business Forums and its conference on Corporate Venturing and Innovation Strategies, for companies interested in research-oriented alliances with Silicon Valley VCs.

orange: What do companies need to know if they want to invest in Silicon Valley?

But a lot of companies do investing that’s strategic rather than immediately financial. Aren’t the rules different for them?

robert ackerman: Venture capital is a club, a tight little

If you’re not making money, then you’re not safe. “Strategic”

club, organized around managing risk. As a VC, I want to invest

means “losing money.” You go into a corporation, and

with people I’ve invested with in the past, because I know

everything that’s “strategic” is losing money. When budgets

how they’re going to be there when times are good and when

come under pressure, you do not want to be “strategic.” You

times are tough. We syndicate. We share information. I’ve got

want to at least be carrying your own weight. That’s the problem for these programs. Many times in the

everybody calibrated. But a corporation is different. The corporation walks in

venture ecosystem, the time that it takes to really begin to

and says, ‘Hi, I’m from a big global company. Perhaps you’ve

realize those strategic benefits is outside of this cycle. And so

heard of us. We operate in 110 companies around the world.

it’s very, very difficult to build a sustainable program

We have 140,000 employees. We have a market cap of $42 billion. And we’re inviting ourselves to your party.” The polite venture capital response to them is, “Fantastic, let’s find things we can collaborate on.” But what the venture capitalist is actually thinking is ‘Okay, what can I sell to this guy? How do I pull money out of his pockets and use it for whatever I need to get it into?”

“Strategic” means “losing money.” You go into a corporation, and everything that’s “strategic” is losing money.

So what should he say instead? The more truthful kind of response would be, “Who cares that you’re a big global company, because you may be here today, but you’re going to be gone tomorrow. You’re reassuring me

When budgets come under pressure, you do not want to be“strategic.”

of your commitment, but you’re corporate direction is going to change. You’re not a long term player. And so you’re going to be a tool of convenience for me in my ecosystem.” That seems pretty cynical.

The history of corporate venturing, with few exceptions, has born that out. They get in, and they get out. Every two years, you’ll have new people in place. You’ll have changes in strategic direction. Corporate priorities will ebb and flow. When the markets get competitive, the top corporate guys look at the venture program - which is usually generating losses - they say ‘Who got us into this? Fire him. Get us out of it.” They forget everything they learned. But five years later, they’ll decide to start all over again.

“

The history of corporate venturing, with few exceptions, has born that out. They get in, and they get out. Every two years, you’ll have new people in place.

It sounds like it comes in waves. It’s fascinating. We’re seeing a wave of this again. It’s picking up again, and they’re all going to go make the same damn mistakes. They’re just going to do it again. Venture capital is a game where you’ve got to be inside baseball. The corporate guys can’t integrate into our world because they’re slow, they’re pondering. There’s a whole culture around these large corporations. That’s why they don’t innovate quickly. We want to be able to reach out to them, on our terms, where we can leverage them. But they can’t get in the way of what we’re trying to do.

“

The corporate guys can’t integrate into our world because they’re slow, they’re pondering. There’s a whole culture around these large corporations. That’s why they don’t innovate quickly.

So why should companies bother with Silicon Valley in the first place? When you’re seeing the future for the first time, there’s a leap of faith required. As venture capitalists in Silicon Valley, we’re in the business of inventing the future. Yet that’s very difficult to do, and that’s why venture capitalists sometimes have a herd mentality, like, “If one of those is good and successful, we need 400 of them.” But it’s the guy who does it the first

The take-aways

time, who sees it for the first time, who has the conviction to pursue that vision and organize people around him - how rare that type of person really is.

Companies who think they When you’re seeing the future for the first time, there’s a leap of faith required. As venture capitalists in Silicon Valley, we’re in the business of inventing the future. Yet that’s very difficult to do,

can use occasional venture investments to gain access to Silicon Valley research will be greeted with open arms. Then, the trouble will begin. They should keep an eye on their wallets. 39

Peter Norvig Google Staying in Touch With Google’s Academic Roots

As director of research at Google, Norvig has his stars aligned: he is at a highly profitable company with a propensity for hiring Ph.D.’s. Google doesn’t have the same sort of separate research operation that Microsoft does, as Norvig explains.

Some people tell me that university research isn’t as interesting as it used to be, that it’s gotten closer to what companies do.

orange:

Google has the reputation for being crammed with

I think it’s a sign of maturity. In the 60s or 70s, nothing had

Ph.D.’s, but not having a separate, Bell Labs-style research outfit.

been done yet, so it was easy to do something brand new. But

What is Google’s philosophy about research?

now, to build something exciting takes longer. You can’t just

peter norvig: I think we have a bit of an identity crisis, and we’re still thinking of ourselves as a startup. At startup, you get a bunch of Ph.D.’s together, along with the non-Ph.D.’s, and everybody just pitches in. If you have to invent something, you invent it. But you don’t really make distinctions, saying, “This guy’s doing (Research), but that guy’s doing (Product Development). That’s the way it’s always been at Google.

“

before, and here are some results.”

I think there’s still interesting work going on in universities.

Although I also think there are some things you can’t do in universities, and that’s one big reason why I’m not in the university now. You need such a huge number of computers just to put together a lab. As an assistant professor, I might be able to afford five grad students. That would put me at a big disadvantage, compared to the industrial teams.

...We have a research effort, with a couple hundred people out of our 20,000. But 90 percent of our Ph.D.’s are not on the “Research Team.” They’re on the “Engineering Team.”

We have a research effort, with a couple hundred people out

“

go out and say, “Well, here’s a brand new field nobody’s done

of our 20,000. But 90 percent of our Ph.D.’s are not on the “Research Team.” They’re on the “Engineering Team.” Some of their time is spent inventing things that haven’t been invented before. If you want to call that “Research,” fine. If you want to call it “Product Development,” well, that’s fine too. Does anyone do purely speculative, “blue-sky” research at Google? I would say mostly no. But let me qualify that. We don’t have anybody whose job it is to write papers, or to prove theorems.

“

...Everything you do at Google should be useful for something. But we may not know right away how that useful thing will fit into a product.

Everything you do at Google should be useful for something.

Some companies idea of research seems to be that they can crowd-

But we may not know right away how that useful thing will fit

source a question on the Internet whenever they need to know

into a product.

something. What do you think of that approach?

This goes back to the start of the company. People always

say Google’s core competency was “Search.” But when it was

When new things are made, they’re built on the back of a

a research project back at Stanford, Larry and Sergey they

long tradition. So in order to build that something new, you’ve

didn’t think they were doing “Search.” Their idea was, “Hey,

got to have the expertise to do it. Some of that expertise you

there’s a lot of really cool stuff on the Internet, and we should

can get by just reading, or by talking to people that you’re

get ourselves a copy of it and see what we can do.” And so

not paying. But you really have to understand it at a deep

they scrounged around for enough computers, and then they

level. And I don’t think that comes for free. You can’t just say,

started experimenting. And it was only later that they said,

“Oh, I want to play in this new area I know nothing about it, so

“You know, the thing that we can actually do is ‘Search.’”

I’ll put a question on some question site and expect to get a good answer.”

I read a comment to the effect that the Google self-driving car shows why government shouldn’t be involved in research, because Google was able to make a car all by itself, without needing any help from

I also think there are some things

the government.

you can’t do in universities, and

That team that works on the Google car sits in the same

that’s one big reason why I’m not in

the three guys from Carnegie Mellon who were sponsored by

the university now... As an assistant professor, I might be able to afford

building as me, and when I look out over their cubicles, I see government work; a guy from MIT, who has been sponsored by the government; and a couple of guys from Stanford, also government funded. All of them have government dollars piled up underneath them.

five grad students. That would put me at a big disadvantage, compared

...when I look out over their cubicles, I

to the industrial teams.

see the three guys from Carnegie Mel-

A lot of people look around and see companies like Groupon and Twitter and FourSquare, where they seem to be creating enormous value without any kind of traditional research. There are a lot of good ideas out there, and you can put together things in lots of ways. Google has concentrated on things that require a deeper level of expertise. But there are other applications where the algorithmic part is trivial, and the value added is being able to connect people to each other in just the right way. We couldn’t do that without the technology and the networks that we have now. But if you can find places

lon who were sponsored by government work; a guy from MIT, who has been sponsored by the government; and a couple of guys from Stanford, also government funded. All of them have government dollars piled up underneath them.

where you can capitalize on that infrastructure, great. What is Google’s relationship with academia like?

The take-aways

We really feel like we have to play nice with academics. We owe them a debt, and we want to continue to have interactions with them. We want to hire their students. We want to bring in their interns over the summer. We want to have visiting professors here. We want to fund their work and we want to participate in conferences. We have to go to conferences

The difference between “research” and “engineering”

and talk to them and read their papers. But we also have to publish papers, because if we were sitting in the back of the room saying nothing, they’d stop trusting us. So you’ve got to participate as a full citizen in that community.

at Google is often just a matter of what is written on your business card.

...we have to play nice with academics. We owe them a debt, and we want to continue to have interactions with them.

We want to hire their students.

Rich Friedrich Hewlett-Packard HP Is Still About More Than Just PCs and Printers

Friedrich is the director of the Strategy and Innovation Office at Hewlett-Packard, a company often described as an example of a venerable tech leader being forced by a changing world to cut back on its legendary commitment to research.

orange:

So why do you always hear “Too bad about HP,

So how many people at HP are doing basic research?

because they’re doing a lot less of the kind of research that made We have about 500 researchers, so if you take a third of that,

them famous.”

that would be around 150 or 170. It’s not always easy to

rich friedrich:

So three and a half years ago when

compute that number, because a person may spend two thirds

our Senior Vice President for Research, Dr. Prith Banerjee

of his or her time doing something that’s really fundamental,

joined, I would say that the total research investment of HP

but a third working on applying it. So you’re never 100%

was making only about 10 or 15 percent focused on basic,

dedicated to one particular category.

fundamental research. He’s upped that considerably, so that Has HP been able to resist short term financial pressures as

today we’re about one third basic research.

successfully as you’d like? Are there times when you think it should So the amount devoted to basic research has doubled, but it’s a bigger piece of a smaller pie?

have pushed back harder? That’s a question for the EVPs and the CEO. But I would say from my position as a director inside the organization I think

Right.

HP has done a reasonable job of resisting lure of the sirens of So give me some examples of basic research, the kinds of things

the quarterly Wall Street report.

that people are doing at HP. If you look at where we’re making a lot of fundamental investments today, one of the big areas is nanotechnology,

Give me some example of things from research that you were able to add that Dell wasn’t able to.

computing

So the couple things that really caught on fire were the Instant-

infrastructure. In fact our Memristor, which has the

On DVD and Instant-On CD players for the laptops. It used to

potential to revolutionize all of memory and all of storage,

be that you had to boot up Windows before you could run a

came about because of investments that Dave Packard

CD player or watch a movie. But we built instant technology

asked the company to make back in the mid 1990s.

by paring down Linux, hosting a mini DVD player and a CD

We also have a lot of photonics work. We’re looking

player. Another example is high end audio, which we’ve had

at how ions behave at the nano level. And we’re making

in the last couple years and which has made a big impact.

significant investments in fundamental research around

Lighter weight laptops, higher resolution screens - there’s

information analytics, which is all very deep mathematics and

been a series of things.

especially

applied

generation

science applied to how you extract out of data something that’s meaningful.

HP’s Vinay Deolalikar got a lot of attention recently for solution he offer for the P=NP problem. What do you say to a shareholder who asks, “What is this P=NP thing, and why are we paying this guy all

...our Memristor, which has the potential to revolutionize all

this money to solve something that’s not going to help the stock?” I’d paraphrase the response that Maxwell gave to Queen Victoria when she asked about Maxwell’s equations, and how

of memory and all of storage,

these could possibly be relevant to England. His response

came about because of

the potential of a baby?” To be a little more concrete, I would

investments that Dave Packard

then I think a shareholder would be right to wonder why we’re

asked the company to make back in the mid 1990s.

was something to the effect, “Your majesty, how do we judge say that if we were doing something related to astrophysics, doing it. But when you’re dealing with algorithms, you’re never quite sure how they’re going to influence what you do later on.

Let me give you a really concrete example. About a

decade ago one of our senior fellows, Bernardo Huberman, did a project which allows executives in a company to do a better job of predicting things such as revenues. They’ve shown that they can take what a decade ago were considered very abstract algorithms and turn them into something that’s very powerful for an enterprise. They’re using them now to predict things, based on analyzing the chatter that goes on Web 2.0 sites.

I think a shareholder would be right to wonder why we’re doing it. But when you’re dealing with algorithms, you’re never quite sure how they’re going to influence what you do later on.

“

I would say that if we were doing something related to astrophysics, then

You’ve described how government’s sponsorship of research was becoming more short term oriented. What is the implication of that? After the dot com phenomena, a lot of professors left universities, many in hopes of becoming billionaires. As the country kind of recovered from that event, there was a lot more pressure applied by groups like the National Science Foundation and the National Institutes for Health for universities to find a corporate sponsor for some of their research. It’s typically meant that timeframes had to be pulled in.

Fundamentally, the United States has become very short

term focused, even on our fundamental research, which means no one’s working on that computing architecture that’s going to be really important in the 2020 to 2030 timeframe. You effectively drain the current profit pool with no way to invest to get your company to the next one.

The take-aways

Fundamentally, the United States has become very short term focused,

HP’s total research budget may

even on our fundamental research,

have shrunk, but the company

which means no one’s working on

doesn’t want anyone thinking its

that computing architecture that’s

commitment to basic

going to be really important in the

research is undiminished.

2020 to 2030 timeframe. 45

Norman Winarsky SRI Is Your R&D Operation Really Your Friend?

Winarsky is a vice president at SRI, the research outfit often best-known for its pioneering work with the personal computer. Much of SRIâ&#x20AC;&#x2122;s work today involves performing research for other companies.

orange:

SRI does research for other people. But what’s wrong

That sounds frightening.

with a company doing research itself, the way Bell Labs did?

norman winarsky: You’re asking, “Why can’t a company

Research institutions generally like doing research that is

have an R&D institution that feeds its research into the

three to five years away from product or service. That’s what

company for products and services, but can simultaneously

a researcher loves to do. But companies want delivery into

be open to outside opportunities for software, hardware, and

the marketplace within the time frame that’s going to affect

the like?” The reason is that I’ve never seen an example of

their stock price and their revenue. That means 12-18 months.

that. It’s natural for an R&D organization to consider outside

So researchers want to stay three or more years out, but

R&D to be competitive with their own approach. It takes new

companies want to stay no more than 18 months out. Between

and innovative management to change the structure, so that

those is the Valley of Death. Companies need to make sure

open innovation can be possible.

that they’re either investing for the crossing of that valley, or that someone else is. This becomes an issue of the board of

...It’s natural for an R&D organization to consider outside R&D to be competitive with their own approach. It takes new and innovative management to change the structure, so that open

directors of that company. You know, they have to oversee the long-term success of the company.

Research institutions generally like doing research that is three to five years away from product or service. That’s what a researcher loves to do.

innovation can be possible.

Funding for basic research definitely seems to be in decline, but That implies that, to the extent companies might be spending less on

do you think it’s been empirically proven to be not profitable? Do

research, that’s not necessarily a bad thing.

you know for a fact that Bell Labs wasn’t, for example, specifically profitable for AT&T?

Research equates in my mind to invention. So if you agree that invention can come from anywhere, and that you’re open to that, then I think spending money on invention is good, to the extent that you have a goal. But one needs to have a goal of innovation, not research: You have to start with a market problem in mind. Companies generally have a problem with what we call at SRI the Innovation Valley of Death.

no one would like to see the results, nor would they share them. But I’ve talked to executives of major companies, hundreds by now, and in a private room after having had a scotch, they’d admit that the cost of R&D is greater than the profits of it.

...But I’ve talked to executives of major companies, hundreds by

now, and in a private room after having had a scotch, they’d admit that the cost of R&D is greater than the profits of it.

“

I haven’t read a study that states that, and probably because

They’ve understood there is a new type of business proposition, which is equally valuable, or even more valuable, than technology.

“

What Zynga, Facebook, Groupon and the others have done is spectacular.

Many people are struck by the number of new tech companies today that seem to be enormously valuable, but which seem to not be based on any sort of research. What we’re discovering is that a company’s value proposition, or its sustainable competitive differentiation, which we at SRI call the “Golden Nugget,” does not have to be technology by any stretch of the imagination. What Zynga, Facebook, Groupon and the others have done is spectacular. They’ve understood there is a new type of business proposition, which is equally valuable, or even more valuable, than technology. The business proposition is an untapped market opportunity that comes from having an audience connected with technology. We’ve invented some power tools, namely the Internet and broadband connections and iPads and mobile phones, and at that point, technology is no longer the limiting problem. So is there any research left to do? What about the patent officer that said that you should close the patent office? This has never been a better time for innovation in IT. At SRI, we have three major themes. One

The take-aways

theme which started with Siri (later bought by Apple) is for the virtual personal assistant. We absolutely believe that being able to personalize and contextualize a person’s interaction is deep technology. Another example of what SRI’s working on is augmented reality. Twenty years ago, SRI created the company that did what you see on the walls of football games, all those ads and so forth and on the field. Augmented reality is

You won’t hear any lamenting

now entering a new generation of helping other experiences,

about the good old days of Bell

security and privacy.

such as games and shopping. The third big theme is cyber-

Labs from SRI. If you run the

R&D lab inside a company, you’ll

which is what we call innovation, than right now.

probably consider them competition. Which in fact is their whole point. 48

Those are just three examples. There hasn’t ever been a

better time for research that will deliver into the marketplace,

There hasn’t ever been a better time for research that will deliver into the marketplace, which is what we call innovation, than right now.

Georges Nahon

Mark Plakias

Orange SIlicon Valley Project Team

Natalie Quizon

Pascale Diaine

Minesh Govenji

Lee Gomes’ acknowledgements: I’d first like to thank Georges Nahon of the Orange Institute, whose support and ideas were central to this project. In addition to the people profiled in this report, I’d also like to thank the following, who made significant contributions of one kind or another. It should not be assumed that anyone who helped with the project is in agreement with its conclusions.

Mark Boroush, National Science Foundation Jules Duga, Battelle Hossein Eslambolchi, 2020 Venture Partners Jason Freidenfelds, Google Virginia Gold, ACM Richard R. John, Columbia University Bronwyn Hall, UC Berkeley Robin Hanson, George Mason University Lillian Hoddeson, University of Illinois David A. Hounshell, Carnegie Mellon University Barry Jaruzelski, Booz & Co. Ed Lazowska, University of Washington Leslie Lamport, Microsoft Baruch Lev, NYU Andrew Odlyzko, University of Minnesota Richard H. Van Atta, Georgetown University Chrissy Vaughn, Waggener Edstrom Lee Gomes, who lives in San Francisco, has written about research, technology and Silicon Valley companies for two decades, much of that time at the Wall Street Journal.

References and images in this publication Page 4, Microscope Stage 3, by Larry Darling, available under Creative Commons at http://www.flickr.com/photos/tncountryfan/5543913413 Page 9, Gas Mask, Broad Arrow, Zero, available under Creative Commons at www.flickr.com/photos/noodlefish/3871148611/in/set72157622187321634/ Page 11, 1 Foray, Dominique, Hall, Bronwyn H. and Mairesse, Jacques, Pitfalls in Estimating the Returns to Corporate R&D Using Accounting Data (September 1, 2007). CDM Working Papers Series CEMI-WORKING PAPER-2007-003. Available at SSRN: http://ssrn.com/abstract=1427754 Page 11, Illustration: Experimental modes of transistors, 1953. From Bell Laboratories, Arthur Gregor, 1972. Page 18 and 19:Peter Lee, http://www.flickr.com/photos/msr_redmond/5515738115/ Page 18 and 22: Joel West, http://www.kgi.edu/Images/Faculty/west_joel.jpg Page 18 and 25: Cameron Marlow, http://www.flickr.com/photos/cameronfactor/3624252776/in/photosof-cameronfactor/ Page 18 and 28: Mendel Rosenblum, http://www.ece.utoronto.ca/aboutus/dls1/Rosenblum.htm Page 18 and 31: David Patterson. http://www.eecs.berkeley.edu/department/EECSbrochure/c6-s5.html Page 18 and 34: Judy Estrin, http://www.ischool.berkeley.edu/newsandevents/events/dls20090415 Page 18 and 37: Robert Ackerman, http://www.allegiscapital.com/team-ackerman.html Page 18 and 40: Peter Norvig, http://pn.smugmug.com/gallery/1677561#27898845_VZvrj Page 18 and 43: Rich Friedrich, http://senseable.mit.edu/futurecities/speakers.html Page 18 and 46: Norman Winarsky, http://www.triplehelixconference.org/keynote-speakers/norman-d-winarsky.html

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