Alors que de plus en plus de grandes entreprises implantent leur centre de recherche ou de développement dans la Silicon Valley, une récente étude réalisée par Orange soulève des interrogations quant aux orientations actuelles suivies par la recherche technologique internet dans cette région. Ce rapport révèle en effet de nouvelles évolutions dans les comportements, les méthodes de travail et les motivations individuelles dues à la croissance d’internet, à l’apparition de nouveaux acteurs du web et à l‘invention de nouveaux produits. Ces nouvelles tendances ont un réel impact sur la recherche en technologies de l’information et d’internet et ses mutations. Cette étude s’appuie sur de nombreux entretiens approfondis menés au cours des derniers mois par Lee Gomes, journaliste spécialisé dans la Silicon Valley, pour Orange, avec des représentants de leaders industriels et d’universités comme Google, Facebook, Microsoft, UC Berkeley, Stanford… Orange met aujourd’hui les conclusions de cette enquête à disposition du public dans le but d’instaurer un dialogue ouvert sur l’évolution de l’écosystème. Source : Orange Press : http://www.orange.com/fr_FR/presse/communiques/cp111007fr2.jsp

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

3. 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 com-
mercial research – 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 Sili-
con 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 inter-
views 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 innova-
tion 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 concentra-
tion of Talent in Silicon Valley is unique in the world – 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. Let’s add to that: when it wants to accomplish it.
- Georges Nahon
CEO
-Mark Plakias
VP
Orange Silicon Valley
3

5. This is happening everywhere, including the deepest
recesses of corporate R&D, where cycles of investment
and divestment are getting shorter. The deterioration
of corporate trust for research is probably based on
management impatience with too-long research cycles,
What’s left to know? 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 as eBay, Amazon, Google, Zynga, Facebook, Yahoo, etc.
of the topics cited in these discussions with researchers in 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.
5

6. 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 time-scale equal for all players. More 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
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
be that this new model is going to forever complement (and
The tacit rules of mutual control better) other more traditional forms of R&D that may survive
-- “do not come into my territory in the fields of IT, communications, and online media and
commerce. At Orange Silicon Valley our conviction is that
and I will not get into yours” -- we cannot understand alone what’s inside a moving train
are over because of all things by watching it from the platform. We need to be in the train
going to digital. ourselves along with others to address the question, “What’s
new to know now?”
6

8. 8
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.
M
ost have heard the story of the woeful ubiquitous mobile devices - is now in place, the way the basics
idiot who happened to be U.S. director of of the automobile were in place once the modern internal
patents in 1899, and who urged that his combustion engine was realized? What if developments in IT
office be closed because there was nothing and data from this point on are all incremental?
remaining to invent. This, of course, does not imply that there won’t be
In fact, that tale is an urban legend with no basis in fact; any major technology improvements, or shifts in corporate
Charles H. Duell, who held the post at the time, far from being fortunes, in coming years and decades. After all, both cars
pessimistic about future discoveries, was actually a booster and car companies look drastically different today than
when it came to what Yankee ingenuity would make possible, they did 50 or even 25 years ago, despite having the same
akin to “You ain’t seen nothing yet.” (Quotes suggesting the technological foundation. But the changes were essential,
opposite have been proven by scholars to be fabrications). gradual and incremental, rather than being earth-shaking and
But the fact that someone, somewhere, even bothered to revolutionary, as they were in Henry Ford’s time.
create the historical falsification in the first place can be taken To understand why we are even raising the question
as a warning of the dangers involved when a given generation of the future of data and IT, let’s first consider the classic
becomes so engrossed in its own repertoire of massive view of the subject - with a bow to particle physics, we can
inventions that it devalues longer-term perspectives. almost call it the “Standard Model” of Silicon Valley. In this
But - and to use another problematic formulation - what telling of history, most IT research was done at one of two
if this time, it’s different? What if this time, they’re right, that locales: inside academia, under the sponsorship of the U.S.
the moment we’re in dwarfs everything up until now by government, and at select groups of large companies with
comparison, and requires our full attention and ingenuity? dominant market positions and the healthy profit margins
To be clear, we are not talking here about the totality of that accompany them. The research-to-product transition
science and technology, but instead, a subsection of it, in followed a traditional path, beginning in a lab somewhere and
the enormously important world of IT, especially as it involves then making its way to the marketplace, perhaps pausing
data and data sciences. along the way to accumulate some venture capital funding.
What if the fundamental data-intensive infrastructure How little that looks like today’s world. For one, federal
of computers - Moore’s Law, new data base tools and funding for research has diminished or been reallocated.

9. Second, the great standalone corporate the innovation of these new giants is
research labs of the post-war era, ecosystem-specific: Google and others
with AT&T’s Bell Labs (now Alcatel- share, via open source, the tools used
Lucent Bell Labs) being the preeminent for managing and learning from Big
example, have been repurposed, if Data, and actively encourage these
they even exist at all. Perhaps most open source resources adoption by
significantly, technologies that not too individuals and entrepreneurs.
many decades ago were but fledgling But the new reality is that the best,
research ideas have today become and most massive, data is in private
robust, even commodity, product hands. Far from being content, almost
categories - notably highly integrated passive, “end-users” of academic
semiconductors, high-capacity storage research, as they might have been
devices, extremely sophisticated in the past, the big Silicon Valley
software and robust ubiquitous companies of today are arguably
networks capable of high-capacity doing most of the heavy lifting in IT
digital communications. research in the first place. In effect, is
The result is on display everywhere it perhaps the case that the task has
in Silicon Valley. Dense chips, cheap fallen to the Google’s of the world,
storage and ubiquitous networking have rather than any traditional “research”
created the world of “Big Data,” in which operations, of providing whatever
hundreds of millions of computers and incremental improvements remain to
mobile devices are creating staggering be made in the art and science of data?
amounts of information. In this document you will hear from
Rather than the clock-like migration thoughtful practitioners on both sides
of technologies from research labs to of this question.
companies, what we see instead is By contrast, academic computer
the steady ascent of what might be science departments find themselves
called the “research giants” - the best doing a severely resource-constrained
example, of course, is Google. These imitation of the commercial efforts
companies, arguably, are the only underway at the big Silicon Valley
institutions with the resources, both companies. To ameliorate this,
capital and human, to handle data at collaboration is necessary, and indeed
the levels it is being created. It follows happening: companies such as
that they have privileged access to the Google, SAP, Amazon, and Huawei
massive data sets that enable the type are supporting long-term university
of analytics and research about human research efforts such as University of
behavior that is creating the wealth of California Berkeley’s AMP Lab. Still, the
the 21st Century. To be sure, part of big picture seems weighted towards
“ 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.
9 9

10. immediate engagement in a commercial In one sense, there is nothing particularly
context: these companies are so wealthy that shocking about suggesting that parts of
they regularly poach some of academia’s most the IT industry have become so mature that
talented faculty members and students, further changes from here out will be incremental. It
depleting academic research efforts. If you has happened consistently over the last two
are interested in exploring some aspect of the centuries, in everything from steam power
“social graph,” where would you rather be: at to electricity to radiography to telephones
even the best-funded academic department, and televisions. All went from being a newly-
or at Facebook, where you would have discovered phenomenon of nature, the domain
access to a 25-petabyte Hadoop cluster? And of researchers and scientists, to being the basis
from which do you think the most interesting of large commercial enterprises, the domain of
insights will spring into how people use business people - with the occasional assist
“social media?” from engineers.
Put in its most stark fashion, as far as data- Even in science itself, research can reach
related IT goes, does traditional research even a mature phase. Isaac Newton did a fairly
matter any more? That question is at the core complete job of describing the movement of
subject of this report. everyday objects in the everyday lives of human
This idea for this project began when a beings, from apples to planets. Early in the 20th
small group of us, sitting together at a table, Century, we discovered that Newton’s Laws
made a simple assumption: Everything else didn’t hold for the very small or the very fast.
about the world has changed on account of the But quantum mechanics and relativity don’t
Internet; why should the practice of research repudiate Newton, but instead modified him
for new domains but leaving unchanged
If you are interested in exploring some aspect the many technologies built on Newtonian
of the “social graph,” where would you rather principles.
We hope readers appreciate that when
be: at even the best-funded academic depart- we ask “Does IT research still matter?” we
ment, or at Facebook, where you would have are asking it not because we view the issue
as settled, but instead, in an attempt to
access to a 25-petabyte Hadoop cluster? provoke thoughtful discussion.
Some readers might be shocked that
be any exception? We interviewed researchers, anyone would question the value of research. (In
research managers, entrepreneurs and other this report, “research” means basic, unstructured
deep thinkers who spend their careers in research, with no obvious short-or mid-term
Silicon Valley. The questions were all designed connection with a company’s existing product
as variations on the same theme: How should lines). But in actuality, there has always been a
technology companies, in an age of ubiquitous surprising lack of consensus about the economic
mobile computing, “big data,” shifting business value of research, at least when it is performed
plans, shortened investment horizons, be by an individual company. (Few doubt that
thinking about “research?” The bulk of this federal dollars on even the most basic, untested
report is devoted to those interviews. forms of research are well spent). Indeed, one
10

11. 11
Experimental modes of transistors, 1953
writer said that as far as companies many academic economists, who
are concerned, research might best be caution against attempting to draw
defined as a “faith-based initiative.” any conclusions at all from publicly-
Consider the contradictory reported accounting data, since the law
conclusions reached on the matter by allows companies considerable latitude
two different groups of professionals: in what they report as “research.” One
business school professors and paper by a trio of economists, with more
business consultants on one hand, and stridency than is usually associated
academic economists on the other. with academic writing, called the report
Representative of the former category “extremely misleading,” saying that in
is a series of annual reports by Booz ignoring decades of prior literature, it
& Co. that began in 2005 and have “mixes incorrect conclusions obtained
continued since. Analysts at the firm from an uninformed and simplistic
say they have been able to find no analysis with some common sense
Bell Labs is an correlation between R&D spending with advice” analogous, to telling people,
excellent case study just about anything most companies “It is better to be rich and healthy than
care about, such as sales growth, poor and sick.”1
in the difficulties of profits and market cap. (Though the There are certain questions about
knowing what sort report noted that the bottom 10% of research that one doesn’t need to be
R&D spenders tended to underperform a trained economist to raise. For one,
of value to assign to in other areas as well). there is plenty of anecdotal evidence to
in-house research. The report did not sit well with suggest that large research operations

12. 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 to human knowledge during its heyday in the
anticipating and responding to new business years before the break-up of AT&T, probably
challenges. Sometimes, this is hardly the fault more so than any single institution on the planet.
of researchers, as in the “innovator’s dilemma” (Transistors, evidence of the Big Bang, Unix and
situations where management simply can’t C; the laser; quantum computing breakthroughs:
bring itself to undergo what might well be the the list goes on and on). But how about AT&T
wrenching business model changes necessary shareholders; from their admittedly provincial
to adjust to shifting technologies. point of view, did they get their money’s worth?
But what do we make of Microsoft’s seeming Answering that question is probably impossible,
lack of ability to anticipate or out-maneuver as it involves unraveling a tangle of hypotheticals
Google, or Google’s current difficulties in keeping and counterfactuals, and nearly everyone we
up with Facebook?” The “research skeptic” asked had a different answer. Most, in fact,
would also note the enormous values attached expressed agnosticism.
to companies that seemed to be based on no The debate about the value of corporate
research at all, but instead on a entrepreneurial research strongly resembles the debate
insight that was perfectly executed. Facebook, among economics about the value of “free
Twitter and Groupon all come to mind. trade.” Is the “engine” of prosperity, or merely
Bell Labs is an excellent case study in the it “handmaiden?” Put differently, does free trade
difficulties of knowing what sort of value to cause fundamental economic growth in the first
assign to in-house research. There is, of course, place, or does it simply accompany it after the
no doubt that the Labs contributed enormously fact, like an attendant in a bridal party? The best
12

13. “ Does research make companies rich,
or can companies do research only if
they are rich in the first place?
“
evidence for the latter hypothesis is that characterizations of their research
nearly all countries, the U.S. included, efforts depending on the audience.
take a protectionist approach to their With Wall Street, they might emphasize
nascent industries. Rephrased to deal its leanness and its tight connection
with the research issue, the question with product groups and quick
becomes, “Does research make commercialization. With prospective
companies rich, or can companies employees in graduate schools, they
do research only if they are rich in are likely to give the impression that
the first place?” new hires are able to pursue their
Now that we have advanced our field’s deepest problems - without
critique of the “Standard Model” of being distracted by any noise from the
research, and suggested why much of grinding wheels of commerce.
Silicon Valley is perhaps unknowingly in An additional issue is that many
a “post-research” phase in its history, people in Silicon Valley are unaware
we are obliged to challenge what we of the area’s actual history, especially
ourselves have been arguing. as it involves the relationship between
First, we are required to point out basic research and corporate
is that when trying to figure out a given success. Most people acknowledge
company’s approach to research, the obvious well-known facts, like the role
least reliable source of information that DARPA played in the creation
is often the company itself. For one, of the Internet.
accounting rules about research are But the pervasiveness of federal
so ill-defined that no two companies involvement in creation of the IT industry
are reporting the same activities when is often underappreciated. At nearly
they report on their “research” budgets. every step of the way, federal funding
(Note that the authoritative reports was involved with major Silicon Valley
by the National Science Foundation developments. In the 1960s, the first
about corporate and government customers of semiconductor products
R&D spending do not rely on public were the military, who displayed ample
accounting data, but instead on patience as chip companies worked
confidential, anonymized information out the bugs in their earliest efforts at
shared with government by industry). fabbing chips. It was just as true in the
Companies will also adjust their 1990s at the creation of Google, since
13

14. “ it may be problematic to assume that Silicon
Valley operated one way in the last era and an
entirely different way today.
“
Larry Page and Sergey Brin did their of Google think the company emerged
work on the “Page Rank” algorithm fully-formed from the heads of its two
while being funded from a grant from founders, the company itself is the first
the NSF. to acknowledge the extent to which its
Another problem is that own considerable engineering efforts
“breakthroughs” are almost never as relied on earlier work by others).
simple as they seem, and rarely occur The point of all this is that it may be
in isolation. At the same time Brin and problematic to assume that Silicon
Page were doing their work, two other Valley operated one way in the last
research groups had essentially the era and an entirely different way today.
same insight involving how a page’s Descriptions of each era are highly
link structure could be mined for crucial anecdotal; for every example of one
information about the page’s reliability. pattern for the path that research might
Later, as Google engineers were take going from lab benches to store
scrambling to adjust to their company’s shelves, it’s possible to come up with a
astonishing growth, their seeming competing narrative.
improvisations occurred inside a Consider storage. Much of the
considerable ecosystem of existing pioneering work on the modern
ideas. One of many examples is the magnetic disk drive was done at IBM
Paxos Algorithm, developed in 1990 by during the 1950s, and companies
Leslie Lamport, then a DEC researcher, have been responsible for the most of
which provides a way of dealing the subsequent research responsible Another critique of our data-
with results provided by potential for the continuing increases in areal oriented hypothesis is that it might
unreliable computers, a clear problem density - the storage equivalent of unknowingly be a symptom of what
in a massively parallel data system Moore’s Law. (The cost of storing a has been described as the tech
like the one Google’s engineers were unit of information on a disk drive is world’s current data fetishism. In many
building. (Incidentally, while many fans now 122 million times cheaper than it areas, such as language translation
was in the 1950s). But dramatic disk and speech recognition, the massive
drive innovations have also occurred amounts of data available today are
in academia, such as the breakthrough allowing companies to fully implement
notion of RAID storage, developed at the statistical “machine learning”
UC Berkeley in the 1980s as a way techniques developed in the 1980s,
to get highly fault-tolerant storage following the failure of traditional “rule-
even while using low-cost, commodity based” AI. Google Translate is the
disk drives. preeminent example here; while far
14

15. &
field (much of which will no doubt occur observation that academic computer
in the academy). Further, it’s possible science has been “overtaken” by data
that we will discover that as long as science that can be done better by the
human beings are involved, past results big tech companies; that academic
are no indicator of future performance, computer science departments seem
no matter how much data one has. to be lagging, not leading, in innovative
All of which are reasons that many ideas. One explanation of this apparent
people view with alarm any attempt to phenomenon involves our hypothesis
minimize the importance of research. that all the basic work has already
Companies, this school of thought been done, which is why academic
holds, have a natural tendency to be research seems to so closely resemble
“free-riders;” to not want to pay for things commercial research. But another
that don’t obviously and immediately interpretation is that universities are
benefit them. Basic research, which faced with a decline in federal research
even its most traditional supporters dollars, and so to attract corporate
say is unpredictable in its distribution sponsors, they must essentially pander
of benefits, is precisely the sort of to what they assume to be the current
thing that companies in the current preoccupation of potential funders.
investor climate are likely to avoid. We must also be careful about
Those concerned about the overall assuming that the yawning gap
state of research today worry that at that now exists between a Google
from perfect, its ability to allow a basic the very moment that market pressures and virtually any other company or
understanding of almost any text in any are forcing firms to pull back on R&D, academic department will remain
language is astonishing. the government is under economic forever. In fact, several forces are at
But the current enthusiasm for data pressure of its own, and is not able to work to narrow it. Improvements in disk
goes beyond implementing machine play its familiar role and take up the storage continue apace; a petabyte 3.5
learning algorithms. Especially in slack. Thus, the basic view is that by inch drive should cost $250 or so within
e-commerce, it is assumed that the vast ignoring research, we won’t be creating the decade. In addition, there are many
amounts of data we leave behind via the ecosystem that will allow the next efforts underway to turn the building
our mobile phones and computers have Google to be formed. and running of a giant data center into
some secret key to our future behavior. In a similar vein, these people a commodity undertaking, no more
The middling success that companies would have a different interpretation difficult than setting up a corporate
like Amazon and Netflix have with their of current events than those offered LAN. These efforts are occurring in
recommendation systems suggest that by critics of the Standard Model. For academia as well as in a new breed
much work remains to be done in this example, it’s common now to hear the 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

16. for example, to providing versions of undertaking, where the investment
Hadoop and its related tools that an calculus is entirely different - VCs say
average IT shop can use. that their ideal remains research whose
It need be noted that even we, in our commercial appeal is demonstratively
deliberately provocative role questioning obvious. Or, as a spokesman for
assumptions about research, would Sequoia Capital, currently one of the
have to agree that there are potentially most successful of the fabled venture
revolutionary breakthroughs on the firms along Palo Alto’s Sand Hill Road,
horizon. An obvious one involves “In our little corner of the world, we get
quantum computing. Computer involved in the “D” part of R&D. We leave
scientists disagree about the repertoire it to the very creative and very capable
of problems that a quantum computer talents at universities, government labs
could effectively take on. But in the and corporate centers to dream up a
very least, they will force us to rethink world of new possibilities.”
the encryption systems currently In closing, there is no doubt that the
responsible for all Web commerce. massive scalability of Internet-based
Another potential breakthrough businesses has changed the way we
involves a fundamental algorithmic think about research. The urgency
advance in learning how to parallelize created by these scale effects is based
computing problems. Microprocessor on the sheer amount of data available:
companies have long since given which poses not just monetization but
up on making a single chip that runs research opportunities that are here
ever-faster; chips today ship with four and now.
or eight (or even 64) “cores,” each of The world has changed, and in
equal power. But just as it takes nine the following section we summarize
months to make a baby, most software the contrasts in that journey from then
problems need to be solved in order, to now.
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 We must also be careful about
change, some things endure. One is
the role played by venture capitalists.
assuming that the yawning gap
VCs have never seen themselves in that now exists between a Google
the business of funding basic research,
and certainly don’t these days. Outside
and virtually any other company or
of biotechnology - an entirely different 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.
16

17. 1940 1960 1980 1985 1990 1995 2000 2005 2010
Organizations A - 1925 B - 1945 C - 1970 D - 1985 E - 1999 F - 2005 G - 2007
Western Electric IBM Research (The SRI International Famous Silicon Valley Apache Software Veteran entrepreneur Google, Motorola,
Laboratories and an Watson Scientific founded as a separate networking organization Foundation is formed Paul Graham co-founds HTC and others form
engineering department Computing Laboratory research institute from Chruchill Club holds to support Apache Y-Conmbinator, which Open Mobile Alliance
of the American was founded at its parent, Stanford first meeting, with web server software. becomes the one of the to promote Android
Telephone & Telegraph Columbia University in University. PARC keynote by Robert most powerful startup ecosytem.
company consolidated New York) founded as research Noyce, inventor of the incubators of modern
to form Bell Telephone arm of Xerox Corp. integrated circuit. times.
Laboratories, Inc.
Hardware A - 1947 B - 1965 C - 1971 D - 1980 E - 1984 F - 2008 G - 2010
John Bardeen and Gordon Moore Leon Chua publishes a Sony and Philips Bell Labs introduces the HP announces HP announces
Walter Brattain, Bell publishes article in paper describing basic collaborate to first megabit memory development of a development of a
Labs invents transistor Electronics claiming principles of a Memristor standardize Compact chip. Memristor based on Memristor based on
density of components Disc audio format. titanium dioxide film. titanium dioxide film.
on an integrated circuits
A doubles annually.
G
B C D
F
A B C D E
F
A B C D E F G
G
B C
E H
A I
The Researcher’s Journey:
D E F G H
Milestones in Technology R&D
Software A -1969 B - 1975 C - 1988 D - 1990 E - 1991 F - 1998 G - 2004 H - 2008 I - 2011
UNIX operating system Digital Equipment Corp Insignia Solutions Leslie Lamport at DEC LINUX operating system VMWare is founded and Google introduces a Yahoo! announces it Work begins on UnQL,
developed at AT&T’s Bell initiates development of introduces SoftPC develops the Paxos devceloped by Linus patents its hypervisor software framework for has launched the largest Unstructured Query
Labs, offering multi-user, a new operating system, Windows emulator algorithm, later used by Torvald, built on open virtualization tools. managing large data instance of Hadoop Language, result of
multi-tasking features. code-named Starlet, for Sun workstations, Google. software licensing By sets across distributed data managemnent NoSQL movement.
Today’s Mac OS X is a which will become the ushering in desktop June of 2010, LINUX computer centers called software running in a
descendent. widely-used multi-user virtualization. was the OS for the 10 Map Reduce. cluster of 10,000 Linux
operating system known fastest supercomputers processor cores.
as VMS. on the planet.
Services A - 1985 B - 1991 C - 1993 D - 1999 E - 2002 F - 2004 G - 2007 H - 2008
Stewart Brand and Larry The world’s first website First SMS from Salesforce.com the W3C releases first Mark Zuckerberg Y-Combinator cloud Apple’s AppStore opens
Brilliant start a dial-up is created at CERN, phone-to-phone sent in world’s first software- public draft of its Web launches facebok.com storage startup Dropbox in July as an update to
BBS called The Well, the employer of Tim Finland. as-a-service (SaaS) Services Architecture website. is founded, five years iTunes, iPhone 3G ships
which becomes the first Berners-Lee, credited company founded by which shows larter ios being valued at the next day with it
online virtual community with marrying hypertext ex-Oracle execs. interoperable software $5 billion. preloaded.
and one of the first to IP protocols. systems communicating
commercial dial-up and described via XML.
ISPs.

18. 18
Voices from Silicon Valley
Peter Lee 19 34 Judy Estrin
Microsoft Entrepreneur
How a traditionally-organized It’s very hard for companies
research division keeps up to think long-term enough
with new trends in research. to invest in research. But
they need to anyway.
Joel West 22 37 Robert Ackerman
Keck Graduate Institute Allegis Capital
“Open Innovation” is an If you’re a company thinking
exciting new way to think you can invest your way
about research, assuming into some cheap Silicon
it’s not just a fancy way of Valley research, prepare to
cutting the R&D budget. have your pockets picked.
Cameron Marlow 25 40 Peter Norvig
Facebook Google
You thought it was just There are lots of smart
a bunch of dorm room people at Google, but they
hackers, but more and don’t do much “blue sky”
more scientists are hanging open-ended research.
out shingles at Facebook. Except when they do.
Mendel Rosenblum 28 43 Rich Friedrich
Stanford, VMware HP
The path from basic It may not be like the old
research to a big company days when Bill and Dave
is circuitous, which is why it were still around, but basic
is so seldom-traveled. research continues at the
company they founded.
David Patterson 31 46 Norman Winarsky
UC Berkeley SRI International
The great American Internal R&D is over-rated,
research system has and often capable of doing
produced many successes, more harm than good.
and we tamper with it at
our peril.

19. 19
Peter
Lee
Microsoft
A Proud R&D Traditionalist
As new managing director of Microsoft
Research Redmond, Lee heads up
one of the computer industry’s few
remaining research operations
patterned after the labs of an earlier
era - autonomous and setting its own
lab direction.

20. orange: People often compare Microsoft Research to the Bell How is it organized?
Labs of old. What do you think of that comparison?
Research areas are like departments in that they have twenty-
five to fifty researchers and research engineers. And the
peter lee: There are some valid comparisons. We are an
research areas are organized around a broad, major direction
independent organization, so the business groups don’t tell
in computing. For example, machine learning, visualization
us what to do. Culturally, our researchers are motivated differ-
and user experience, and large scale data and analytics.
ently, maybe in ways that weren’t as true at Bell Labs. They’re
highly motivated to get their research ideas onto every desk- What do you think of some of the newer ideas that people are talking
top and into every data center in the world. Even in the short about - things like prizes or crowd sourcing or open innovation, etc?
time I’ve been here, I’ve been astounded at the ambition level
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.
“ Each department or each division is expected to show impact;
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.
20

21. “ The things that Microsoft Research does for Microsoft, couldn’t be
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 Why do you think basic research has the reputation that you can’t
of our partnership with the Bing group. A huge number of the measure its ROI? What is it that the people are not seeing, or are
forgetting, when they have that perspective on basic research?
underlying algorithms that power Microsoft Office. All the
machine translation products. All the cloud services - Azure,
There’s probably a cyclical nature to this. Within the company
SQL server, Hotmail - have their origins in Microsoft Research.
right now, the perspective on Microsoft Research and the
And we provide services for predictive analytics of software
value of Microsoft Research are possibly at an all-time high.
defects in a huge range of software development projects. It’s
And so it’s a very good time. But I’m a realist also. I understand
hard to imagine crowd-sourcing those sorts of things.
that these things come in cycles.
Having said that, crowd-sourcing and mass globalization
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 Even when you’re at a
about. Of course, we want the company to be very successful
and be more successful every day, but objectively I don’t think
company with a long-term
there’s an issue about our security here. Except that, and this
commitment to research,
is something I also learned at DARPA, people doing basic
research everywhere in this country have certain anxieties it’s nice to have the occasional
about society’s understanding and tolerance about basic
research. And so our researchers here aren’t immune to that. hit on your hands to keep the
top bosses happy.
21

22. 22
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.

23. 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
That has certainly contributed to the interest in Open
particularly hot area, in the way that the “Resource-Based
Innovation. When I go and talk to people out there, a lot of
View of the firm” was hot 20 years ago. If you look up “Open
the interest is from companies who either A) want to get rid of
Innovation” on Google Scholar, you see that there are
their R&D people or B) just gutted their R&D department and
thousands of papers. It’s come from nothing in 2003 to where
want to know what they should do next.
it is today.
Do you think the phrase is being overused?
What is new about the idea? Or is it just a useful name for something
people were already doing?
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 In many cases, when they appoint a VP for Open
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.”
Like sponsoring research at universities?
A related issue is the recognition by a company that
not all the smart people in the world work for them. That
They could have a universities relations arm. They could have
recognition, I think, is new.
ecosystem management or technology sourcing or technology
Once upon a time, you could have said that the smartest
IP procurement. They could have, on the other side, a patent
people in computing worked at IBM.
licensing office. Normally, the Open Innovation Officer, VP or
But then came the fragmentation of the computer
Senior VP or whatever, the Director of Open Innovations, is the
industry with the PC revolution. You saw manufacturing
person bringing innovations into the firm. They usually don’t
and product development going offshore and the Internet’s
give that title to somebody who’s trying to find markets for
dissemination of information, and open source software.
existing technology.
And all of a sudden, people realized that the idea that any
company - even the greatest company in the world - could
have a monopoly or a preponderance of knowledge in an
area just isn’t plausible.
23

24. “ 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
of its own parts, but it also sources things outside where it doesn’t
“
have the scale or the technology.
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
in-house and we always use our in-house janitor, our in-
The take-aways house 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.
Really, what Open Innovation is saying is that firms ought
Like many things in to be aware of what the best technology is for anything relevant
to their line of business. They shouldn’t automatically assume
business, Open Innovation is that they do it in-house, nor should they automatically assume
that they do it outside. Instead, they do need to monitor the
part-real, part-hype. The real
state of the art of what’s going on outside the company, to be
opportunity from Open Innova- able to say when necessary, “Look, this part of our technology
is just not state-of-the-art.”
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.
24

25. 25
Cameron
Marlow
Facebook
A Hot Start-up Begins Its R&D Rite of Passage
The only “research problem” 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, you’ve
got to start planning for it.

26. orange: So why exactly does Facebook need researchers? How do you distinguish research from engineering? Couldn’t
Don’t you guys just sit around and keep growing? 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 The types of questions we’re answering are as fundamental
research. We’ve hired a number of people and published a 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 The social interactions on the
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 Internet, and on Facebook in
research at Facebook is one where we work as closely with
the product as possible, because the problems we face are
particular, are at a level of detail
some of the most interesting problems that exist.
and scale that haven’t existed
How often are people surprised when they hear about Facebook before. They allow us to answer
doing research-research as opposed to engineering?
questions about social interaction
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 and social forces that we’ve never
with are doing research.
been able to answer...
We all come from like a very
The social interactions on the Internet, and on Facebook
Internet-friendly research in particular, are at a level of detail and scale that haven’t
existed before. They allow us to answer questions about
background, and it’s kind of social interaction and social forces that we’ve never been able
to answer, even though some of these questions are as old
expected that if we came to
as the discipline of sociology. Of course, the fact that these
Facebook, we’d be doing some questions exist doesn’t mean we’re going to answer all of
them; there isn’t perfect alignment in everything we do. But in
kind of research. the day of a typical engineer, we need to answer questions like,
“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.
I could go on for an hour. We have a lot of interesting work
Your real work is working on problems. So there is a bit of
that’s being done with taking our code base and compiling it
a different incentive here. People really want to make users
into C. The compiler community is very interested in HipHop
more happy. I think it attracts a different type of researcher.
(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.
26

27. 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.
“ Here at Facebook, the code base is available to
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 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 take-aways
The model I used to think about the standard corporate
research labs is that the company was like a planet, with the
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 Successful young compa-
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
AT&T Labs or a Xerox Park
fundamentally changed the way
“
researchers can get an idea
into the hands of millions
of users in not much longer
that the core company operated. than it takes to test the code.
27

28. 28
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 Valley’s
rare entrepreneurs who was able to grow
some basic research into an enormously
important company.

29. 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?
So why the PC?
The idea of virtual machine monitors was actually invented
The nice thing about trying to do it for the PC was it was pretty
by IBM in the late 1950s and early 1960s. But as PCs became
clear we didn’t depend on anybody. The PC was opening up,
more common, it pretty much died as a research idea. I’m
and we knew what the hardware did, so it made it more of a
an experimental system builder, and so I propose systems,
tractable problem to do it as an outside company.
and when I demonstrate them, I try to build prototypes of
them. In the original paper, I re-launched virtualization. It was
Who pushed you to do the company?
a mixture of old and new ideas. Some of the newer stuff, like
the transparent memory sharing, hadn’t been done before, I had two graduate students, and they’re actually the two
graduate students who have helped found VMware, Edouard
Did you have anything commercial in mind at first?
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.
29

30. 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.
“ The problem is companies are focused on how something is going to return
“
to the bottom line. Basic research is getting pretty rare.
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.
Graduate students are
motivated by many things,
including reading about how “ It’s definitely true that when you’re
in a position at a company, and you’re
looking at where to spend your
rich and famous other graduate
students have become. money, everything is focused on the
Academics who hope to also 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. you’re going to benefit from it.
30

31. 31
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 Stanford’s John Hennesey, and
recipient of numerous prizes and
recent president of the ACM.

32. orange: There are people who think that computers and IT What are some examples of research that don’t just cure headaches
have gotten so mature that we can now leave it to private industry 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 on it continuously for 50 years. We’ve been trying to work on
back to the things I learned when I was a student that my own making progress on it. Everything that Intel ships has parallel
students laugh at when I tell them. cores in it. The whole industry has bet its future that we’re
It’s going to be the same way when they’re older. One finally going to solve it.
example involves all the security problems we have with the So we are forced to transform the whole information
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. It’s not a controversial statement. Lots of start-up
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
funded by venture capitalists.
How much of the research now being done at Berkeley can only be
Technology is amazingly cheap done in academia, and how much of it could be done someplace in
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
get brilliant people from all over the world who don’t know that
call this the “headache model” things can’t be done. The U.S. university system is the best
in the world. If you ranked the top ten universities, probably
of funding research. 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.
“
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