Rapport sur les orientations de la recherche technologique dans la Silicon Valley. « What’s Left to Know ? »

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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

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Rapport sur les orientations de la recherche technologique dans la Silicon Valley. « What’s Left to Know ? »

  1. 1. research in a total-connect worldconversations about Tech Research Futures
  2. 2. Editorial: Talking about TalentThis is about a set of conversations. Indeed, a conversation that started inFebruary 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 evenrelevant anymore? Those conversations continued and started involving others, including the authorof this remarkable set of interviews. Things got pretty transgressive: what if what wesee before us really is it for the next 20 years? What if most of the important tools andmethods 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 massivelyincremental mode. To explore where research is going, you have to talk to practitioners. And, youhave to speak in their language, understand their issues, and know the canon. Wewere 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 StreetJournal and Forbes, Lee was the perfect entry-point into a wider discussion. The resultis what you have here --- a rich set of discussions with some of the companies anduniversities responsible for the future of high-tech advanced research. Those inter-views plus our own first hand observations and interactions with peers and majorcustomers 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 recognizethat 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. Respectfor Talent, recognition that Talent is highly mobile and votes with its feet -- this is whatdrives the questions posed here. Is that PhD as important as that startup? Is mungingsome ugly public data set as rewarding as working on the Facebook graph? These arenot questions about technology, but about where Talent wants to go and what it wantsto accomplish. Let’s add to that: when it wants to accomplish it. - Georges Nahon CEO -Mark Plakias VP Orange Silicon Valley 3
  3. 3. 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 suchAt 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 bethe IT, communications, and online media and commerce producing anything competitive with what the barbariansindustries. In the course of this ongoing collaboration the produce and deliver. A condescending view is that Corporatevoices from both industry and academia have spoken and R&D projects may be taken by surprise by the agility andtheir message seems clear: life in the “Labs” -- and beyond -- audacity of the barbarians -- who have no faith and nois never going to be the same. Almost daily we can observe respect for the laws or rules governing the establishmentsa 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 carrythe fruits of smart people working outside of the corporate the perception of threat, as they have nothing that can beor academic R&D sphere. Who are these smart people? threatenedThey’re not wearing white coats, nor do they always But is this just attitude, or is it data-driven? Thepublish papers. From the corporate R&D establishment’s idea that analytics and pattern-recognition of very large dataperspective, 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. Asthings are running very fast in a digital and networked world, Facebook’s Cameron Marlow puts it in his interview: “Theand what research does and how it is done probably needs social interactions on the Internet, and on Facebook into be revisited. The title of this report phrases the current particular, are at a level of detail and scale that haven’tstate of affairs in information and tech research as a question existed before. They allow us to answer questions aboutin epistemology, but ‘what’s left to know?’ is also a question social interaction and forces that we’ve never been able toabout tempo and scale. We know big corporations spend answer...” Although SRI’s Winarsky does not see Zynga’smost of their time protecting the most profitable part of their “new type of business proposition” as anything resemblingbusiness now, but digital platforms are impacting these research, he does describe it as “even more valuable thancenters so quickly that further R&D in these disrupted and technology.” Google’s Peter Norvig sees the availability ofdiscarded 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
  4. 4. 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 technologiesand 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 happeningthe industry were calibrated by other incumbents’ R&D labs internally in R&D is discussed at various points in theseperformance in a time-scale equal for all players. More pages as management seeing all this money and time spentimportantly, everyone was staying in their own business developing new innovative products, but getting beat toterritory -- until digital changed everything and made every market by barbarians. This seems to be forcing managementcompany look like it was playing in the other guy’s garden. to succumb to the temptation to kill years of effort, with theThe 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 andall 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 ofcore of computing and communications seems somehow PALM and its coffer of patents , the acquisition of Nortel’snot as visible or compelling as it used to be. While this is patent portfolio by a consortium of IT companies and thea contestable statement, and there are rich discussions Google/Motorola multi-billion dollar patent portfolio grabsabout this point inside these pages, one incontestable fact have thrown this strategy into a new light: one where the bestis 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 toDavid Patterson recognizes this trend, which he views as drive licensing claims which add $5 to the cost of a mobilemanageable: “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 (andThe 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
  5. 5. 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 corporateCharles H. Duell, who held the post at the time, far from being fortunes, in coming years and decades. After all, both carspessimistic about future discoveries, was actually a booster and car companies look drastically different today thanwhen it came to what Yankee ingenuity would make possible, they did 50 or even 25 years ago, despite having the sameakin 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 andBut 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 questionas a warning of the dangers involved when a given generation of the future of data and IT, let’s first consider the classicbecomes so engrossed in its own repertoire of massive view of the subject - with a bow to particle physics, we caninventions 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 twoif 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 withcomparison, and requires our full attention and ingenuity? dominant market positions and the healthy profit marginsTo be clear, we are not talking here about the totality of that accompany them. The research-to-product transitionscience and technology, but instead, a subsection of it, in followed a traditional path, beginning in a lab somewhere andthe enormously important world of IT, especially as it involves then making its way to the marketplace, perhaps pausingdata 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, federalof computers - Moore’s Law, new data base tools and funding for research has diminished or been reallocated.
  6. 6. 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
  7. 7. 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 unchangedIf you are interested in exploring some aspect the many technologies built on Newtonianof the “social graph,” where would you rather principles. We hope readers appreciate that whenbe: at even the best-funded academic depart- we ask “Does IT research still matter?” wement, or at Facebook, where you would have are asking it not because we view the issue as settled, but instead, in an attempt toaccess 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
  8. 8. 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 senseBell 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.”1in the difficulties of profits and market cap. (Though the There are certain questions aboutknowing 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 toin-house research. The report did not sit well with suggest that large research operations
  9. 9. 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 best12
  10. 10. “ 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
  11. 11. “ 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 emergedwork on the “Page Rank” algorithm fully-formed from the heads of its twowhile being funded from a grant from founders, the company itself is the firstthe 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 bein isolation. At the same time Brin and problematic to assume that SiliconPage were doing their work, two other Valley operated one way in the lastresearch groups had essentially the era and an entirely different way today.same insight involving how a page’s Descriptions of each era are highlylink structure could be mined for crucial anecdotal; for every example of oneinformation about the page’s reliability. pattern for the path that research might Later, as Google engineers were take going from lab benches to storescrambling to adjust to their company’s shelves, it’s possible to come up with aastonishing growth, their seeming competing narrative.improvisations occurred inside a Consider storage. Much of theconsiderable ecosystem of existing pioneering work on the modernideas. One of many examples is the magnetic disk drive was done at IBMPaxos Algorithm, developed in 1990 by during the 1950s, and companiesLeslie Lamport, then a DEC researcher, have been responsible for the most ofwhich 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 mightunreliable computers, a clear problem density - the storage equivalent of unknowingly be a symptom of whatin a massively parallel data system Moore’s Law. (The cost of storing a has been described as the techlike the one Google’s engineers were unit of information on a disk drive is world’s current data fetishism. In manybuilding. (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
  12. 12. & 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 Googlefrom perfect, its ability to allow a basic the very moment that market pressures and virtually any other company orunderstanding of almost any text in any are forcing firms to pull back on R&D, academic department will remainlanguage 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 diskgoes beyond implementing machine play its familiar role and take up the storage continue apace; a petabyte 3.5learning algorithms. Especially in slack. Thus, the basic view is that by inch drive should cost $250 or so withine-commerce, it is assumed that the vast ignoring research, we won’t be creating the decade. In addition, there are manyamounts of data we leave behind via the ecosystem that will allow the next efforts underway to turn the buildingour mobile phones and computers have Google to be formed. and running of a giant data center intosome secret key to our future behavior. In a similar vein, these people a commodity undertaking, no moreThe middling success that companies would have a different interpretation difficult than setting up a corporatelike Amazon and Netflix have with their of current events than those offered LAN. These efforts are occurring inrecommendation systems suggest that by critics of the Standard Model. For academia as well as in a new breedmuch 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
  13. 13. for example, to providing versions of undertaking, where the investmentHadoop and its related tools that an calculus is entirely different - VCs sayaverage IT shop can use. that their ideal remains research whose It need be noted that even we, in our commercial appeal is demonstrativelydeliberately provocative role questioning obvious. Or, as a spokesman forassumptions about research, would Sequoia Capital, currently one of thehave to agree that there are potentially most successful of the fabled venturerevolutionary breakthroughs on the firms along Palo Alto’s Sand Hill Road,horizon. An obvious one involves “In our little corner of the world, we getquantum computing. Computer involved in the “D” part of R&D. We leavescientists disagree about the repertoire it to the very creative and very capableof problems that a quantum computer talents at universities, government labscould effectively take on. But in the and corporate centers to dream up avery least, they will force us to rethink world of new possibilities.”the encryption systems currently In closing, there is no doubt that theresponsible for all Web commerce. massive scalability of Internet-based Another potential breakthrough businesses has changed the way weinvolves a fundamental algorithmic think about research. The urgencyadvance in learning how to parallelize created by these scale effects is basedcomputing problems. Microprocessor on the sheer amount of data available:companies have long since given which poses not just monetization butup on making a single chip that runs research opportunities that are hereever-faster; chips today ship with four and now.or eight (or even 64) “cores,” each of The world has changed, and inequal power. But just as it takes nine the following section we summarizemonths to make a baby, most software the contrasts in that journey from thenproblems need to be solved in order, to now.one step at a time. A fundamentalalgorithm to change that - not thatanyone has any idea of what it mightlook like - is inevitable . “ Finally, we’d also like to pointout that even in a world of constant We must also be careful aboutchange, some things endure. One isthe role played by venture capitalists. assuming that the yawning gapVCs have never seen themselves in that now exists between a Googlethe business of funding basic research,and certainly don’t these days. Outside and virtually any other company orof 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
  14. 14. 1940 1960 1980 1985 1990 1995 2000 2005 2010Organizations 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&DSoftware 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.
  15. 15. 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.
  16. 16. 19PeterLeeMicrosoftA Proud R&D TraditionalistAs new managing director of MicrosoftResearch Redmond, Lee heads upone of the computer industry’s fewremaining research operationspatterned after the labs of an earlierera - autonomous and setting its ownlab direction.
  17. 17. 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 thepeter lee: There are some valid comparisons. We are an research areas are organized around a broad, major directionindependent organization, so the business groups don’t tell in computing. For example, machine learning, visualizationus 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’rehighly motivated to get their research ideas onto every desk- What do you think of some of the newer ideas that people are talkingtop 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 levelthat researchers have when they think they have a good and Oh, I think it’s incredibly interesting. The potential for whatuseful 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 alane being a kind of mission-focused research where we’re much broader community and increase the idea flow in waysreacting 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 closelyAnd 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 amountof research here, but also demand that we get good impact of activity in both the academic and enthusiast communitiesin all three. around Kinect hacks. That is an example of something that just kind of spontaneously grew up on its own but is a tremendousYou 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 theacademic community. Show impact on our product groups, I don’t see it as either/or. The things that Microsoft Researchand show impact in terms of progress towards developing does for Microsoft, couldn’t be done any other way. We’re areally 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
  18. 18. “ 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’tof 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 themachine translation products. All the cloud services - Azure, There’s probably a cyclical nature to this. Within the companySQL server, Hotmail - have their origins in Microsoft Research. right now, the perspective on Microsoft Research and theAnd 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 understandhard to imagine crowd-sourcing those sorts of things. that these things come in cycles. Having said that, crowd-sourcing and mass globalizationconcepts are extremely interesting, and we believe they arepotentially a great source of innovative ideas.There’s a pretty strong correlation between how profitable acompany is and how much it spends on research. Do you worryabout funding from Microsoft Research being cut in the eventcompany profits decline? The take-awaysWe’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 impacton the company relative to our size is pretty enormous. Andso viewed like that it doesn’t seem like there’s much to worry Even when you’re at aabout. Of course, we want the company to be very successfuland be more successful every day, but objectively I don’t think company with a long-termthere’s an issue about our security here. Except that, and this commitment to research,is something I also learned at DARPA, people doing basicresearch everywhere in this country have certain anxieties it’s nice to have the occasionalabout society’s understanding and tolerance about basicresearch. And so our researchers here aren’t immune to that. hit on your hands to keep the top bosses happy. 21
  19. 19. 22JoelWestKeck Graduate Institute of Applied Life Sciences“Open Innovation” and Its DiscontentsThere is no issue related to themanagement of R&D more popular atthe moment than “Open Innovation.”Joel West knows as much about it asanyone, making his commentary on itsoccassional misuse worth nothing. Aconsultant and business professor atthe Keck Graduate Institute, he is alsoco-editor of Open Innovation:Researching a New Paradigm fromOxford University Press.
  20. 20. orange: As far as big ideas in business, Open Innovation seems A lot of companies are cutting research budgets these days, and onein 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 Openparticularly hot area, in the way that the “Resource-Based Innovation. When I go and talk to people out there, a lot ofView 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 ofInnovation” on Google Scholar, you see that there are their R&D people or B) just gutted their R&D department andthousands 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 somethingpeople were already doing? We don’t have a term for it, but there is an Open InnovationSome people call it the “Old wine in new bottles issue.” Some equivalent of “greenwashing.” Greenwashing is where peoplepeople say this is a practice that’s been going on, and it’s just wrap themselves in claims of environmental-friendliness, butbeen given a new name. Certainly, what’s true is that much of don’t change their actual practices to make their productsthis 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 “Openin 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 makeinside 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 Openlarge industrial corporations, in which they assume they know Innovation, there is an attitude change and they really arebetter than anybody in the world. Open Innovation forces being more collaborative. At other times, it’s just a new namefirms 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 thatnot all the smart people in the world work for them. That They could have a universities relations arm. They could haverecognition, 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 patentpeople 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 theindustry with the PC revolution. You saw manufacturing person bringing innovations into the firm. They usually don’tand product development going offshore and the Internet’s give that title to somebody who’s trying to find markets fordissemination of information, and open source software. existing technology.And all of a sudden, people realized that the idea that anycompany - even the greatest company in the world - couldhave a monopoly or a preponderance of knowledge in anarea just isn’t plausible. 23
  21. 21. “ 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 oughtLike many things in to be aware of what the best technology is for anything relevant to their line of business. They shouldn’t automatically assumebusiness, 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 thepart-real, part-hype. The real state of the art of what’s going on outside the company, to beopportunity 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 opento all good sources of ideas.The hype comes with companiesthat hide behind the term as aeuphemism for cuttingresearch budgets. 24
  22. 22. 25CameronMarlowFacebookA Hot Start-up Begins Its R&D Rite of PassageThe only “research problem” mostpeople associate with Facebookis figuring out how to add enoughservers to keep up with its user base.But Facebook is starting to learn thelesson of many tech companies; thatif you are in it for the long haul, you’vegot to start planning for it.
  23. 23. orange: So why exactly does Facebook need researchers? How do you distinguish research from engineering? Couldn’tDon’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 “FacebookResearch,” with proper nouns, but Facebook does a lot of The types of questions we’re answering are as fundamentalresearch. 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 graduateschool, especially those interested in corporate research The social interactions on thelabs, want to do great work, but also want to have an impacton people’s experience. The image I’ve tried to present for Internet, and on Facebook inresearch at Facebook is one where we work as closely withthe product as possible, because the problems we face are particular, are at a level of detailsome of the most interesting problems that exist. and scale that haven’t existedHow often are people surprised when they hear about Facebook before. They allow us to answerdoing research-research as opposed to engineering? questions about social interactionI guess I may be a little biased, but I don’t think anyone’ssurprised that I’m doing research, or the people that I work and social forces that we’ve neverwith 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?” orWe 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 cameto Facebook, we’d be doing some kind of research. The Can you give me an example of work you’re doing at Facebook thatpublishing model here is a little different than some other someone in the academy would look at and say, “Yeah, that wouldcompanies. In other research operations, there is an emphasis be legitimate computer science research if it were happening in myon 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 workYour real work is working on problems. So there is a bit of that’s being done with taking our code base and compiling ita different incentive here. People really want to make users into C. The compiler community is very interested in HipHopmore 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
  24. 24. 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 onsimply 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 peopleWe have a PR department here that likes to put us in front of have seen it and they give you the thumbs-up, you commitreporters, and even though the types of things we generate your code. You don’t wait around for some product team toare on the academic side of things, they tend to be of give you a blessing and build it themselves. If you know howgreat interest to the world. So almost every paper that we to do it, just do it yourself. People at Facebook are actuallypublish is turned into a much bigger communication about making changes to the core product, which may not be partFacebook 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 bigtechnology companies? The take-awaysThe model I used to think about the standard corporateresearch labs is that the company was like a planet, with thelab being in orbit spinning around the planet, and in case theplanet implodes, there’s some chance that this other heavenlybody 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 fundamentallychanged 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
  25. 25. 28MendelRosenblumVMware, StanfordOn Being A Basic Research Poster BoyRosenblum, as an associate professorat Stanford University, did the originaltheoretical work that led to VMware, makinghim one of the handful of Silicon Valley’srare entrepreneurs who was able to growsome basic research into an enormouslyimportant company.
  26. 26. orange: First off, do you even agree that the work you did onvirtualization would qualify as basic research?mendel rosenblum: I was involved with a group ofpeople trying to build a super computer, a very, very, largemachine. But I wasn’t really interested in scientific computing,so I was trying to find out if we could use it for somethingelse, like running a whole enterprise’s worth of computation.That’s how we stumbled on the idea. If you look at the originalpapers, we were talking about running a bunch of virtualmachines with modern computing environments on a singlemachine. We didn’t know it at the time, but the vision turnedout 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 prettyby 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 aan 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 ofthem. 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, likethe 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, EdouardDid you have anything commercial in mind at first? Bugnion and Scott Devine. They’d been sitting aroundWe were going to do a virtual machine monitor for one of watching the Yahoo guys, David Filo and Jerry Yang, takethe big servers like Digital Equipment or HP. That’s what our off and become famous. So they immediately said, “Can weresearch was on: building software for the big servers. And commercialize it?” It wasn’t an ideal time for me, because Iso we went and talked to the companies making them, and was coming up for tenure. But I talked to (Stanford Universitythe first one said, “Why don’t you just come and join us and president) John Hennessy about it, and he told me he haddo it as an employee?” But that didn’t sound very interesting started MIPS when he was coming up for tenure, so he didn’tto me. see a problem.Why not?Oh, I don’t know. I guess we had the idea that you’re notgoing to get like rich and famous building up a big companyif you do it as a team inside a big corporation. I remembertalking to a vice president at Digital Equipment Corporation,and he named these examples of projects that they hadnurtured inside DEC and then spun out. As far as I could tell,they were all disasters. 29
  27. 27. 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 aremotivated 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 yourrich and famous other graduatestudents have become. money, everything is focused on theAcademics who hope to also short-term of the company. Withdo well in the marketplace research, the hardest thing for peoplewould be wise to surround is that you don’t really know how “themselves with them. you’re going to benefit from it. 30
  28. 28. 31DavidPattersonUC BerkeleyThe Best Days of Traditional Research Still Lie AheadDave Patterson is an embodimentof the elite of traditional academiccomputer research. He is a professorat UC Berkeley, known for hismicroprocessor architecture workwith Stanford’s John Hennesey, andrecipient of numerous prizes andrecent president of the ACM.
  29. 29. orange: There are people who think that computers and IT What are some examples of research that don’t just cure headacheshave 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 hardestdavid patterson: That’s just crazy. We’ve just scratched problem computer science has faced. We’ve been workingthe surface of information technology. In my career, I can look on it continuously for 50 years. We’ve been trying to work onback to the things I learned when I was a student that my own making progress on it. Everything that Intel ships has parallelstudents 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 informationtechnology 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. Wemajor security threat to this country. It’s embarrassing that it’s can put more transistors into chips, but we can’t turn it intoso vulnerable. People are relying on programs like Windows performance unless we solve one of the hardest problemsNT 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 couldthere are still real big holes. You might call this the “headache finally make easy-to-write parallel programs. There’s a Deadmodel” 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. “ 32

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