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Ian Armas Foster, HPC In The Cloud, Avoiding Scientific Computing Bottlenecks in the Cloud, here.

Yesterday, HPC in the Cloud discussed the prospect of running scientific computing applications in the cloud on Amazon’s CPU and GPU cores in EC2, particularly with regard to computational fluid dynamics. It is fitting then that HPC Experiment, a research initiative comprised of teams of IT engineers, experts, and analysts, hosted a presentation on the subject this week.

GLL, Twin Primes are Useful, here,

Yitang Zhang, of the University of New Hampshire, has apparently proved a finite approximation to the famous Twin Prime Conjecture. This is a result of the first order. After ten days of progressively more detailed news, including today’sarticle in the New York Times, Zhang’s 56-page preprinthas just been released on the Annals of Mathematics journal website. This may be a revision of the original submission, which was said in a story in Nature last week to have needed “a few minor tweaks.”

Today Ken and I want to explain important aspects of the Twin Prime Conjecture.

Bobbito Garcia & Kevin Couliau, Doin’It In The Park, here.

 

Irving Wladawsky-Berger, WSJ, Spotting Black Swans with Data Science, here. Dude, didn’t you hear? No-one expects the Spanish Inquisition (or the Black Swan). Taleb is going to totally lose it because the Black Swan’s two main weapons are  Surprise, Fear, and Obscurity. 20 points to Hufflepuff and 20 points to Dr. Wladawsky-Berger for due diligence in demonstrating how the Pink Iguana dominates the ever quantitatively elusive Black Swan. Maybe Dataflow helps spotting Black Swans, I mean it can’t hurt, right?

This could help financial institutions, for example, to better assess their risks and potentially extend loans to individuals and businesses that would not have otherwise qualified. It could enable health care practitioners to better identify individuals who are most at risk to develop diabetes and start taking precautionary actions.

This ability to work across data sets and silos could help us get early clues to hard-to-predict, high-impact black swan events, so we can dig deeper into these clues and assess their validity.  When experts investigate catastrophic black swan events, be they airline crashes, financial crises, or terrorist attacks, they often find that we failed to anticipate them even when the needed information was present because the data was spread across different organizations and was never properly brought together.

Aaronson, Shtetl-Optimized, D-Wave: Truth finally starts to emerge, here.

Two years ago almost to the day, I announced my retirement as Chief D-Wave Skeptic.  But—as many readers predicted at the time—recent events (and the contents of my inbox!) have given me no choice except to resume my post.  In an all-too-familiar pattern, multiplerounds of D-Wave-related hype have made it all over the world before the truth has had time to put its pants on and drop its daughter off in daycare.  And the current hype is particularly a shame, because once one slices through all the layers of ugh—the rigged comparisons, the “dramatic announcements” that mean nothing, the lazy journalists cherry-picking what they want to hear and ignoring the inconvenient bits—there really has been a huge scientific advance this past month in characterizing the D-Wave devices.  I’m speaking about the experiments on the D-Wave One installed at USC, the main results of which finally appeared in April.  Two of the coauthors of this new work—Matthias Troyer and Daniel Lidar—were at MIT recently to speak about their results, Troyer last week and Lidar this Tuesday.  Intriguingly, despite being coauthors on the same paper, Troyer and Lidar have very different interpretations of what their results mean, but we’ll get to that later.  For now, let me summarize what I think their work has established.

Random.org, here. You can pick numbers directly from atmospheric noise rather than pseudo-random number generators, here.  I got:

Here are your 2 lottery tickets:

13-15-34-46-53 / 03
07-08-11-19-45 / 24

Timestamp: 2013-05-18 13:15:03 UTC

Perhaps you have wondered how predictable machines like computers can generate randomness. In reality, most random numbers used in computer programs are pseudo-random, which means they are generated in a predictable fashion using a mathematical formula. This is fine for many purposes, but it may not be random in the way you expect if you’re used to dice rolls and lottery drawings.

RANDOM.ORG offers true random numbers to anyone on the Internet. The randomness comes from atmospheric noise, which for many purposes is better than the pseudo-random number algorithms typically used in computer programs. People use RANDOM.ORG for holding drawings, lotteries and sweepstakes, to drive games and gambling sites, for scientific applications and for art and music. The service has existed since 1998 and was built and is being operated by Mads Haahr of the School of Computer Science and Statistics at Trinity College, Dublin in Ireland.

As of today, RANDOM.ORG has generated 1.32 trillion random bits for the Internet community.

Walter Hickey, BI, Here’s How Many Tickets You Need To Buy To Guarantee Winning A Prize In Tomorrow’s Gigantic Powerball Jackpot Lottery, here.

The Powerball Jackpot has hit a whopping $600 million, and it’s only a matter of time before lottery fever hits America again.

We talked about the various statistics a lottery player needs to familiarize themselves with, but there’s one in particular that players really care about. People don’t really expect to win the jackpot, but it’s certainly nice to win something from the endeavor.

The best way to improve your odds of victory are to buy more tickets. An while there’s no way to be 100% certain you’ll win on at least one of them, there are way to make sure you’ve got an estimable chance.

Read more: http://www.businessinsider.com/powerball-prizes-how-many-tickets-you-need-to-buy-2013-5#ixzz2TeRgGlrr

The Onion, Sponsored Content Pretty Fucking Awesome, here. Blog Free or Die, E.L. Wisty.

NEW YORK—Media consumers across the United States are reporting this week that sponsored content—articles and videos paid for by advertisers and distributed by print and digital publications—is easily the coolest fucking published material anyone could ever read or watch.

“I love, love, fucking love sponsored content,” said news and entertainment reader Erica Olson, adding that when she can tell a corporation is financially behind a piece of writing, she is even more inclined to click on it. “First off, it’s cool. That’s not debatable. Second, I don’t find it in any way insulting to my intelligence. In fact, it makes me feel smarter. And third, did I mention that sponsored content is just really fucking cool?”

Ben Walsh, Reuters, Why the US and Europe need more inflation, here.

The latest round of inflation data from the US and Europe is in, and inflation continues to fall below central bank targets. In the US, inflation in April was 1.1%. Prices fell 0.4% when food and fuel are included in the calculation. In Europe, inflation dropped to 1.2%, a three-year low.

Epicurean Dealmaker, Mr. Indispensable, here.

Seriously, folks, the brouhaha surrounding the upcoming nonbinding shareholder vote to separate the Chairman and Chief Executive Officer roles at J.P. Morgan is getting a bit silly. People are marshaling all sorts of weak, irrelevant, and disingenuous reasons on both sides to argue for and against the resolution. Hence we get ludicrous examples of access journalists asking a gaggle of powerful white men whether another powerful white man should lose his power. Gee, I wonder how that turned out, don’t you?

Scott Timberg, Salon, Jaron Lanier: The Internet destroyed the middle class, here.

Jaron Lanier is a computer science pioneer who has grown gradually disenchanted with the online world since his early days popularizing the idea of virtual reality. “Lanier is often described as ‘visionary,’ ” Jennifer Kahn wrote in a 2011 New Yorker profile, “a word that manages to convey both a capacity for mercurial insight and a lack of practical job skills.”

Raised mostly in Texas and New Mexico by bohemian parents who’d escaped anti-Semitic violence in Europe, he’s been a young disciple of Richard Feynman, an employee at Atari, a scholar at Columbia, a visiting artist at New York University, and a columnist for Discover magazine. He’s also a longtime composer and musician, and a collector of antique and archaic instruments, many of them Asian.

His book continues his war on digital utopianism and his assertion of humanist and individualistic values in a hive-mind world. But Lanier still sees potential in digital technology: He just wants it reoriented away from its main role so far, which involves “spying” on citizens, creating a winner-take-all society, eroding professions and, in exchange, throwing bonbons to the crowd.

This week sees the publication of “Who Owns the Future?,” which digs into technology, economics and culture in unconventional ways. (How is a pirated music file like a 21st century mortgage?) Lanier argues that there is little essential difference between Facebook and a digital trading company, or Amazon and an enormous bank. (“Stanford sometimes seems like one of the Silicon Valley companies.”)

Reed Smith, The Swap Report, CFTC Open Meeting Scheduled…, here. Derivatives regulation.

The proposed agenda covers:

  • Minimum Block Sizes for Swaps;
  • The ”Made Available to Trade” Rule Under section 2(h)(8) of the Commodity Exchange Act and Swap Transaction Compliance and Implementation Schedule;
  • Core Principles for Swap Execution Facilities (SEFs); and
  • Anti-disruptive Practices Authority – Interpretive Guidance and Policy Statement.

You can obtain information about participation by clicking here.

Shane Parrish, Farnam Street, The Divine Comedy, here.

Last month poet and critic Clive James released a new translation of The Divine Comedy. Although, in fairness, it’s more of an interpretation than a strict translation. I don’t think the purists would enjoy it, but if you’re not doing a masters thesis on it, I think you’ll love this translation. I know I’m certainly enjoying it.

Deus Ex Macchiato, The missing futures data repository, here.

Congress mandated that swap transactions be reported to a “Swap Data Repository” that regulators can monitor to conduct real-time market surveillance and that the public can access immediately and for free. Nothing comparable exists in the futures market. There is no “Futures Data Repository,” and no real-time public reporting of futures data, which means that the public will no longer have the access to market data that it was supposed to have under Title VII. This also creates a firewall between the markets and regulators, denying them access to the real-time trading data they need to determine whether speculators are manipulating the energy markets.

QuickFIX, Source code, here.

Source Code
QuickFIX
https://quickfix.svn.sourceforge.net/svnroot/quickfix/trunk/quickfixQuickFIX Log Viewer
https://quickfix.svn.sourceforge.net/svnroot/quickfix/trunk/quickfix-logviewer
Other Tools
Stunnel SSL tunnel
QuickFAST C++ FAST protocol implementation
OpenFAST Java FAST protocol implementation
Wireshark Packet decorder

Boost, C++ Libraries, here.

Boost provides free peer-reviewed portable C++ source libraries.

We emphasize libraries that work well with the C++ Standard Library. Boost libraries are intended to be widely useful, and usable across a broad spectrum of applications. The Boost license encourages both commercial and non-commercial use.

We aim to establish “existing practice” and provide reference implementations so that Boost libraries are suitable for eventual standardization. Ten Boost libraries are included in the C++ Standards Committee’s Library Technical Report (TR1) and in the new C++11 Standard. C++11 also includes several more Boost libraries in addition to those from TR1. More Boost libraries are proposed for TR2.

David Foster Wallace, Vimeo, This is Water, here. Little tighter than Burry’s UCLA address.

Peter Woit, Not Even Wrong, Miscellaneous Links, here.

Via Simon Willerton at the n-Category Cafe, Edinburgh now has a gallery with a wonderful collection of portraits of seventy mathematicians, including commentary from Michael and Lily Atiyah, an online version is here.

Michael J De la Merced, NYT A Citi Hedge Fund Busness Prepares for Life on Its Own, here. Dorfman ran Credit for MS back in the day.

The spinoff is a new test for Jim O’Brien and Jonathan Dorfman, the Citi executives who will serve as Napier Park’s co-chief executives. But in some ways, it opens up new opportunities for the nascent firm and its more than 100 employees, especially since it may attract new clients who hesitated to invest in alternative-asset operations owned by banks.

Matthew Boesler, BI, Timestamp: Bill Gross Calls The Moment The Great Bond Bull Market Ended, here.

Gross: The secular 30-yr bull market in bonds likely ended 4/29/2013. PIMCO can help you navigate a likely lower return 2 – 3% future.

Tom Lin, SSRN, The New Investor, here. It’s a long detailed recital of the key recent technology events in global trading with abundant references of uncertain quality. Limited insight is presented as to what the aggregated list of events  might mean  from either the technology, ecofin, or legal perspective. Didn’t come away with any sense of how the global regulatory framework is likely to change.  For example will EU regulations drive OTC trading to AsiaPac and US? Will US regulatory actions drive OTC trading to AsiaPac? Do I need to learn Chinese?

The Cy-fi side of this is more interesting than I thought it would be; but coining Cyborg Finance without any sort of ironic distance is still sort of creepy and pandering. The Mercer County Cash Register argument is that automating finance is not that much different than process optimization in Frederick Taylor’s Scientific Management and the Efficiency Movement. The serious guys from Tech running between interviews carefully implying that they are cutting edge rocket scientists with nanosecond latency HFT widgets are simply modern day Jerry Lewis impersonators who can boot Eclipse. But that view glosses over many of the valid issues that Lin lists: the global Ecofin linkage, Moore’s Law, Cyber Security, and Technology asymmetry are all significant sources of  idiosyncratic risk complicating the  straightforward process of automating trading. Don’t hire dopes to code up automated trading algorithms, I guess.

A sea change is happening in finance. Machines appear to be on the rise and humans on the decline. Human endeavors have become unmanned endeavors. Human thought and human deliberation have been replaced by computerized analysis and mathematical models. Technological advances have made finance faster, larger, more global, more interconnected, and less human. Modern finance is becoming an industry in which the main players are no longer entirely human. Instead, the key players are now cyborgs: part machine, part human. Modern finance is transforming into what this Article calls cyborg finance.

This Article offers one of the first broad, descriptive, and normative examinations of this sea change and its wide-ranging effects on law, society, and finance. The Article begins by placing the rise of artificial intelligence and computerization in finance within a larger social context. Next, it explores the evolution and birth of a new investor paradigm in law precipitated by that rise. This Article then identifies and addresses regulatory dangers, challenges, and consequences tied to the increasing reliance on artificial intelligence and computers. Specifically, it warns of emerging financial threats in cyberspace, examines new systemic risks linked to speed and connectivity, studies law’s capacity to govern this evolving financial landscape, and explores the growing resource asymmetries in finance. Finally, drawing on themes from the legal discourse about the choice between rules and standards, this Article closes with a defense of humans in an uncertain financial world in which machines continue to rise, and it asserts that smarter humans working with smart machines possess the key to better returns and better futures.

Hack the market, the other interesting thing about the Serge Aleynikov story, here. A discontinued blog.

A few months back I’d seen Jane St‘s Yaron Minsky give an interesting talk on OCAML in which he describes the virtues of ocaml as applied to the algo trading domain.  You should watch it as he’s entertaining and clearly a “true believer.”   The key argument he makes is that algo trading requires correctness, agility and performance and that ocaml provides a great set of tools for addressing these needs.  Correctness and agility are supported by the rich type system while performance is just a happy feature of the language.

Phil Albinus, Advanced Trading, Is Trading Via Microwaves Ready for Prime Time, here. So Dyna Pie would be using “brave new technology” attached to dirigibles. Seal Team 6 technology?

We spoke with Shawn Melamed, global head of commercial products at Strike Technologies, about who is using this brave new technology.

Is this a new technology that investment firms are using right now or is it still too new and untested for trading?

Shawn Melamed, Strike Technologies: There are probably 20 to 30 firms using it today. It’s relatively new obviously. The technology has been around only for a year now – really live – but people have been using it. Some of the larger firms initially built it internally for their own trading purposes and not through a vendor. What you see now only recently is the rationale to build a commercial offering and we’re spearheading that (offering). The vendors who offer that tend to offer the economies of scale. It’s a very heavy expense, much harder than just buying from a teleco provider the same type of line.

Can you describe these firms? Are they large institutional investors or smaller hedge funds?

Melamed: A combination of both. We have the larger institutions and banks and you get the prop firms that are trading equities, futures, FX – it depends. A lot of the benefits of microwave technology is to provide one asset class data at another data center. The ability to get futures data, to trade equities or ETFs, is one thing – the ability to get futures data to trade treasuries is another.

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