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Steven Poole, aeon, Slaves to the algorithm, here. hat tip ws.
At first thought, it seems like a pure futuristic boon — the idea of a car that drives itself, currently under development by Google. Already legal in Nevada, Florida and California, computerised cars will be able to drive faster and closer together, reducing congestion while also being safer. They’ll drop you at your office then go and park themselves. What’s not to like? Well, for a start, as the mordant critic of computer-aided ‘solutionism’ Evgeny Morozov points out, the consequences for urban planning might be undesirable to some. ‘Would self-driving cars result in inferior public transportation as more people took up driving?’ he wonders in his new book, To Save Everything, Click Here (2013).
More recently, Gary Marcus, professor of psychology at New York University, offered a vivid thought experiment in The New Yorker. Suppose you are in a self-driving car going across a narrow bridge, and a school bus full of children hurtles out of control towards you. There is no room for the vehicles to pass each other. Should the self-driving car take the decision to drive off the bridge and kill you in order to save the children?
Joe Weisenthal, BI, Computer Industry Pioneer Claims To Have Figured Out The True Creator Of Bitcoin, here. Nelson does a good Sherlock Holmes impression in the video, don’t miss it. Just start counting until Lipton gets ahold of this, 3 2 1… See also quartz and obviously the Winklevoss twins are photo bombing this story as well so it’s just a matter of time before Blog Maverick weighs in. Pink I sees this as Nelson barking up the wrong tree. The gulf from doing 500 pages of inter-universal Teichmuller theory as an extension to p-adic Teichmuller theory to Merkle Tree hashing and the 20 lines of C-code for the Poisson distribution seems like it could be large. Nelson has Mochizuki confused with Kubla Khan? Besides, everyone knows that Al Gore is Satoshi Nakamoto, Serially.
Ted Nelson, a computer scientist, has posted a video to the web claiming that he’s figured it out, and that it’s Kyoto University math professor Shinichi Mochizuki.
Henry Blodget, BI, Bitcoin Just Hit The Big Time — Here’s What Everyone Ridiculing It Doesn’t Understand, here. The aspect of mining computer cycles for monetization is solid. Bitcoin, HFT, and various other sorts of quantitative modeling all fall in the same general category. The argument would go more or less the same way Daniel Boorstin outlines the rollout of the Industrial Revolution in The Americans. The unifying theme for Aircraft Wing simulation, Computer Aided Design, Fluid Flow, Automated Trading, Collateralized Securitization, and even Advertising Auctions is monetization of the capacity to allocate compute cycles in substantial quantities at specific locations.
The electronic currency Bitcoin just got a big vote of confidence from one of the world’s most successful venture capital investors.
Fred Wilson of Union Square Ventures just invested in a startup called “Coinbase,” which facilitates Bitcoin transactions.
This investment doesn’t mean that Bitcoin is guaranteed to become a mainstream currency, but it’s a small step in that direction.
Phys.org, US seizes Bitcoin operator accounts, here. I suspect Nelson shouldn’t spend a lot of time waiting for his invitation to speak at Kyoto U.
A warrant revealed by the Department of Homeland Security showed a judge signed the seizure order Tuesday for the accounts of Mutum Sigillum LCC, a subsidiary of Japan-based Mt. Gox, the world’s biggest Bitcoin exchange.
The warrant said the account based on the electronic payments platform Dwolla and held at Veridian Credit Union “was used to move money” as “part of an unlicensed money service” in violation of US law.
The US law enforcement action creates doubts about the future of Bitcoin, a mysterious digital currency which saw a flurry of interest this year which some called a bubble.
Bitcoins were launched in 2009 in the wake of the global financial crisis by an anonymous programmer who wanted to create a currency independent of any central bank or financial institution.
A form of “e-money,” Bitcoin is made of strings of dazzlingly complex code, written in such a way that it becomes increasingly difficult to generate new Bitcoins, with the number in circulation designed to eventually top out at 21 million.
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.
Samantha, Create Blog, Your Blog Sucks, here. There’s got to be Customized Cash Register blogs that suck worse than Pink I.
Every time you log in to your dashboard, the sound of crickets greets you as you check out your weekly traffic statistics. You think why isn’t it working? I’m posting content like they said, shouldn’t I have a flood of visitors?
Well, there could be many reason why this is happening, advertising, SEO etc, or maybe your blog sucks?
Samantha: O that we now had here
But one ten thousand of those followers in England
That do no work to-day!
E.L. Wisty: What’s she that wishes so?
My cousin Samantha? No, my fair cousin;
If we are mark’d to die, we are now
To do our country loss; and if to live,
The fewer followers, the greater share of honour.
God’s will! I pray thee, wish not one follower more.
By Jove, I am not covetous for gold,
Nor care I who doth feed upon my cost;
It yearns me not if followers my garments wear;
Such outward things dwell not in my desires.
But if it be a sin to covet honour,
I am the most offending soul alive.
No, faith, my coz, wish not a follower from England.
God’s peace! I would not lose so great an honour
As one follower more methinks would share from me
For the best hope I have. O, do not wish one more!
Rather proclaim it, Samantha, through my host,
That he which hath no stomach to this blog,
Let him depart; his passport shall be made,
And crowns for convoy put into his purse;
We would not post in that man’s company
That fears his fellowship to die with us.
This day is call’d the feast of Crispian.
He that outlives this day, and comes safe home,
Will stand a tip-toe when this day is nam’d,
And rouse him at the name of Crispian.
He that shall live this day, and see old age,
Will yearly on the vigil feast his neighbours,
And say “To-morrow is Saint Crispian.”
Then will he open his browser and show his scars,
And say “These things I learned on Crispian’s day.”
Old men forget; yet all shall be forgot,
But he’ll remember, with advantages,
What feats he did that day. Then shall our names,
Familiar in his mouth as household words-
Godel’s Last Letter, Mathbabe and Ritholtz,
Salmon and Tao, Mankiw and Pollack-
Be in their flowing cups freshly rememb’red.
This story shall the good man teach his son;
And Crispin Crispian shall ne’er go by,
From this day to the ending of the world,
But we in it shall be remembered-
We few, we happy few, we band of brothers;
For he to-day that shares his posts with me
Shall be my brother; be he ne’er so vile,
This day shall gentle his condition;
And gentlemen in England now-a-bed
Shall think themselves accurs’d they were not here,
And hold their manhood’s cheap whiles any speaks
That blogged with us upon Saint Crispin’s day.
Train is pulling into PJ gotta go.
:wq
Steve Lohr, NYT Bits, David Ferrucci: Life After Watson, here. What is incredibly powerful AI that can combine deductive and inductive processes needed to develop, apply, refine and explain fundamental OATS risk management and reporting at a large hedge fund?
Dr. Ferrucci, 51, said he had “a great, great career” at I.B.M., spanning 20 years, and “they paid me very well.”
He said he “never imagined myself at a hedge fund,” but eventually the appeal of working in a smaller environment in an entirely new field for him — applying artificial intelligence to macroeconomic modeling — won him over.Dr. Ferrucci said the more recent work he was doing at I.B.M., called WatsonPaths, was the direction he thought artificial intelligence research needed to go to make further advances, and it was the approach he saw Bridgewater pursuing to economic modeling.
Much of artificial intelligence today, he said, focuses on mining vast amounts of data to make predictions. Those predictions are based on statistical probabilities and patterns — a certain symptom is highly correlated with a certain disease, for example.
“But in a purely data-driven approach, I can’t explain my decisions,” Dr. Ferrucci said. “People are so enamored with the data-driven approach that they believe correlation is sufficient.”
The Big Data formula, he noted, has proved to be “incredibly powerful” for tasks like natural-language processing — a central technology behind Google search, for instance.
WatsonPaths, by contrast, builds step-by-step graphs, or paths, that trace possible causes rather than mere statistical correlations. In the case of medicine at the Cleveland Clinic project, for example, the paths go from an observation of symptoms to a conclusion about the diagnosis of a disease and treatment.
That approach is a hybrid of the Big Data tools, which sift through troves of medical literature, and logic tools to identify likely chains of inference — what humans see as logical explanations for the “why” of things. The approach is also a step in the direction of classic artificial intelligence, which relied on knowledge rules and relationships, to create so-called expert systems. The blend combines elements of what Dr. Ferrucci termed “my 30-year journey in A.I.”
At Bridgewater, Dr. Ferrucci sees a similar path to modeling the economy and markets. “Their approach to investment,” he wrote in his e-mail, “is based on a fundamental understanding of how the global ‘economic machine’ works.”
Its models, he added, are “informed by but not blindly driven by the data.” The opportunity, Dr. Ferrucci wrote, is to build “predictive systems that fit perfectly with my interests. How cool is it to imagine a machine that can combine deductive and inductive processes to develop, apply, refine and explain a fundamental economic theory?”
Paul Baiocchi, ETF Report, The Hottest Bernanke Trade in ETFs, here. You know in addition to IR swap market microstructure, the use of ETFs to bundle rates risk seems like a real good thing to know about.
Last Wednesday, the little-followed, largely overlooked ProShares Ultra 7-10 Year Treasury ETF (NYSEArca: UST) went from $12 million in assets under management to more than $833 million overnight.
The increase in assets of more than almost 6,000 percent overnight was enough to catch our eyes on its own, but the fact that it accompanied a 53 percent increase in assets in a similar, multibillion-dollar ETF—the iShares Barclays 3-7 Year Treasury Bond Fund (NYSEArca: IEI)—really rang the alarm bells.
Sam Biddle, ValleyWag, Ex-Facebook Exec: Startup World Should Be “Utterly Ashamed Of Itself, here.
Former Facebook bigwig and current investor Chamath Palihapitiya isn’t pulling any punches at this week’s TechCrunch Disrupt, where many a punch is typically pulled. He’s disgusted with what’s called tech innovation now, saying “we are at an absolute minimum in terms of things that are being started.”
Joe Wiesenthal and Sam Ro, BI, Cypriot Banks Reopen, And So Far It’s Pretty Quiet, here.
So far, the only people queuing outside #Cyprus‘ banks?… Journalists. pic.twitter.com/6tJgSJBIpD
Coppola Comment, The Broken Euro, here.
Imagine you live in a prosperous country, with a lovely climate, beautiful beaches, blue seas. But there’s something funny about this country. It doesn’t have a functioning banking system.
You can put money into your bank, but you can’t get it out again. At least you can, through ATMs, but only in very small amounts.
If you have money on deposit, you can’t take the money out and close the account. And if it’s a time deposit, when it reaches the end of its life, you can’t have the money to spend. You have to roll it over into a new deposit.
You can’t cash a cheque in a high street bank. You can’t pay bills in a high street bank, either. And no high street bank is lending any money, so if you want a loan, forget it. In fact high street banks are not much use.
Your employer pays you in cash, because there are no electronic payments. Which is just as well, really, because you need cash. There are no automated payments such as direct debits, so you pay all your household bills in cash. Credit and debit cards are no longer accepted anywhere, so you buy all your shopping and petrol for your car with cash. You can’t make phone or internet purchases.
Naked Capitalism, Yes, Virginia, HFT and Liquidity are Not All They Are Cracked Up to Be, here. I suspect that my elderly right-thinking in-laws took over Naked Capitalism to write about stuff they heard about that makes them really mad. To be fair though, my in-laws understand about internalization, and whoever wrote this, impressive academic citations notwithstanding, doesn’t.
You may have seen a big outbreak in the academic literature and business media of defenses of liquidity for liquidity’s sake, evidently prompted by increased interest in and in the EU, implementation of transaction taxes as a way to tame speculation and secondarily raise revenues.
And other efforts to curb market manipulation are underway. For instance, the SEC and the FBI are joining forces to try to rein in predatory HFT, but are finding it an uphill battle due to the fragmentation of information:
Doron Zeilberger, Opinion 112, here.
It took the Annals of Mathematics many years to finally accept, very reluctantly, Tom Hales’ seminal, computer-assisted, article proving Kepler’s 300-year-old conjecture, because they didn’t trust computer proofs. It took them only a couple of months to accept a human-generated proof, by Daniel Biss, that was later found, by Nikolai Mnev, to be seriously flawed (and even though the error was pointed out more than five years ago, it took them about four years to publish a retraction). Annals editor Robert MacPherson looked at the bright side, commenting that “mathematics is self-correcting”. I am not so sure, Professor MacPherson! For any crooked politician that has been caught, there are ten of them that have never (and will never) be caught. I am sure that there are many other humanly-generated Annals articles that are seriously flawed, because they were only checked by one or two human mathematicians, who would rather do their own research, and since they remain anonymous they are not accountable for their sloppy job.
