Results for “Watson”
84 found

Assorted links

1. How did popcorn come to be associated with the movies?

2. The ascendancy of data in eight young economics stars.

3. “Hauling iron ore across Australia’s outback pays some 400 engineers about $224,000 per year, but the gravy train is coming to an end thanks to robots.”  The Ricardo effect.

4. Possibly innocent man was held in solitary confinement for 41 years, he has now passed away.

5. Does eye contact harm your case? (speculative)

6. Watson, meet your new partner, Amos.

7. www.grundeinkommen.ch.  Wikipedia ist hier.

Where this all is leading

I.B.M.’s Watson, the supercomputing technology that defeated human Jeopardy! champions in 2011, is a prime example of the power of data-intensive artificial intelligence.

Watson-style computing, analysts said, is precisely the technology that would make the ambitious data-collection program of the N.S.A. seem practical. Computers could instantly sift through the mass of Internet communications data, see patterns of suspicious online behavior and thus narrow the hunt for terrorists.

Both the N.S.A. and the Central Intelligence Agency have been testing Watson in the last two years, said a consultant who has advised the government and asked not to be identified because he was not authorized to speak.

There is more here, pointer is from Claudia Sahm.

Assorted links

1. “Wanting to be liked.”

2. Trifecta (good photos too).

3. Hobson, underconsumption, globalization, and the great stagnation, by Robert Skidelsky; uneven but interesting.  I’ve been waiting for this tradition to be rediscovered, I suppose Hilferding is next.

4. WSJ reviews the excellent Arnold Kling.

5. I am more pro-immigration than he is, but Ross Douthat is right now writing the best material on immigration reform.  It is odd for me how, in the midst of a major policy discussion of the issue, most of the people I read cover the topic but do not mention or much discuss five nights of riots in Sweden.  The economics of additional immigration work out fine in my view, and I am happy to count the well-being of foreigners without hesitation.  The real question is how much immigration a nation’s politics can handle.  Fortunately we are not at the “five nights of riots” margin in the United States, but Ross still raises the key question, namely “the kind of social solidarity that mass immigration often tends to undercut…” and the role of that solidarity in supporting a free society.  The key question is how many low-skilled immigrants a nation can take in and still keep a good politics.

6. Location-aware radio.

*The Great Divide: Nature and Human Nature in the Old World and the New*

That is the new book by the very active and very smart Peter Watson, due out soon but I bought a copy in the UK.

Why has the New World been so different from the Old World?  What a splendid seventeenth and eighteenth century question.  Imagine Jared Diamond — and with comparable scope — yet with shamans, peyote, and El Niño playing a role in the argument.  I recommend it to everyone who can keep in mind how speculative the argument will be.

If we had to sum up what has gone before and describe in a few words the main features shaping early life in the Old World, those words would be: the weakening monsoon, cereals (grain), domesticated mammals and pastoralism, the plough and the traction complex, riding, megaliths, milk, alcohol.  One way to highlight the differences between the two worlds is to perform the same summing-up exercise for the Americas…For the New World the crucial and equivalent words would be: El Niño, volcanoes, earthquakes, maize (corn), the potato, hallucinogens, tobacco, chocolate, rubber, the jaguar, and the bison.

Unlike Diamond, this book assigns ideology a central role in the story.  Europe and the Middle East generate the ideas of the shepherd, the New World the ideas of the shaman, some of which may have been picked up or carried from the Chukchi of Siberia.  Perhaps my favorite point in the book is the observation that the Old World had a greater diversity of ideologies.

Watson touches on many Hansonian themes about the differences between gatherers and foragers.  Here is a Guardian review.  Here is an Independent review.  Here is a Matthew Price review.

This is an easy book to criticize, see the reviews or for instance take this passage:

…artwork was not developed [in the early stages of the New World] because there was no need to establish either dedicated territories or tribal identities.  And/or food was in such plentiful supply that they had no need to keep records that assisted their memory of animal habits.

One really does have to take this book as a scenario, not as science.  It is nonetheless interesting if used with care.

The Volume Clock

That is the title of a new paper by David Easley, Marcos M. Lopez de Prado, and Maureen O’Hara:

Abstract:
Over the last two centuries, technological advantages have allowed some traders to be faster than others. We argue that, contrary to popular perception, speed is not the defining characteristic that sets High Frequency Trading (HFT) apart. HFT is the natural evolution of a new trading paradigm that is characterized by strategic decisions made in a volume-clock metric. Even if the speed advantage disappears, HFT will evolve to continue exploiting Low Frequency Trading’s (LFT) structural weaknesses. However, LFT practitioners are not defenseless against HFT players, and we offer options that can help them survive and adapt to this new environment.

The paper has many interesting bits, such as this:

Databases with trillions of observations are now commonplace in financial firms. Machine learning methods, such as Nearest Neighbor or Multivariate Embedding algorithms search for patterns within a library of recorded events. This ability to process and learn from what is known as “big data” only reinforces the advantages of HFT’s “event-time” paradigm, very much like how “Deep Blue” could assign probabilities to Kasparov’s next 20 moves, based on hundreds of thousands of past games (or more recently, why Watson could outplay his Jeopardy opponents).

The upshot is that speed makes HFTs more effective, but slowing them down won’t change their basic behavior: Strategic sequential trading in event time.

One message of the paper is that sequential strategic behavior will occur at any speed.  I liked this sentence:

As we have seen, HFT algos can easily detect when there is a human in the trading room, and take advantage.

And the ending bit is this:

There is a natural balance between HFTs and LFTs. Just as in nature the number of predators is limited by the available prey, the number of HFTs is constrained by the available LFT flows. Rather than seeking “endangered species” status for LFTs (by virtue of legislative action like a Tobin tax or speed limit), it seems more efficient and less intrusive to starve some HFTs by making LFTs smarter. Carrier pigeons or dedicated fiber optic cable notwithstanding, the market still operates to provide liquidity and price discovery – only now it does it very quickly and strategically.

Relative to baseline forecasts, ACA and otherwise

Ruritania is fighting a war, and the status quo setting is that 90,000 lives will be lost each year.  General Blythe comes up with a plan that increases the chance of winning the war, but is likely to cost 120,000 lives a year.  He claims his plan costs only 30,000 lives a year, relative to baseline.  General Smythe has a war plan which on net costs only 80,000 lives a year, so he argues that his plan saves 10,000 lives a year.

In comparative terms these claims are not incorrect, and there are obvious reasons why bureaucracies should draw up such estimates.  Yet an anti-war group, SDS, argues that the real cost of the war is 90,000 lives each year, and that the one alternative plan costs 120,000 lives a year and the other 80,000 lives a year.  If you are rethinking the entire war, the SDS estimates are relevant.

If we are going to keep at the war no matter what, the estimates of the Generals may be more useful.  In the meantime, the generals get upset that SDS is stepping out of the framework of policy discourse and refusing to offer or accept numbers “relative to baseline.”  Discourse fractures and names are flung.

To translate that into 2012, the “war” is the joint view — extremely common in America — that a) tax revenues are on an acceptable track, and b) we should spend more and more on health care each year at high rates, including in per capita terms.

If you think that dual project is sustainable, you may be relatively interested in estimates relative to baseline.  If, like me, you think that project is like a failed and failing war, a success “relative to baseline” won’t much impress you.  In fact it may scare you all the more to hear about success relative to baseline, as that can be taken as a signal that there is no really good plan behind the scenes.  Here are a few factors which could radically upset current mainstream baselines:

1. Rates of growth stay in the range of 1 to 1.5 percent, see the work of Stock and Watson, top macro econometricians.  Try redoing budget projections with those numbers.

2. Real rates of growth are higher than that, but they take the form of non-taxable pecuniary benefits.

3. Growth rates are acceptable, but more and more of economic growth is captured by private capital, which is difficult to tax for either mobility or political economy reasons.

4. The United States may need to fight a major war, or prepare to do so.  (I do favor cutting the defense budget now, but we can’t be sure that cuts can last.)

5. The political economy of revenue hikes and/or spending cuts becomes or remains intractable.  Buchanan and Wagner have been stressing this point for decades.  A decision to borrow forty cents of a dollar spent, right now, may end up as more or less permanent, at least for as long as markets allow.  Ezra’s excellent posts about how far “right” the Democratic Party has moved on taxes are along these lines.

6. Another major recession may arrive, perhaps from abroad.

7. Life expectancy goes up a few more years than we had thought, yet productivity for the elderly doesn’t rise in lockstep.  You don’t have to think of that as “bad news,” but it still would be a major fiscal problem.

Maybe none of those are modal forecasts, but add them all up and I say the probability of being way off baseline is greater than 0.5, and possibly more than one of those problems will kick in.  In expected value terms, the costs of those possible fiscal scenarios loom very, very large (yet suddenly the modern liberal desire to think in terms of “worst case scenarios” has diminished).

Imagine people sitting around in Spain, in 2006, debating various scenarios relative to the “baseline budget.”  Maybe that’s America today, though we do not face the same particular problems or timing that Spain did.

Now enter Chuck Blahous, who wrote an article charging that ACA is likely to prove very costly, and that we are spending our cost savings on Medicare and other programs in advance, when we in fact need those cost savings to restore fiscal sanity.  You will find responses here from Ezra Klein, Kevin Drum, Paul Krugman and there were many others, accessible through Google, Blahous counters here.

I have reread the Blahous article carefully, with an eye toward judging whether Blahous is simply playing “baseline games,” as some of the critics allege.  I do not see that he is.  He stresses that he is making economic, practical, causal, and public choice arguments, and that those trump baseline games in importance.  He is trying to get us out of an obsessive focus on the baseline game, not play it in some misleading way.

To be sure, my view, or at least my emphasis, is different from that of Blahous in at least two ways.  First, he is more worried about the political economy of Congressional responses when the trust funds are exhausted, whereas I am more worried about the list immediately above (that said, Blahous very clearly does discuss several other major concerns besides double-counting and he may well agree with these broader worries too).  Second, my inclination is to focus on the entire budget, as a unified entity, and not so much stand-alone ACA (or Social Security, as in other debates) per se.  I suspect Blahous may well agree with me, but as a more active budget analyst/specialist than I am he is forced into debates on stand-alone analyses, whereas I can play the role of aloof blogger.  In any case, “fixing” this difference of emphasis would strengthen rather than weaken the overall thrust of his argument.

At the end of the day, I agree with the basic point of Blahous, which is that ACA, should it stand, is spending potentially available budget savings which we will need for other purposes.  I also would argue, though I do not have space to do so here, that this has become standard practice in American politics, with Democrats too.

Here are some choice words from Steven Rattner, who worked at Treasury under Obama:

Given that context, the government’s accounting practice — counting $748 billion of cost savings and $259 billion of revenue increases toward both Medicare and the cost of the Obama plan — is particularly troubling. Moreover, this problem is largely hidden from public view.

Under Washington’s delusional rules, budget crunchers in both the White House and Congress credit this $1 trillion twice: once in calculating that the care law will generate more revenues than costs, and again in concluding that the Obama plan will chip away at the Medicare problem.

You can argue that Rattner isn’t quite correctly describing CBO procedures in his piece, but on the economic and causal arguments he, like Blahous, is essentially correct.

At the end of the day, economic models do not use a “relative to baseline” framework.  The effect of “Delta G,” “Delta T,” or any other variable, depends on realized and expected values of that variable and others, and not that the size of that variable relative to what other people are proposing.  As I mentioned above, “relative to baseline” does have legitimate bureaucratic and accounting uses.  But we should not let it blind us to a) the divorce of that mode of reasoning from traditional economics, b) the likely unsustainability of our current fiscal path, and c) that the actual reality of ACA and other policies that we are spending “cost savings” as soon as we create them or even sooner.

Addendum: I am happy to call out the various Ryan budget proposals as unworkable fiscal disasters, most of all on the revenue side.  I also refused to endorse the 43 Bush “tax cuts” at the time, though I was sent one of those pieces of paper to sign.  No point in throwing the “Team Republican” charge, which in any case disrupts discourse rather than advancing it.

What Export-Oriented America Means

That is the title of my new 4000 or so word essay for The American Interest.  Excerpt:

At least three forces are likely to combine to make the United States an [increasing] export powerhouse.

First, artificial intelligence and computing power are the future, or even the present, for much of manufacturing. It’s not just the robots; look at the hundreds of computers and software-driven devices embedded in a new car. Factory floors these days are nearly empty of people because software-driven machines are doing most of the work. The factory has been reinvented as a quiet place. There is now a joke that “a modern textile mill employs only a man and a dog—the man to feed the dog, and the dog to keep the man away from the machines.”

The next steps in the artificial intelligence revolution, as manifested most publicly through systems like Deep Blue, Watson and Siri, will revolutionize production in one sector after another. Computing power solves more problems each year, including manufacturing problems.

It’s not just that Silicon Valley and the Pentagon and our universities give the United States a big edge with smart machines. The subtler point is this: The more the world relies on smart machines, the more domestic wage rates become irrelevant for export prowess.

…The second force behind export growth will be the recent discoveries of very large shale oil and natural gas deposits in the United States…

That brings us to the third reason why America is likely to return as a dominant export power: demand from the rapidly developing countries, and not just or even mainly demand for fossil fuel. As the developing world becomes wealthier, demand for American exports will grow. (Mexico, which is already geared to a U.S.-dominated global economy, is likely to be another big winner, but that is a story for another day.)

In the early stages of growth in developing nations, importers buy timber, copper, nickel and resources linked to construction and infrastructure development. Those have not been U.S. export specialties, and so a lot of the gains from these countries’ growth so far have gone to Canada, Australia and Chile. Usually American outputs are geared toward wealthier consumers and higher-quality outputs, which is what you would expect from the world’s wealthiest and most technologically advanced home market. To put it simply, the closer other nations come to our economic level, the more they will want to buy our stuff.

That’s just the introduction.  The rest of the essay considers: “how will this shape American foreign policy, jobs, education, politics and poverty?”  For instance:

Some of the new technological and export-related breakthroughs will consist of making education and health care more affordable, often through software and smart machines that bypass the current credentialized control of those fields. Imagine getting an online medical diagnosis from a smart machine like IBM’s Watson, or learning mathematics from an online MITx program or one of its successors. The American poor and lower middle class will have considerably greater opportunities, at least if they are savvy with information technology and disciplined enough to take advantage of these new free or cheaper goods. Of course, this will not come close to helping everybody. These internet tools reward the self-motivated, who will be disproportionately well educated, even if their parents lack higher education, wealth and connections. Many of the rest will still fall by the wayside.

Do read the whole thing.  You can think of it as some current thoughts on what it would look like to climb out of The Great Stagnation.

Addendum: Reihan adds excellent comments.

Sherlock Holmes v. Sherlock

Sherlock Holmes: A Game of Shadows is ok so long as you are expecting a comic book adventure along the lines of Captain America or Iron Man (natch) and not a detective-mystery ala Sherlock Holmes. A smart character requires smart writers and in this movie the producers saved the money for special effects.

In contrast, the British TV series Sherlock is a must see. Sherlock reboots Holmes into our world. Yet despite advancing in time some 130 years when Sherlock first meets Watson he says, exactly as in the original, “You have been in Afghanistan, I perceive.” A shiver ran down my spine.

Sherlock is fast-paced but clever. It’s written by two Doctor Who vets who invest Holmes with wit, originality and intellect, rather than the quasi-magical powers found in the aforementioned movie. The chemistry between Holmes and Watson is  clear – one understands in this version what is lacking in many others, these two need each other.

The first season has only 3, 90 minute, episodes but a second season just ran in Britain and I expect it will soon be available in the U.S.

Paging Dr. Siri

In 2004 I wrote In Praise of Impersonal Medicine arguing:

I have nothing against my physician but I would prefer to be diagnosed by a computer.  A typical physician spends most of the day playing twenty questions. Where does it hurt?  Do you have a cough?  How high is the patient’s blood pressure?  But an expert system can play twenty questions better than most people.  An expert system can use the best knowledge in the field, it can stay current with the journals, and it never forgets.

and in 2006 I noted:

The practice of modern medicine is surprisingly primitive…My credit card company knows far more about my shopping history than my physician knows about my medical history.

I now believe that we are on the cusp of major changes to medicine. The thousand dollar genome sequence is less than a year away, Ford has just developed a car seat that can monitor your health, many people are already using wrist monitors to measure heart and sleep patterns. All of this data will soon be combined with massive databases to offer predictive and prescriptive health diagnosis.

In Do We Need Doctors or Algorithms the venture capitalist Vinod Khosla expands:

IBM’s Watson computer… is now being applied to medical diagnosis after handling imprecise and vague tasks like winning at Jeopardy, which experts a few years ago would have said could not be done. “Computers cannot match the judgment of humans on these kinds of tasks!” And with enough data, medical diagnosis or 90% of it is an easier task than Jeopardy.

Already Kaiser Permanent already has 10 million real-time medical records with details of 30,000,000 e-visits last year with caregivers and computer modeling of key diseases per individual that data scientists would love to get their hand on. Already, according to IDC 14% of the US population is using their phones for medical help and 200 million health and fitness related mobile applications have been downloaded according to pyramid research. Fun stuff, though early. They are probably two generations away from systems that are actually useful.

…But I doubt very much if within 10-15 years (given continued investment and innovation and keeping the AMA from quashing such efforts politically) I won’t be able to ask Siri’s great great grandchild (Version 9.0?) for an opinion far more accurate than the one I get today from the average physician. Instead of asking Siri 9.0, “I feel like sushi” or “where can I dispose a body” (try it…it’s fairly accurate!) and with your iPhone X or Android Y with all the power of IBM’s current Watson computer in the mobile phone and an even more powerful “Nvidia times 10-100” server which will cost far less than med school with terabytes or petabytes of data on hundreds of millions (billions?) of patients, including their complete genomics and proteomics (each sample costing about the same as a typical blood test).