First They Came For The Attorneys: JPMorgan Automates Document Review, Saving 360,000 Hours per Year

From Bloomberg: 

JPMorgan Software Does in Seconds What Took Lawyers 360,000 Hours

• New software does in seconds what took staff 360,000 hours
• Bank seeking to streamline systems, avoid redundancies

At JPMorgan Chase & Co., a learning machine is parsing financial deals that once kept legal teams busy for thousands of hours.

The program, called COIN, for Contract Intelligence, does the mind-numbing job of interpreting commercial-loan agreements that, until the project went online in June, consumed 360,000 hours of work each year by lawyers and loan officers. The software reviews documents in seconds, is less error-prone and never asks for vacation.

While the financial industry has long touted its technological innovations, a new era of automation is now in overdrive as cheap computing power converges with fears of losing customers to startups. Made possible by investments in machine learning and a new private cloud network, COIN is just the start for the biggest U.S. bank. The firm recently set up technology hubs for teams specializing in big data, robotics and cloud infrastructure to find new sources of revenue, while reducing expenses and risks.

The push to automate mundane tasks and create new tools for bankers and clients -- a growing part of the firm’s $9.6 billion technology budget -- is a core theme as the company hosts its annual investor day on Tuesday.

Behind the strategy, overseen by Chief Operating Operating Officer Matt Zames and Chief Information Officer Dana Deasy, is an undercurrent of anxiety: Though JPMorgan emerged from the financial crisis as one of few big winners, its dominance is at risk unless it aggressively pursues new technologies, according to interviews with a half-dozen bank executives.

Redundant Software
That was the message Zames had for Deasy when he joined the firm from BP Plc in late 2013. The New York-based bank’s internal systems, an amalgam from decades of mergers, had too many redundant software programs that didn’t work together seamlessly.

“Matt said, ‘Remember one thing above all else: We absolutely need to be the leaders in technology across financial services,’” Deasy said last week in an interview. “Everything we’ve done from that day forward stems from that meeting.”

After visiting companies including Apple Inc. and Facebook Inc. three years ago to understand how their developers worked, the bank set out to create its own computing cloud called Gaia that went online last year. Machine learning and big-data efforts now reside on the private platform, which effectively has limitless capacity to support their thirst for processing power. The system already is helping the bank automate some coding activities and making its 20,000 developers more productive, saving money, Zames said. When needed, the firm can also tap into outside cloud services from Amazon.com Inc., Microsoft Corp. and International Business Machines Corp....MUCH MORE

"Mike Mayo Doesn’t Need A Job To F@ck With JPMorgan"

From DealBreaker:

True artists are possessed by a potent need to express themselves, and that yearning is exponentially stronger for the great ones who will do whatever it takes to put their art out into the world. 

If you’d confiscated van Gogh’s paintbrushes, he would have scrawled wavy landscapes on the wall with his own blood. If you’d taken away Mozart’s piano, he would have banged on pots to create a melody. If you’d banned Shakespeare from the theater, he would have staged his plays in the fields. 

So when you lay off super bank analyst Mike Mayo don’t think for one minute that he will not find a way to troll the living shit out of JPMorgan on Investor Day… 

Mike Mayo, the bank analyst who sparred with JPMorgan Chase & Co. executives at prior Investor Day presentations, showed up at the lender’s 2017 event less than 24 hours after his former employer, CLSA Ltd., shut down its U.S. equity-research operation.“Mike Mayo, free agent analyst,” he said when introducing himself Tuesday, before asking a question to JPMorgan Chief Financial Officer Marianne Lake about profitability from deposits....

...MORE

Factors: The Problem With Small Cap Stocks (the effect probably isn't real)

I hate to argue with Fama-French, hate it hate it, hate it.
That said, I'm not sure it isn't just an artifact of the survivorship bias explained below.
Momentum is real though, for now,

From Dual Momentum:

Factor Zoo or Unicorn Ranch?

According to Morningstar, as of June 2016, the assets in smart beta exchange traded products totaled $490 billion. BlackRock forecasts smart beta using size, value, quality, momentum, and low-volatility will reach $1 trillion by 2020 and $2.4 trillion by 2025. This annual growth rate of 19% is double the growth rate of the entire ETF market. Are factors the cure-all for our investment needs? Or are they like “active management” that everyone wanted to have instead of passive index funds in the 1970s?

No one then wanted to be just average. This ironically gave many investors below average returns as they used the same information to compete against one another.  Superior performance was usually due more to luck than to skill. But Bill McNabb, CEO of Vanguard, points out that passive index funds have been in the top quartile of long-term performance.

Factor-based investors and advisors now think they have an advantage. They base this belief on the results of theoretical asset pricing models, many of which have failed empirically.

Asset pricing models look at long-term long/short returns without taking into account the price impact of trading. Factors that looked good on paper may be lacking in robustness, pervasiveness, persistence, or intuitiveness. Let us see.   

Does Size Matter?
The small cap size premium was the first identified factor. Banz wrote about it in 1981. His results were influenced by extreme outliers from the 1930s.

Looking at more recent history, the oldest small cap index is the Russell 2000. It started in January 1979. Here is the Russell 2000 annual return and volatility over the life of the index compared to the S&P 500 index.

Russell 2000 underperformed the S&P 500 by 1.3% annually and had a substantially higher standard deviation. The Russell 2000 thus  underperformed on both a risk-adjusted and non-risk adjusted basis.{1]

Here is a chart comparing the Sharpe ratios of all small and large cap stocks over a longer period of time. Small cap stocks usually failed to show significantly higher risk-adjusted profits than large cap stocks.  

In the table below long-only small caps slightly outperformed large caps globally since 1982. But small caps have underperformed large caps in the U.S. since 1926. Where is the outperformance that Banz talked about?...

...MORE

A Phillips (of the curve, not the company) View of the Eurozone

With an update of the Phillips hydraulic model after the jump.

From FT Alphaville:

A ‘Phillips’ view of the euro

This guest post is from Michael O’Sullivan, chief investment officer for Europe and emerging markets at Credit Suisse Wealth Management…
__________
Well before he was celebrated for his work on the link between unemployment and inflation, Bill Phillips built an extraordinary machine that pumped coloured water through glass vessels in order to demonstrate how money flows around an economic system. Levers in the machine permitted users to simulate the effect on the system of fiscal policy changes and such was the intuitive appeal of the machine that major universities like Harvard and Oxford ordered their own versions.

In today’s algorithmic, QE driven markets such a machine might seem well out of place, but now that the Greek situation has reared its head, again, and with some politicians in Europe campaigning on the basis of euro exit, policymakers in Brussels could do a lot worse than build their own version of Phillips’ machine. Indeed, such a contraption might aid a much needed period of introspection into the workings of the euro and may shine light on the areas missed by the rather tame 2015 Five Presidents Report.

In the spirit of Phillips’ machine, picture the euro-zone as a system where liquidity passes through nineteen different vessels, at different speeds and causing very disparate pressures on each of them. A few like Greece, are too weak economically and politically to withstand these pressures.

More broadly, it is now clear that in the absence of counter balancing mechanisms or safety valves, a common monetary policy can have a different impact on say, the Portuguese economy as compared to the Finnish one. This much was clear in the early 2000’s when a monetary policy that was set for a recovering German economy granted negative real interest rates to Ireland and Spain, where banks and consumers then deployed cheap cash with vigour.

In this respect, the engineers of the euro need to figure out how to accommodate a single monetary policy within different economies. The Commission should consider the inveterate Greek crisis as a warning to resist the urge to further expand euro membership and smother its adherents with fiscal uniformity. Instead they must cleverly redevelop the way it is engineered so that it is harmonious within its existing member economies and transmission mechanisms within thin these.

There are at least ways in which this can be done, the most important being fiscal policy. The principal suggestion here is to revise the restrictive set of fiscal rules to give more emphasis to a framework where national governments have fiscal flexibility. Importantly, they would be bound by the advice of independent fiscal councils and through restrictions on debt issuance, to run fiscal policies that are on balance countercyclical to euro-zone monetary policy and that are economically productive rather than political in their aim. Using fiscal policy to complement monetary policy would help to ensure the euro-zone’s economies, especially the smaller ones, do not become ‘too hot’ or ‘too cold’ in the fashion of Bill Clinton’s ‘Goldilocks’ economy.

This would also demand plenty of policy innovation at the macro-prudential level and euro-zone countries like Ireland could fine tune their structural recovery in this way. Doing so in a structured way, rather than say populist ‘moral suasion’ makes more sense and would permit greater policy engagement in how the moving parts in a small open economy work together. Ideally, a body like the national central bank should oversee the transmission of lending to households, in a way not unlike it did before the euro. Additionally, instead of harmonising fiscal rules, the EU may want to harmonise the processes required to set up a new business, or create a quicker pan-European approach to this.

There is a second engineering challenge facing the euro version of the Phillips machine, which is that very different levels and forms of indebtedness mean that a common monetary policy flows in distinct paths across euro-zone economies, or in some cases doesn’t flow at all. Here the EU might look to China where the authorities have ordained a program of financial restructuring that privatises much of the debt held by local and national authorities....MORE

Previously:
November 2012
Like Phillips, Irving Fisher Was a Plumber: Hydraulic Models of the Economy
March 2011
The computer model that once explained the British economy (and the new one that explains the world)

...Schematic diagram of the Phillips machine. ( Click to enlarge.)

And here's the latest incarnation:

Genius squared.

The second schematic is from a post on GE's Mark I nuclear reactor at ZeroHedge!

"Cycles of Insanity and Creativity Within Contemplative Neural Systems"

An oldie but goodie.
Well...not that old, last August. But good.
Original post:

Oh great.
Now we're making machines that exhibit psychopathologies.

From Stephen Thaler, PhD via his Linked in page, Aug. 5 2016:

After more than 40 years of observing inventive artificial neural systems at work (i.e., Creativity Machines), I have found that they are susceptible to the very same cognitive pathologies as the brain. In fact, as such forms of synthetic psychology are pushed toward higher levels of creativity, the more likely they are to exhibit the classic psychopathologies, such as schizophrenia, manic-depression, and various attention disorders.

Finally getting up the nerve to solo publish within a culture well outside physics and computer science, I took my chances with Elsevier’s journal Medical Hypotheses, and was pleasantly surprised. After all, neurobiology obeys physics. So, if the biologists consider this the proverbial “spherical chicken in vacuum” then they should reconsider its power in providing a streamlined, bottom-up perspective on both the mechanics of seminal cognition and what can go wrong with that process. True, insanity and creativity have been known to positively correlate with one another for centuries, but I am offering the nuts-and-bolts model, using amazingly simple mathematical principles.

If interested in exploring further, go to http://www.medical-hypotheses.com/article/S0306-9877(16)30363-2/abstract.

For free access to the article over the next 40 days, go to http://authors.elsevier.com/a/1TSHC15pGbnziG.

Thaler is an interesting guy although he is definitely going his own way in AI research.
From Next Big Future:

Artificial intelligence researchers claims sentient creativity machines will be made within 5 years

The AI researcher Dr. Stephen Thaler has given an interview recently in which he claims that his AI research will lead to sentient, cognizant "creativity machines" within 5 years.

The research continues to accelerate.

Consciousness appears to be more like an intensive rather than extensive property/behavior of the brain. It’s sort of like the gas law equation, PV= nRT, with P and T being intensive and n and V extensive. So, consciousness is intensive, but we as humans deny simpler forms of consciousness, while fearing the scaled up version attainable via machine intelligence.

Imagination Engines, Inc. was founded upon key scientific and engineering breakthroughs in the area of artificial neural networks by Dr. Stephen Thaler.

An Imagination Engine is a trained artificial neural network that is stimulated to generate new ideas and plans of action through a very amazing effect that is an outgrowth of scientific experiments conducted in 1975 by our founder, Dr. Stephen Thaler. In these initial experiments, neural networks were trained upon a collection of patterns representing some conceptual space (i.e., examples of either music, literature, or known chemical compounds), and then the networks were internally 'tickled' by randomly varying the connection weights joining neurons. Astonishingly...MORE

For the naysayers the practical results were good enough to land some Department of Defense and NIST funding.
Creative crazies, sounds about right.

Series 1 Episode 09 – The Cooper-Hofstadter Polarization (2008)

Bank of America Merrill Lynch on the Agricultural Economy, 2017--Meh

From ZeroHedge:

BofAML Explains Why The Ag Economy Isn't Likely To Get Much Better In 2017

The fact that farm incomes have come under increasing pressure over the past couple of years should come as little surprise to our readers (for those who missed our latest update, see: "Midwest Farm Bubble Continues Collapse As Farm Incomes Expected To Crash In 2017").  Unfortunately, at least according to Bank of America's Global Ag Chemical team led by Steve Byrne, farmers shouldn't expect a reprieve any time in the near future.

As BAML points out, the grain commodity farmers of the U.S. are locked in a vicious cycle, the result of which is a perpetually oversupplied market.  To summarize the key takeaways, farmers continue to plant so long as cash profits are positive (because depreciation isn't a real cost and who cares about returns on capital anyway...silly finance people) while yield growth continues to outpace demand growth which leaves markets perpetually oversupplied and commodity prices well below what would be required to provide a normalized profit level for farmers. 

Meanwhile, since farmers seem to be incapable of unilaterally reducing supply, an external supply shock (e.g. a weather-related event) seems to be the only hope of the industry ever normalizing again.

With that, here is a little more detail on the vicious ag cycle per BAML...
Yield growth per acre continues to average 1-2% per annum...

Yields continue to improve with no sign of abatement as seed technology improves and farmers utilize better information technology (precision ag) to gain better understanding of acreage and maximize yield potential. While weather can disrupt yields year-to-year, directionally yields have improved at a 1-2% CAGR for corn, soy and wheat since 2000. In our view, this will continue to place deflationary pressure on crop prices longer-term, particularly given the extent to which global yields trail yields in more developed ag economies.

 

...which continues to drive new record highs in production despite an already weak pricing environment.

Global corn production is similarly heading for a new record high in 2016/17, up 7% YoY and driven mostly by an almost equally big rise in yields. The US 2016/17 crop that was just harvested looks especially strong. Concerns over whether ear filling was impeded by the hot and dry summer weather are now fading as the harvest is done and the USDA revised up its yield estimate by 1% to 11.01mt/ha in November. Meanwhile, in LatAm farmers are currently planting for the 2016/17 harvest and production looks even stronger, up 26% on presumed yield normalization and exacerbated by a 7% increase in acreage.

 

Meanwhile, global corn demand is expected to recover somewhat in 2016/2017 but no where near the expected 7% supply increase.

Global corn demand growth slowed to just 2% per annum in the past two years, due to a drop in global pork production. Corn is the staple diet of the word’s more than 1bn pigs. The decline in pork production was mainly caused by an environmental crackdown in the Chinese farming sector, and the country’s pork production fell by 3% in 2015 and another 5% likely in 2016.

Then in March 2016, China ended its domestic corn price floor, giving relief to pig farmers, and corn demand started picking up again. Corn demand from pig production will continue to rise structurally in the years to come on the ramp-up of new modern mega farms in Northern China. Overall global corn demand can recover to 3% growth this market year (2016/17) and hold up at 2-3% growth annually in the years to come, in our view. However, we have started to see signs of slowing feed demand as elevated corn prices have led to substitution to other feeds, in some instances. Global feed demand levels will be key in determining the aggregate corn demand picture.

 ...MUCH MORE

"Softbank’s Son: Why Do I Spend So Much Money? The Singularity Is Real"

From Barron's Tech Trader Daily:

Monday morning at the Mobile World Congress trade show in Barcelona, SoftBank (9984JP) chairman Masayoshi Son gave a keynote to answer the question “Why do I spend so much money?”

Son, who sounds like he’s been taking campaign cues from Donald Trump, emphasized the huge scale of his efforts. His firm’s investment fund, called the “Vision Fund,” has $100 billion committed to it, which is more than the global total of venture capital money of $65 billion. And he spent $32 billion to acquire ARM Holdings, which makes chips that go into smartphones, cars, and much more.

Why all the spending? Son asked the audience if they knew about “The Singularity,” the principle that machine intelligence will overtake human intelligence. Son believes it’s real — not just that, he knows when it’s happening.

“I calculated 20 years ago that it would be 2018” when the cross-over happens, he told the packed auditorium. “I recently rechecked the calculation and it was still 2018. If it’s off by a year or two, I don’t care.”

“I believe it’s coming, in the next thirty years, so that’s why I’m in a hurry,” he said, “to bring the cash.”

Son went through an explanation of human IQ and machine IQ. Human IQ is on average 100. He joked that probably his audience was a bit above that. Then he said geniuses such as Einstein have 200 IQs. Then he said that machine intelligence will have a 10,000 IQ.

Humans have about 30 billion neurons, or binary connections, he said. The billions of transistors inside chips would seem to be about at the point of overtaking the complexity of those 30 billion binary connections in the human brain, if his calculations are right.

What happens is that ARM will ship all the chips for that, he said confidently.

“They run 99% of smartphones,” he pointed out. “ARM will ship a trillion IoT [Internet of Things] chips in the next decade,” he said. So, Son, who controls Sprint (S), said, “we will have a trillion customers” to connect all that. “Okay?”

Okay. He observed that in a few years’ time, the average pair of sneakers will have more chip IQ than the average human....MUCH MORE

NVIDIA: In Case You Missed It, Citron Research (Andrew Left) Says They Covered the NVDA Short

Left had said they were targeting $90, it didn't get there
Up $3.24 (3.19%) at $104.70.

Investor's Business Daily, Fri. Feb. 24:

Graphics chipmaker Nvidia (NVDA) saw its shares tumble for the second straight day on Friday, but reassuring comments from Wall Street analysts helped the stock recover some lost ground.

Nvidia stock dropped as much as 4.8% to 95.70 in morning trading on the stock market today. But shares clawed their way to a gain of 1% to 101.46 at the close.

On Thursday, Nvidia plummeted 9.3% to 100.49 after BMO Capital Markets and Nomura cut their ratings and price targets on the stock, saying it was overvalued. The stock sliced through its 50-day moving average, a key support level.

On Friday, Mizuho Securities and UBS reiterated this buy ratings on Nvidia, saying the pullback had created a buying opportunity.

IBD'S TAKE: Nvidia stock has shown signs of hitting a climax top. It touched an all-time high of 120.92 on Feb. 7, and at that point had been up 358% in the past year.

"We would be buyers with the recent 15% pullback in NVDA post earnings," Mizuho analyst Vijay Rakesh said in a report Friday. "Gaming and Deep Learning will continue to be long-term sustainable trends as new (game) titles get released and enterprise transforms from agility and speed to a smarter, efficient, predictive enterprise."

Rakesh maintained his price target of 130 on Nvidia.
UBS analyst Stephen Chin kept his 12-month price target of 132.

"We keep a buy rating on Nvidia as we expect data center sales to more than double over the next couple years to $2 billion-plus and a 15% growth CAGR in the core gaming GPU business," Chin said in a report.

Short-seller Citron Research announced Friday that it closed out its short position in Nvidia and had rotated into betting against car-sensor tech firm Mobileye (MBLY). 

Nvidia is one of nine chip industry-related stocks on the IBD 50 list of top-performing growth stocks. Others include Broadcom (AVGO), InterDigital (IDCC) and Monolithic Power Systems (MPWR)....

Updating our $NVDA call....switching focus to $MBLY Ridiculous comparison We expect $MBLY to trade short term $35. Insiders tell the story pic.twitter.com/OwuC9xGRSu

— Citron Research (@CitronResearch) February 24, 2017

"...technological unemployment will be worse than you think".

From Daniel Susskind:

A MODEL OF TECHNOLOGICAL UNEMPLOYMENT, OXFORD UNIVERSITY Discussion paper, NO. 819, February 2017 

DOWNLOAD: VERSION 22 FEBRUARY 2017

In the past 15 years a new area of the economics literature has emerged to explore the consequences of technological change on the labour market. This is the ‘task-based’ literature. The account that emerges is optimistic about the prospects for labour in the 21st century. The central argument of this paper is that this particular optimism is unjustified.

In this paper I try to make two contributions. The first is to show that the literature’s current conception of how the latest machines operate and the capabilities that this implies -- what is known as the ‘ALM hypothesis’ -- is incorrect. Put simply, the ALM hypothesis implies that while machines can perform ‘routine’ tasks, they cannot perform ‘non-routine’ tasks. Tasks are ‘routine’ when human beings find it straightforward to explain how they perform them (rather than because they are boring or dull). The ALM hypothesis argues that because human beings cannot easily articulate the rules they follow when performing ‘non-routine’ tasks, it is therefore hard to write a set of rules for a machine to follow to perform these tasks. As a result, it is claimed that these ‘non-routine’ tasks cannot readily be automated.

The problem is that the ALM hypothesis is dated. It assumes that the only way to automate a task is to understand, articulate, and replicate the way a human being performs that task. But recent technological advances in processing power, data retrieval and storage capabilities, and algorithm design, means that this constraint no longer holds. It is no longer necessary to replicate human thinking and reasoning processes in order to outperform human beings....MORE

Headline from and HT to Marginal Revolution

"Warped sense of humour could be ‘sign of impending dementia’"

Following last week's "Long-winded speech could be early sign of Alzheimer's disease, says study" a "friend" sent this along.
I can't catch a freaking break this month.

From the Independent, November 2015:

An increasingly dark or twisted sense of humour could be an early warning sign of impending dementia, according to experts.

The results have appeared in the Journal of Alzheimer’s Disease, which was carried out by University College London.

Dr Camilla Clark recruited 48 patients with frontotemporal dementia from their dementia clinic at University College London. The patient's friends and family were asked to rate their friend or relative's enjoyment of different kinds of comedy.

These included slapstick comedy such as Mr Bean, satirical comedy such as Yes, Minister or absurdist comedy such as Monty Python and examples of inappropriate humour.  Dr Clark found that the dementia patients preferred slapstick humour to satirical, when compared to 21 healthy people of a similar age....MORE

The "friend" courteously included the PubMed citation at the U.S. National Institutes of Health:
Altered sense of humor in dementia.

Architecture: "How to Detect A Brutalist Building"

I'm not quite sure how this bit of genius ended up in the link-vault.



I believe this fellow is the creator although neither of the sources (reddit r/brutalism and 20 Bedford Way have a link)

And while I personally don't care for the style, to each his/her/ze's own. On the other hand I was astounded by this news last November:

Follow-Up On Last Night's Impressionist-Modern Sale At Sotheby’s (BID)

Apparently the market for Italian Fascist/brutalist macho isn't as strong as one might think.

Following up on "Attention Collectors: A Potential Mispricing In the Art Market":

From Art Market Monitor, Nov. 1:

The Baffling But Tireless Tamara de Lempicka Market

Bloomberg’s James Tarmy wonders why Tamara de Lempicka’s portrait of a man, Guido Sommi, is priced so much lower than her private market?...

It didn't sell even though Guido was her favorite model/lover/fascist.
Hey, it was the '20's.

Earlier:
Indicators: "Led by $54.5 M. Munch, Muted Impressionist-Modern Sale at Sotheby’s Nets $157.7 M., Down 48 Percent From Last Year

"Electric-car makers on battery alert as hedge funds stockpile cobalt"

Following up on last May's "Why the CIA Reads The Financial Times (and you should too) Tesla and Cobalt".
From the Financial Times via the Irish Times, Feb. 23:

Speculators swell appetite for metal as price of scarce material up by 50% 

Suppliers to Tesla and other electric-car makers are scrambling to secure shipments of the key battery material cobalt after a group of hedge funds amassed a large stockpile of the scarce metal.

In a bold wager on higher prices, half a dozen funds, including Switzerland-based Pala Investments and China’s Shanghai Chaos, have purchased and stored an estimated 6,000 tonnes of cobalt, worth as much as $280 million, according to the investors, traders and analysts.

The stockpile is equivalent to 17 per cent of last year’s production of the metal. Increasing use of batteries with chemical forms of the metal by Chinese electric-car makers, alongside ambitious plans by the likes of Elon Musk’s Tesla, have created a fertile backdrop for speculators hoping to profit from swelling appetite for cobalt, which boosts lithium-ion batteries’ power.

They are betting that demand for electric vehicles will exceed market expectations and push the up the price as battery makers such as Panasonic, which makes battery cells for Tesla, rush to lock-up supplies of the material. 

Global demand

Global demand is already expected to outstrip supply this year by 900 tonnes, according to commodity consultancy CRU. It estimates demand will grow 20 per cent a year for the next five years, thanks to buying from the electric car industry whose production grew by 41 per cent last year and which accounts for half of annual consumption. 

The price of cobalt, mined almost exclusively in the Democratic Republic of Congo, is already up by more than 50 per cent since November to $21 a metric pound. Prices rose to a peak of about $50 a pound in 2007, before dropping to a low of $10 in 2015....MORE

We have a silly habit of dropping breadcrumbs as we journey along the way, here's the intro to that 2016 piece:

A couple weeks ago we posted a seemingly innocuous piece with a boring headline: "'Freeport Sinks On Sale of Africa Copper Mine To Chinese' (FCX; LUN.TO)".

I figured there were at best two thousand people in the whole world who knew or cared about the back story and real import of what was going on so I'd just drop it as an Easter egg for the cognoscenti and other assorted electric vehicle/conflict mineral/African warlord/Elon Musk/extractive industry/Génocidaire hunter/U.S. political corruption watchers to find.

Well now that cat's out of the bag.

Big kudos to the FT's Henry Sanderson for recognizing one hell of a story and a small request for the Financial Times: Can you tell us what the old ENRC is up to these days?

From The Financial Times, May 25.... 

Apropos of nothing in particular, from the FT, Feb. 26: 

Mystery deepens over Chinese forces in Afghanistan

Elon Musk Slams Unionization Drive at Tesla, Promises Free Frozen Yogurt, Roller Coaster (TSLA)

Following up on last week's "Elon Musk says he doesn’t think Tesla unionization is “likely to occur” (TSLA)".
From BuzzFeed, Fri. Feb. 24:

Elon Musk Slams Tesla Union Drive, Promises Workers Free Frozen Yogurt

Tesla CEO Elon Musk sent an email to factory employees Thursday night calling an employee’s claims regarding working conditions “obviously…untrue”, and the United Auto Workers effort to unionize Tesla’s Fremont factory disingenuous....

...Tesla declined comment. The full text of Musk’s email is below.

"...As we get closer to being a profitable company, we will be able to afford more and more fun things. For example, as I mentioned at the last company talk, we are going to hold a really amazing party once Model 3 reaches volume production later this year. There will also be little things that come along like free frozen yogurt stands scattered around the factory and my personal favorite: a Tesla electric pod car roller coaster (with an optional loop the loop route, of course!) that will allow fast and fun travel throughout our Fremont campus, dipping in and out of the factory and connecting all the parking lots. It’s going to get crazy good 😊"

"Whatever happened to secular stagnation?"

From Gavyn Davies' blog at the Financial Times:

A year ago, Lawrence Summers’ perceptive warnings about the possibility of secular stagnation in the world economy were dominating global markets. China, Japan and the Eurozone were in deflation, and the US was being dragged into the mess by the rising dollar. Global recession risks were elevated, and commodity prices continued to fall. Fixed investment had slumped. Productivity growth and demographic growth looked to be increasingly anemic everywhere.

Estimates of the equilibrium real interest rate in many economies were being marked down. It seemed possible that the world economy would fall into a “Japanese trap”, in which nominal interest rates would be permanently stuck at the zero lower bound, and would therefore not be able to fall enough to stimulate economic activity.

Just when the sky seemed to be at its darkest, the outlook suddenly began to improve. Global reflation replaced secular stagnation as the theme that dominated investor psychology, especially after Donald Trump’s election in November. Why has secular stagnation lost its mass appeal, and has it disappeared forever? Was it all a case of crying wolf?

Lawrence Summers has always made it clear that in his mind secular stagnation was a hypothesis, not a proven reality, especially in the US. He and others have argued that the combination of very low global GDP growth, alongside falling real interest rates, could be caused by two factors: (i) inadequate global demand, stemming from low business investment, high savings rates in Asia, wide disparity in income distribution and rising risk aversion; and (ii) inadequate global supply, stemming from falling productivity growth, and slowing growth in the labour force....MORE

Inside Facebook's Artificial Intelligence Machine (FB)

There's a good chance we'll be referring back to this piece so I wanted to have it easily available.
From Backchannel:

The Applied Machine Learning group helps Facebook see, talk, and understand. It may even root out fake news.

When asked to head Facebook’s Applied Machine Learning group — to supercharge the world’s biggest social network with an AI makeover — Joaquin Quiñonero Candela hesitated.

It was not that the Spanish-born scientist, a self-described “machine learning (ML) person,” hadn’t already witnessed how AI could help Facebook. Since joining the company in 2012, he had overseen a transformation of the company’s ad operation, using an ML approach to make sponsored posts more relevant and effective. Significantly, he did this in a way that empowered engineers in his group to use AI even if they weren’t trained to do so, making the ad division richer overall in machine learning skills. But he wasn’t sure the same magic would take hold in the larger arena of Facebook, where billions of people-to-people connections depend on fuzzier values than the hard data that measures ads. “I wanted to be convinced that there was going to be value in it,” he says of the promotion.

Despite his doubts, Candela took the post. And now, after barely two years, his hesitation seems almost absurd.

How absurd? Last month, Candela addressed an audience of engineers at a New York City conference. “I’m going to make a strong statement,” he warned them. “Facebook today cannot exist without AI. Every time you use Facebook or Instagram or Messenger, you may not realize it, but your experiences are being powered by AI.”

Last November I went to Facebook’s mammoth headquarters in Menlo Park to interview Candela and some of his team, so that I could see how AI suddenly became Facebook’s oxygen. To date, much of the attention around Facebook’s presence in the field has been focused on its world-class Facebook Artificial Intelligence Research group (FAIR), led by renowned neural net expert Yann LeCun. FAIR, along with competitors at Google, Microsoft, Baidu, Amazon, and Apple (now that the secretive company is allowing its scientists to publish), is one of the preferred destinations for coveted grads of elite AI programs. It’s one of the top producers of breakthroughs in the brain-inspired digital neural networks behind recent improvements in the way computers see, hear, and even converse. But Candela’s Applied Machine Learning group (AML) is charged with integrating the research of FAIR and other outposts into Facebook’s actual products—and, perhaps more importantly, empowering all of the company’s engineers to integrate machine learning into their work.

Because Facebook can’t exist without AI, it needs all its engineers to build with it.

***

My visit occurs two days after the presidential election and one day after CEO Mark Zuckerberg blithely remarked that “it’s crazy” to think that Facebook’s circulation of fake news helped elect Donald Trump. The comment would turn out be the equivalent of driving a fuel tanker into a growing fire of outrage over Facebook’s alleged complicity in the orgy of misinformation that plagued its News Feed in the last year. Though much of the controversy is beyond Candela’s pay grade, he knows that ultimately Facebook’s response to the fake news crisis will rely on machine learning efforts in which his own team will have a part.

But to the relief of the PR person sitting in on our interview, Candela wants to show me something else—a demo that embodies the work of his group. To my surprise, it’s something that performs a relatively frivolous trick: It redraws a photo or streams a video in the style of an art masterpiece by a distinctive painter. In fact, it’s reminiscent of the kind of digital stunt you’d see on Snapchat, and the idea of transmogrifying photos into Picasso’s cubism has already been accomplished.

“The technology behind this is called neural style transfer,” he explains. “It’s a big neural net that gets trained to repaint an original photograph using a particular style.” He pulls out his phone and snaps a photo. A tap and a swipe later, it turns into a recognizable offshoot of Van Gogh’s “The Starry Night.” More impressively, it can render a video in a given style as it streams. But what’s really different, he says, is something I can’t see: Facebook has built its neural net so it will work on the phone itself.

That isn’t novel, either — Apple has previously bragged that it does some neural computation on the iPhone. But the task was much harder for Facebook because, well, it doesn’t control the hardware. Candela says his team could execute this trick because the group’s work is cumulative — each project makes it easier to build another, and every project is constructed so that future engineers can build similar products with less training required —so stuff like this can be built quickly. “It took eight weeks from us to start working on this to the moment we had a public test, which is pretty crazy,” he says....MORE

Vaclav Smil: "Cellphones as a fifth-order elaboration of Maxwell’s theory"

From IEEE Spectrum:

Stages of Electronics

 

Now that the world has become addicted to portable electronics, billions of people have come to see the companies providing these gadgets as the most innovative, and the people who head those companies as the most exalted, of all time. “Genius” is a starter category in this discussion.
But clever and appealing though today’s electronic gadgets may be, to the historian they are nothing but the inevitable fifth-order elaborations of two fundamental ideas: electromagnetic radiation, the theory of which was formulated by James Clerk Maxwell in the 1860s, and miniaturized fabrication, which followed Richard Feynman’s 1959 dictum [PDF] that “there’s plenty of room at the bottom.”

Maxwell was a true genius. The history of science offers few examples of work as brilliant as unifying electricity, magnetism, and light as aspects of a single phenomenon: electromagnetic waves. As Max Planck put it, “in doing so he achieved greatness unequalled.”

In late 1879 and early 1880, David Edward Hughes actually transmitted and received those invisible signals but did not publish his results. And in 1883, Thomas Edison also came very close to the actual use of such waves with his patent for an apparatus “showing conductivity of continuous currents through high vacuo.” He displayed it in 1884 at the International Electrical Exhibition in Philadelphia, then abandoned it as a mere curiosity.

That is why the second-order elaboration of electromagnetism came only between 1886 and 1888, when Heinrich Hertz deliberately generated and received electromagnetic waves whose frequencies he accurately placed “in a position intermediate between the acoustic oscillations of ponderable bodies and the light-oscillations of the ether.”

The third-order elaboration began with the first broadcasts, by Oliver J. Lodge and Alexander S. Popov, in 1894 and 1895, and it continued with the first transatlantic transmission, by Guglielmo Marconi in 1901; the first long-distance transmission of voice and music, by Reginald A. Fessenden in 1906; and the invention of vacuum tubes—John A. Fleming’s diode in 1904, Greenleaf W. Pickard’s point-contact diode (cat’s whisker) in 1906, and Lee de Forest’s triode in 1907....MORE

A Simple Measure of Economic Complexity

Via arXive, Quantitative Finance > Statistical Finance, Jan. 2016:

Abstract

We show from a simple model that a country's technological development can be measured by the logarithm of the number of products it makes. We show that much of the income gaps among countries are due to differences in technology, as measured by this simple metric. Finally, we show that the so-called Economic Complexity Index (ECI), a recently proposed measure of collective knowhow, is in fact an estimate of this simple metric (with correlation above 0.9).

1 Introduction
The standard approach to economic growth and development simplifies a country’s whole production to three aggregate s — GDP, labor and capital — thus disregarding its complexity. Complexity of production has to do with the diversity of products a country makes, which is itself a manifestation of the diversity of productive knowledge by which many products can be made — namely the various skills and technical knowledge applied by workers or automated by machines . Products differ precisely by the amount of knowledge involved in their production, which goes from zero for natural resources sold in the raw to maximum values for highly complex products such as aircrafts.

It is along such line of thought that emerged a literature , by Hausmann and Hidalgo notably, which links complexity of production to economic development [ 1 - 3 ] . Rich countries make various products, especially complex products, while poor countries make fewer and more rudimentary ones . In fact the mere number of products a country makes, or its diversification , indicates its development. Though basic , this opposes the long tradition in economics that link s international prosperity to the specialization of countries . Hausmann and Hidalgo propose a more elaborate metric called Economic Complexity Index (ECI) to quantify the amount of productive knowledge (or knowhow ) that underlies a country’s production. ECI is therefore, to use a more traditional term, a measure of a country’s technology — if technology is taken to mean precisely the sum of practical knowledge within a society . Similarly, we can define the technological sophistication of a product by the amount of knowhow involved in its production. This is measured by the Product Complexity Index (PCI) in the authors’ theory. In fact ECI and PCI are jointly computed, based on the idea that an economy’s technology is reflected in the products it makes, and, vice versa, a product reflects the technologies of the economies making it. A reformulation of the same idea was suggested by Caldarelli et al., which we shall also consider [ 4 - 6 ] . There, the metrics are named Country Fitness and Product Complexity.

Our goal in this paper is to propose a simpler and mo re natur al measure of technology : the logarithm of diversification . This metric derives from the following basic combinatorics. First, a product is but some transformed natural resources, namely some raw materials to which is applied a set of knowhow to turn it in to a valuable outcome . Second, and more fundamentally, knowledge comes in discrete units ( or ‘ bits ’) that combine to make more and more sophisticated knowledge .

Therefore with k units of knowhow , a country can make potentially 2 k d products, whose sophistication s range from zero for natural resources ( sold in the raw) to k . Thus, we can estimate the total amount of knowhow k involved in a country’s production by its log - diversification ( up to a scaling constant) . Only, bits of knowledge don’t combine such randomly: a collection of ideas is productively relevant only when it form s a coherent set of productive knowledge ( namely when they can be put together to transform a raw material ) .

So we shall develop a more realistic (yet still simple ) model of this combinatorics of knowhow . The point remains , however: log - diversification is the natural measure of technology . We show that this simple metric explains much of the income differences among countries. Finally, we show theoretically and empirically that ECI is in fact an estimate of this metric , in standardized form, while Fitness is linked to it by construction. But first we develop a simple conceptual framework and describe the data used throughout...

...MUCH MORE (14 page PDF)

Sticking with the "simple is good" theme, here's a post from 2011:
How to Predict a Nation's GDP per Capita at r=.97 Using "Economic Freedom and average citizenry IQ -- plus slight tweaks from trading block membership and oil"

BIS: Dollar Replaces VIX as the New Fear Guage ("there's something weird going on")

From ZeroHedge, Feb. 18:

"There's Something Weird Going On": Jeff Snider On The Global Dollar Shortage

The first time we explained that one of the biggest risks facing a world in which the dollar is the reserve currency is a global USD shortage, was in mid-2009, when we wrote "How The Federal Reserve Bailed Out The World."

At the time, the IMF calculated that just ahead of the financial crisis, "major European banks’ US dollar funding gap had reached $1.0–1.2 trillion by mid-2007. Until the onset of the crisis, European banks had met this need by tapping the interbank market ($432 billion) and by borrowing from central banks ($386 billion), and used FX swaps ($315 billion) to convert (primarily) domestic currency funding into dollars." The IMF then extrapolated that "were all liabilities to non-banks treated as short-term funding, the upper-bound estimate would be $6.5 trillion."

Since then the shortage, which some have dubbed a potential multi-trillion dollar margin call, has only grown and became a prominent issue back in March of 2015, when this phenomenon was used to explain why the cross-currency swap had plunged to multi-year lows. As JPM explained at the time, "the fx basis reflects the relative supply and demand for dollar vs. foreign currency funds and a very negative basis currently points to relative shortage of USD funding or relative abundance of funding in other currencies. Such supply and demand imbalances can create big shifts in the fx basis away from its actuarial value of zero."

Fast forward a year and a half later, when none other than the Bank of International Settlements, or the "Central canks' central bank", warned last November that it was no longer the VIX that was the widely accepted barometer of market "fear", it was now the dollar's turn to become the global fear gauge: "just as the VIX index was a good summary measure of the price of balance sheet before the crisis, so the dollar has become a good measure of the price of balance sheet after the crisis. The mantle of the barometer of risk appetite and leverage has slipped from the VIX, and has passed to the dollar."

Shortly thereafter we once recapped the main risks emerging from this increasingly more prominent threat to global financial stability, and wondered at what point would the Fed finally address this risk pointed out not only by this website for nearly 8 years, but also by the BIS, in a post which piggybacked on the recent work by ADM ISI's Paul Mylchreest, who has made tracking the global dollar shortage one of his primary objectives.

* * *

Now, in an exhaustive, 70 minute interview, submitted by Patrick Ceresna at MacroVoices.com, another prominent analyst who has been closely tracking the global dollar shortage, Alhambra Partners' Jeffrey Snider sat down with Erik Townsend to explain - once again - why this is such a critical topic, even if it comes at a time of unprecedented global complacency (it's amazing what record high stock prices will do to concerns - or lack thereof - about the future).

As Snider puts it, while most other risk indicators imply smooth sailing, "there is 'something' weird going on" when it comes to dollar funding and global imbalances of the world's reserve currency, i.e., dollar shortage.

• In the interview, among the many topics covered, are
• Understanding the Eurodollar Money Market
• Swap Spreads and Interbank Hierarchy
• Dimensions in the Eurodollar Futures and Eurodollar Money Supply
• Why does the World Need So Many Dollars?
• How the Eurodollar market supplanted the Bretton Woods System
• U.S. Dollar and the Dollar Funding Gap
• Reflation Trade Debunked
• Interest Rates Trapped
• Failing Global Currency System

While we urge readers to listen to the full interview below, here are some of the highlights, starting with "why the Dollar shortage a symptom of an inherently unstable system."

As Snider explains, "the dollar shortage isn't so much the shortage per se, it’s the fact that it's a symptom of what is an inherently unstable system." He notes that "the reason banks are withdrawing from the system is that it's just is no longer tenable" and "so there has to be some kind of – whether you want to look at it like another Bretton Woods – conference, a global monetary system, a global monetary get together where people start to analyze solutions to the problem as they are rather than keep trying to apply band aids that are not going to work. "

But, he concludes, "step one of that task is to actually recognize the problem as it is and so doing more stimulus or doing more QE isn't going to solve anything it isn’t do anything just like prior QEs and prior stimulus haven't done anything either because the problem is an unstable system."...MUCH MORE

Marc Andreessen Is Tweeting Again

From @pmarca:

Ask me anything! $20 per answer. All $ goes to @BlackGirlsCode. Send your questions here: https://t.co/IKp1WAsN4u 😀

— Marc Andreessen (@pmarca) February 23, 2017

Jalopnik: "Uber Is Doomed"

Readers who have followed the Uber story over the last few years, especially if you read Izabella Kaminska at FT Alphaville, know that despite posting on the lurid details from time to time (us more than she) our (and her) focus has been on the business/finance/econ aspects of Uber, although the political economy and other social science stuff can't help appearing, because what Kalanick built was in his own image.

From a 2014 post, "Here's the Real Problem With Uber: You Can't Trust Them":

The first thing I thought of when I started digging into Uber:

"From all our legends, mythology, and history (and who is to know where mythology leaves off and history begins – or which is which), the first radical known to man who rebelled against the establishment and did it so effectively that he at least won his own kingdom – Lucifer."

-Page ix of Rules for Radicals.

That's Alinsky seemingly quoting himself and the way I read it he's saying the Devil challenged authority and won his own kingdom.
That emulating the methods of Satan using any means fair or foul, including lying, cheating and stealing is the way to get riches and power.

And that was the moment when I stopped thinking of Uber as frat boys making stupid boob jokes and started thinking of them as nasty little political operatives.

If you're into this kind of stuff, Rule 12 appears to be the approach Uber management favors:

RULE 12: Pick the target, freeze it, personalize it, and polarize it." Cut off the support network and isolate the target from sympathy. Go after people and not institutions; people hurt faster than institutions. (This is cruel, but very effective. Direct, personalized criticism and ridicule works.)

I should note we are fans of Alinsky's tactical brilliance, oftentimes struggling to resist employing rule #5:

#5 Ridicule is man’s most potent weapon. It’s hard to counterattack ridicule, and it infuriates the opposition, which then reacts to your advantage....

So yeah, although the focus has been on the quantifiable, the soft science stuff is there as well and may be the thing that takes Uber down. At least that's the charitable interpretation, that Kalanick, blinded by hubris didn't see the flaws in the business plan.

The less favorable interpretation is that he knew all along and kept pushing in the hope that magic would happen.
That would be a fraud.

Anyhoo, here's one of the best automotive websites on the net talking Uber.

From Jalopnik:

If there is one quote that sums up the ethos of Uber, it might be this cut from the company’s firebrand CEO Travis Kalanick: “Stand by your principles and be comfortable with confrontation. So few people are, so when the people with the red tape come, it becomes a negotiation.” But after a month marked by one disaster after another, it’s hard to see how Uber’s defiant, confrontational attitude hasn’t blown up in its face. And those disasters mask one key, critical issue: Uber is doomed because it can’t actually make money.

After a discombobulated 2016, in which Uber burned through more than $2 billion, amid findings that rider fares only cover roughly 40 percent of a ride, with the remainder subsidized by venture capitalists, it’s hard to imagine Kalanick could take the company public at its stunning current valuation of nearly $70 billion.

And now, in the past few weeks alone, Uber has been accused of having a workplace that fosters a culture of misogyny, accused of stealing from Google the blueprint of a successful self-driving system, and has lost 200,000 customers over ties to President Donald Trump and how it responded to a taxi driver boycott.

Yet even when those factors are removed, it’s becoming more evident that Uber will collapse on its own. Barring a drastic shift in the company’s business—an implausible rollout of self-driving car fleets across the U.S., an increase of fares by three-fold, or a complete monopolization of the taxi and ride-hailing markets—Uber’s lifeline is shrinking. Its business model could collapse if one court case, and there are many, goes against it. Or perhaps more pressing, if it simply runs out of cash.
That Kalanick quote about confrontation may be as innocuous as a random sound bite, but it’s representative of the ride-hailing giant’s methodology since its founding in 2009: a perpetual resistance to regulatory oversight; a belief that, ultimately, an unfettered market is the key to prosperity. 

At first glance it seems like Kalanick’s libertarian ideals have paid off. Most recently valued at a reported $69 billion, Uber has captured a majority of the ground transportation market and flipped the taxi industry—a sector Kalanick once famously and snidely referred to as the Big Taxi Cartel—on its head. His philosophy mirrors the mindset of one of his favorite authors, the laissez-faire Ayn Rand. In 2012, Kalanick proffered that Uber’s battle against government regulations has an “uncanny resemblance” to the Randian philosophy. A billionaire fighting The System—and prevailing. It’s a good story for those who find truth in Atlas Shrugged.

Uber’s long had skeptics, and it’s not innovative to paint Kalanick, 40, as the boogeyman of Silicon Valley, where unseemly savants exist in vast supply.

The precarious moment in the company’s eight-year history falls on Kalanick’s lap. It’s his baby after all—a startup founded on seemingly nothing more than a vague idea, without much regard for the workforce to make it possible, or even a clear idea of what business model it actually wants to pursue. Uber has jumped from one idea to the next: UberX, UberEats, autonomous cars, and now flying cars, of all things.

“Instead of just focusing on being a good taxi company for the digital age… it’s blowing all sots of money [on] self driving-cars and China and now India. The company just so much reflects the megalomania of Travis Kalanick and whatever he thinks he’s doing.”

 

The impact of Uber’s death would probably be as much of a rebuke of Kalanick’s vision of running on a scatterbrained dream, not so much a solid business model and philosophy, that you could muster.

It would also be devastating for some. The livelihood of 11,000 employees across the world rests on Kalanick’s decision to submit to that philosophy—which, at its core, is a ruthless way of doing business. At the very least, drivers in the pre-Uber market could earn a decent living. Conversely, for example, Uber drivers taking advantage of new “vehicle solution” pilot program in Boston — renting cars by the hour through Zipcar — will earn less than Massachusetts’ minimum wage. How innovative. 

The Contractor Problem
One of the biggest issues that has left Uber’s business model hanging in the balance is its resistance to classifying its drivers—there are reportedly 600,000 in the U.S.—as employees, not contractors. If Uber is a house of cards, this is a key part of the foundation that, once removed, would demolish the structure.

Indeed, the company has said reclassifying drivers could “force Uber to restructure its entire business model.” The result of its opposition to readjust has been entirely expected. Without the perks and protections that an employee may enjoy—health care, benefits, gasoline and work reimbursements, vehicle maintenance, all of which could reportedly total as much as $730 million—complaints from drivers have piled up, ranging from low pay to new services like UberEats (a loathed food delivery service that’s reportedly set to lose over $100 million annually) and UberPOOL, its carpool option which increases the company’s take per-ride, lowers the take-home pay for drives, and is understood to be quite a drag for drivers and passengers alike. Drivers themselves said as much in a recent, disastrous question-and-answer session with Uber’s president....MUCH MORE

If interested, we have an awful lot of posts on Uber; here's the Google search of the site:

site:climateerinvest.blogspot.com uber

Technology Review's "10 Breakthrough Technologies 2017"

From MIT's Technology Review:

10 Breakthrough Technologies 2017

These technologies all have staying power. They will affect the economy and our politics, improve medicine, or influence our culture. Some are unfolding now; others will take a decade or more to develop. But you should know about all of them right now.

• 
  

  Reversing Paralysis

  Scientists are making remarkable progress at using brain implants to restore the freedom of movement that spinal cord injuries take away.
  
• 
  

  Self-Driving Trucks

  Tractor-trailers without a human at the wheel will soon barrel onto highways near you. What will this mean for the nation’s 1.7 million truck drivers?
  
• 
  

  Paying with Your Face

  Face-detecting systems in China now authorize payments, provide access to facilities, and track down criminals. Will other countries follow?
  
• 
  

  Practical Quantum Computers

  Advances at Google, Intel, and several research groups indicate that computers with previously unimaginable power are finally within reach.
  
• 
  

  The 360-Degree Selfie

  Inexpensive cameras that make spherical images are opening a new era in photography and changing the way people share stories.
  
• 
  

  Hot Solar Cells

  By converting heat to focused beams of light, a new solar device could create cheap and continuous power.
  
• 
  

  Gene Therapy 2.0

  Scientists have solved fundamental problems that were holding back cures for rare hereditary disorders. Next we’ll see if the same approach can take on cancer, heart disease, and other common illnesses.
  
• 
  

  The Cell Atlas

  Biology’s next mega-project will find out what we’re really made of.
  
• 
  

  Botnets of Things

  The relentless push to add connectivity to home gadgets is creating dangerous side effects that figure to get even worse.
  
• 
  

  Reinforcement Learning

  By experimenting, computers are figuring out how to do things that no programmer could teach them.