Showing posts with label machine learning. Show all posts
Showing posts with label machine learning. Show all posts

Sunday, October 22, 2017

First A.I. ETF Claims It Can Replace An Army Of Research Analysts

“Look Dave, I can see you’re really upset about this. I honestly think you ought to sit down calmly, take a stress pill and think things over.”


 


From Stanley Kubrick’s 2001: A Space Odyssey.



As if MiFID II wasn’t bad enough, now this “EquBot AI Technology with Watson has the ability to mimic an army of equity research analysts working around the clock, 365 days a year, while removing human error and bias from the process.” That is the claim of Chida Khatua, the ETF’sCEO.Unlike the existing algos used by quant funds, A.I.   the ability to learn from its mistakes without further requiring programming.


This week, EquBot LLC, in partnership with ETF Managers Group (ETFMG) launched the world’s first ETF powered by artificial intelligence, the AI Powered Equity ETF (NYSE Arca: AIEQ). According to Business Wire, the new ETF uses “cognitive and big data processing abilities of IBM Watson™ to analyze U.S.-listed investment opportunities”.


For those in the dark as far as “Watson” is concerned, it’s Wiki entry notes “Watson is a question answering (QA) computing system that IBM built to apply advanced natural language processing, information retrieval, knowledge representation, automated reasoning, and machine learning technologies to the field of open domain question answering. Watson was named after IBM"s first CEO, industrialist Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! and, in 2011, the Watson computer system competed on Jeopardy! against former winners Brad Rutter and Ken Jennings winning the first place prize of $1 million. Watson had access to 200 million pages of structured and unstructured content consuming four terabytes of disk storage…but was not connected to the Internet during the game. For each clue, Watson"s three most probable responses were displayed on the television screen. Watson consistently outperformed its human opponents on the game"s signaling device, but had trouble in a few categories, notably those having short clues containing only a few words.”


Business Wire explained how EquBot makes investment decisions “EquBot’s approach ranks investment opportunities based on their probability of benefiting from current economic conditions, trends, and world- and company-specific events, and identifies those equities with the greatest potential for appreciation. EquBot and ETFMG expect the fund’s portfolio to typically consist of 30 to 70 of U.S. equities only and volatility comparable to the broader U.S. equity market…the fund’s underlying technology is constantly analyzing information for approximately 6,000 U.S.-listed equities, including company management and market sentiment, and processes more than one million regulatory filings, quarterly results releases, news articles, and social media posts every day.”


According to Chida Khatua, CEO and co-founder of EquBot LLC “Machine learning is one of the most powerful applications of artificial intelligence. As powerful as many algorithms underlying expensive quantitative hedge funds and other vehicles might be, unless they’re also built with AI and machine learning baked right in, mistakes can be propagated and opportunities for outperformance can be missed.”


Neither of the founders is lacking in confidence when discussing the potential for the new ETF. From Business Wire “With the launch of AIEQ, we’re not only bringing our new fund to market,’ said Art Amador, co-founder and COO of EquBot. ‘We believe we’re pioneering a whole new investment category; one that will soon have investors and advisors diversifying their portfolios among passive, active and AI approaches”


He added “Everyday, there is more information, not less. That information explosion has made the jobs of portfolio managers, equity analysts, quantitative investors and even index builders more challenging.”


He"s not wrong there.


A.I. might be the future of investing, although there have been funds that were so good (LTCM), they didn’t need to post collateral. This is different, obviously as we’re not just talking about a bunch of really "brainy" humans.


But how sad will it be if we go from this...



To this...



To this...



An end up with this...



The regulators are already doing their best to make the investment world less fun.


“Open the pod bays doors, HAL”



Writing about this, we were reminded of another life or death confrontation between humans and technology in Stanley’s Kubrick’s “2001: A Space Odyssey”, which also had an oblique reference to an IBM computer. In the movie, there is an argument as to whether the failure of an antenna is due to human error, as the HAL 9000 insists, or HAL, as Mission Control advises. In the ensuing conflict, HAL initially gains the upper hand, kills Poole and almost kills Bowman. Bowman manages to re-enter the ship and get to HAL’s processor core, regressing HAL to his first programmed memory.


“I know everything hasn’t been quite right with me, but I can assure you now, very confidently, that it’s going to be alright again. I feel much better now.”




 









Wednesday, October 18, 2017

$1 Trillion In Liquidity Is Leaving: "This Will Be The Market's First Crash-Test In 10 Years"

In his latest presentation, Francesco Filia of Fasanara Capital discusses how years of monumental liquidity injections by major Central Banks ($15 trillion since 2009) successfully avoided a circuit break after the Global Financial Crisis, but failed to deliver on the core promise of economic growth through the "wealth effect", which instead became an "inequality effect", exacerbating populism and representing a constant threat to the status quo.


Fasanara discusses how elusive, over-fitting economic narratives are used ex-post to legitimize the "fake markets" - as defined previously by the hedge fund - induced by artificial flows. Meanwhile, as an unintended consequence, such money flows produced a dangerous market structure, dominated by both passive-aggressive investment vehicles and a high-beta long-only momentum community ($8 trn and rising rapidly), oftentimes under the commercial disguise of brands such as behavioral Alternative Risk Premia, factor investing, risk parity funds, low vol / short vol vehicles, trend-chasing algos, machine learning.


However as Filia, and many others before him, writes, only when the tide goes out, will we discover who has been swimming naked, and how big of a momentum/crowding trap was built up in the process. The undoing of loose monetary policies (NIRP, ZIRP), and the transitioning from "Peak Quantitative Easing" to Quantitative Tightening, will create a liquidity withdrawal of over $1 trillion in 2018 alone. The reaction of the passive community will determine the speed of the adjustment in the pricing for both safe and risk assets.


And, echoing what Deutsche Bank said last week, when it warned that central bank liquiidty injections will collapse from $2 trillion now to 0 in 12 months, a "most worrying" turn of events, Fasanara doubles down that "such liquidity withdrawal will represent the first real crash-test for markets in 10 years." 



Filia concludes that "the big opportunity in today"s markets is to position for such moment of adjustment, as it is totally priced out despite its potential for severe disruption, thus offering the most pronounced asymmetric profile."


Below are the key slides from Fasanara"s presentation:









The full, must read presentation is below (link):

Saturday, October 14, 2017

Tech Vs. Trump: The Great Battle Of Our Time Has Begun

Authored by Niall Ferguson via The Spectator,


Social media helped Donald Trump take the White House. Silicon Valley won’t let it happen again...



In the 1962 Japanese sci-fi classic King Kong vs Godzilla, the two giant monsters fight to a stalemate atop Mount Fuji. I have been wondering for some time when the two giants of American social media would square up for what promises to be a comparably brutal battle. Finally, it began last month - and where else but on Twitter?


‘Facebook was always anti-Trump,’ tweeted the President of the United States on 27 September.


Mark Zuckerberg shot back hours later (on Facebook, of course): ‘Trump says Facebook is against him. Liberals say we helped Trump. Both sides are upset about ideas and content they don’t like. That’s what running a platform for all ideas looks like.’


A platform for all ideas? Well, maybe. Others see Facebook differently. As Zuckerberg’s response to Trump acknowledged, the President is not alone in criticising him. The various inquiries into Russian meddling in the 2016 presidential election are turning up much that is awkward, notably that Russia bought around 3,000 Facebook ads designed to spread politically divisive posts to Americans before and after the election, as well as to promote inflammatory political protests on issues such as Muslim immigration.


It may be too big a stretch to claim that Russian Facebook ads swung the election in Trump’s favour. But it seems plausible that his campaign’s use of social media, particularly Facebook, gave it a vital edge that compensated for its financial disadvantage relative to Hillary Clinton’s campaign. On that, if on nothing else, I suspect Steve Bannon and Clinton would agree. ‘Facebook is now the largest news platform in the world,’ Clinton writes in her election postmortem. ‘With that awesome power comes great responsibility.’


Awesome power, yes. At the end of June, the number of active Facebook users (people who visit the site at least once a month) passed the two billion mark. WhatsApp, Messenger and Instagram — all owned by Facebook — have three billion users altogether, though no doubt there is much overlap. Two- thirds of American adults are on Facebook and 45 per cent get their news from it. More than half the UK population access Facebook at least once a month. The average user is on the site for 1/16 of every day.


But great responsibility? In the wake of the Las Vegas massacre, Facebook briefly featured a bogus story that the shooter had ‘Trump-hating’ views. A fake page claimed responsibility for the attack on behalf of the far-left Antifa movement, saying the goal had been to kill ‘Trump-supporting fascist dogs’.


Last month, the non-profit investigative news site ProPublica revealed that Facebook’s online ad tools had helped advertisers to target self-described ‘Jew haters’ or people who had used phrases such as ‘how to burn Jews’. In the words of Facebook’s chief operating officer Sheryl Sandberg: ‘The fact that hateful terms were even offered as options was totally inappropriate and a fail on our part.’ Facebook ‘never intended or anticipated this functionality being used this way’.


What Facebook intended and how Facebook is used turn out to be very different. The company’s motto used to be: ‘Make the world more open and connected.’ It’s no longer quite so simple.


‘For most of the existence of the company, this idea of connecting the world has not been a controversial thing,’ Zuckerberg recently said. ‘Something changed.’


What has changed is that the world has belatedly woken up to realities about social networks that were already obvious to anyone familiar with history and network science.


For most of history, it is true, hierarchies have tended to dominate distributed networks. However, there are historical precedents for technological change leading to enhanced connectedness that empowers social networks and weakens hierarchies.


The first began exactly 500 years ago, when Martin Luther launched his campaign for reform of the Roman Catholic church. Had it not been for the printing press, Luther would have been just another obscure heretic and might well have ended his life in the flames of the stake. But Gutenberg’s innovation enabled Luther’s message to ‘go viral’ — as we would now say — and it spread with remarkable speed throughout Germany and then across north-western Europe.


Luther was as much of a utopian as the pioneers of Silicon Valley in our own time. In his mind, the Reformation would create a powerful new network of pious Christians, all enabled to read the Bible in the vernacular and to establish more direct relationships with God than the indirect ones mediated by a corrupt ecclesiastical hierarchy. The vision of St Peter of a ‘priesthood of all believers’ would finally be realised.


But the true upshot of the Reformation was not harmony but polarisation and conflict. Not everyone was inspired by Luther’s message. Some sought to go further than him. Others reacted violently against the proposed reforms. The Counter-Reformation adopted the Protestants’ novel techniques of propagation and deployed them against the heretics.


Yet it proved impossible to destroy Protestant networks, even with mass executions and hideously cruel torture. If anything, persecution promoted radicalisation. Meanwhile, the constantly growing network of printed words proved itself as ready to spread madness as holiness. The witch craze of the 17th century was a classic example of a monster meme, claiming innocent lives from Scotland to Salem, Massachusetts.


There are three big differences between now and then.





First, today’s social networks are vastly bigger, faster and more widespread than those of the early modern era.



Secondly, whereas the printing press was a truly decentralised technology — Johannes Gutenberg was no Bill Gates — the ownership of today’s IT infrastructure is concentrated in remarkably few hands.



Finally, our networked age began by disrupting markets and later politics; only one religion, Islam, has been significantly affected.



But the similarities are nevertheless striking. Now, as then, newly empowered networks have led to polarisation, not harmony. Now, as then, the networks have acted as a transmission mechanism for all kinds of manias and panics as well as truth and beauty. And now, as then, the networks have eroded territorial sovereignty, weakening the established structures of political authority.


The US government sought to harness the power of social networks when the National Security Agency co-opted the big technology companies into its PRISM programme of mass domestic and foreign surveillance. But the new networks did not easily integrate into old power structures. Globally disseminated leaks, courtesy of Edward Snowden and Julian Assange, exposed PRISM, while a new kind of populist politics flourished on social media.


A defining feature of social networks (as in the Reformation) is their tendency to divide rather than unite. Recent research on American blogs and Twitter reveals a similar pattern: the emergence of two self-segregated ideological communities, one liberal, the other conservative. Just as birds of a feather flock together (network geeks call it ‘homophily’) so Twitter users retweet within their political clusters. One study found that with tweets on hot-button political topics (such as gun control, same-sex marriage and climate change), the use of emotional words increases their diffusion by a factor of 20 per cent for each additional word. Ever wondered why tweets are full of expletives? Now you know.


The presidential election of 2016 was a tale of many networks. By going viral through a largely self-organised network, Trump beat Clinton’s old-school, hierarchically structured campaign, which poured money into antiquated channels like local television. Isis contributed to the febrile atmosphere with its worst attack in North America (in Orlando in June last year), prompting Trump’s populist (and popular) promise of a ‘Muslim ban’. But the Trump network had itself been penetrated by the Russian intelligence network. Trump’s campaign and, to a much smaller extent, the Russians both used Facebook and Twitter as tools to discredit his opponent and discourage potential Democratic voters.


Make no mistake: 2016 will never happen again. Silicon Valley hates Trump for too many reasons to count. The most important are his stance on immigration (on which the Valley depends for its supply of skilled software engineers) and Big Tech’s need to ‘virtue-signal’ to its most valued user demographic: the young and affluent. They lean left. So does the otherwise capitalist Valley.


The political consequences were not immediately obvious, unless you were paying close attention, but after the Charlottesville clashes between white supremacists, neo-Nazis and their various left-wing opponents, they were there for all to see. Matthew Prince, CEO of the internet service provider Cloudflare, described what happened: ‘Literally, I woke up in a bad mood and decided someone shouldn’t be allowed on the internet.’ On the basis that ‘the people behind the Daily Stormer are assholes’, he denied their fascistic website access to the worldwide web. As Prince himself rightly observed: ‘No one should have that power. We need to have a discussion around this with clear rules and clear frameworks. My whims and those of Jeff [Bezos] and Larry [Page] and Satya [Nadella] and Mark [Zuckerberg] shouldn’t be what determines what should be online.’ Yet that discussion has barely begun. And until it happens, it will indeed be they who decide who is allowed on the internet.


This goes to the heart of the matter. According to Zuckerberg, Facebook is ‘a tech company, not a media company… We build the tools; we do not produce any content’. Yet in practice, according to a recent Reuters investigation, ‘an elite group of at least five senior executives regularly directs content policy and makes editorial judgment calls.’ In the words of Espen Egil Hansen, the editor-in-chief of the Norwegian newspaper Aftenposten, Zuckerberg is now ‘the world’s most powerful editor’.


It is not only neo-Nazi sites that find themselves on the online equivalent of the newsroom spike. Twitter has recently rejected paid-for tweets from the Center for Immigration Studies (CIS) on the grounds of ‘Hate’. These tweets were hardly excerpts from Mein Kampf: for example: ‘The fiscal cost created by illegal immigrants of $746.3bn compares to a total cost of deportation of $124.1bn.’ In the words of CIS director Mark Krikorian, ‘The internet is now a utility more important than phones or cable TV. If people can be denied access to it based on the content of their ideas and speech (rather than specific illegal acts), why not make phone service contingent on your political views? Or mail delivery?’


Google recently revealed that it is using machine learning to document ‘hate crimes and events’ in America. Among their partners in this effort is the notorious Southern Poverty Law Center (SPLC), which maintains a list of ‘anti-Muslim extremists’ — including my wife, Ayaan Hirsi Ali, and the British liberal Muslim Maajid Nawaz — but no list whatsoever of Muslim extremists.


‘YouTube doesn’t allow hate speech or content that promotes or incites violence,’ declared a recent message to YouTube content creators. But who decides what is ‘hate speech’? The phrase has become the 21st-century equivalent of ‘heresy’. It’s what you call something before you proscribe it.


Silicon Valley insists it is home to neutral network platforms. This is no longer credible. Facebook alone has, without quite meaning to, evolved into the most powerful publisher in the history of the world. Zuckerberg is William Randolph Hearst to the power of ten.


So what to do? Left-leaning Democrats have an answer: revive the progressive interpretation of anti-trust policy and break up the internet monopolies. Superficially, they have a case. Amazon controls 65 per cent of all online new book sales. Google’s market share of online search is 87 per cent in the US. In mobile social networking, Facebook and its subsidiaries control 75 per cent of the American market.


Yet who seriously cares what the hipster anti-trust types say? Silicon Valley is a huge donor to the Democrats. Why would they make life difficult for Big Tech when it so openly leans left? The real question is when Republicans (and not just the President) are going to wake up to the threat they now face.


Two big battles are looming: one on the question of net neutrality (the principle that all bits of data should be treated alike, regardless of their content or value), the other on the 1996 Communications and Decency Act, which allows tech firms exemption from liability for content that appears on their platforms. A group of senators led by Rob Portman has started the ball rolling by seeking to impose liability on companies that knowingly facilitate sex trafficking on their platforms. The initial response of the Internet Association, a trade group that is essentially a mouthpiece for the Valley, was revealing: ‘The entire internet industry wants to end human trafficking,’ it said. ‘But there are ways to do this without amending a law foundational to legitimate internet services.’ Last month, however, the IA conceded the need for ‘targeted amendments’.


This battle is only just beginning, but its outcome could be decisive in both the 2018 midterm elections to Congress and the 2020 presidential race. The regulatory status quo is not only highly favourable to Silicon Valley. It could also prove highly unfavourable to Republican candidates — though (so far as I could tell on a recent visit to Washington) the penny has not yet dropped with lawmakers who are accustomed to talking only about deregulation, not regulation.


In many ways, what we are about to witness will be a classic struggle between new networks and established hierarchies. Like King Kong’s epic slugfest with Godzilla, however, it’s far from easy to predict which side will prevail - or how much collateral damage they will both inflict on American democracy. In the old Godzilla movies, after all, the one predictable thing is that Tokyo always gets destroyed.

Monday, October 9, 2017

Facebook Security Chief Lashes Out: "Censorship Is Easy If You Don't Worry About Becoming The Ministry Of Truth"

In a furious tweetstorm this weekend, Facebook"s Chief Security Officer warned interfering desperate politicians and triggered letfists that the fake news problem is more complicated and dangerous to solve than the public thinks.



As a reminder, we noted that Alex Stamos was seemingly pressured into "finding" Russian evidence after Senator Mark Warner paid the social media company a visit -





A few weeks after the French election, Warner flew out to California to visit Facebook in person. It was an opportunity for the senator to press Stamos directly on whether the Russians had used the company’s tools to disseminate anti-Clinton ads to key districts.



Officials said Stamos underlined to Warner the magnitude of the challenge Facebook faced policing political content that looked legitimate.



Stamos told Warner that Facebook had found no accounts that used advertising but agreed with the senator that some probably existed. The difficulty for Facebook was finding them.



For months, a team of engineers at Facebook had been searching through accounts, looking for signs that they were set up by operatives working on behalf of the Kremlin. The task was immense.



Warner’s visit spurred the company to make some changes in how it conducted its internal investigation. Instead of searching through impossibly large batches of data, Facebook decided to focus on a subset of political ads.



Technicians then searched for “indicators” that would link those ads to Russia. To narrow down the search further, Facebook zeroed in on a Russian entity known as the Internet Research Agency, which had been publicly identified as a troll farm.



“They worked backwards,” a U.S. official said of the process at Facebook.



The breakthrough moment came just days after a Facebook spokesman on July 20 told CNN that “we have seen no evidence that Russian actors bought ads on Facebook in connection with the election.”



And the rest is history as 3000 "Russian Ads" were suddenly discovered to enable Warner to keep the narrative alive - and more crucially demand social media companies crackdown on "fake news", on politically-sponsored and divisive ads, and on anything they decide is not really fitting their identity-politics-based narratives.


However, given this weekend"s tweetstorm by Stamos, we suspect he has finally snapped and been forced to shove some common sense down the throats of the vengeful politicians who see no unintended consequences in their demands for big-brother-esque newspeak. 





"It’s very difficult to spot fake news and propaganda using just computer programs," Stamos said in a series of Twitter posts on Saturday.



“Nobody of substance at the big companies thinks of algorithms as neutral,” Stamos wrote, adding that the media is simplifying the matter.



“Nobody is not aware of the risks.”








As Bloomberg reports, the easy technical solutions would boil down to silencing topics that Facebook is aware are being spread by bots -- which should only be done “if you don’t worry about becoming the Ministry of Truth” with machine learning systems “trained on your personal biases,” he said.





“A lot of people aren’t thinking hard about the world they are asking [Silicon Valley] to build,” Stamos wrote.



“When the gods wish to punish us they answer our prayers.”



Stamos’s comments shed light on why Facebook added 1,000 more people review its advertising, rather than attempting an automated solution.


The company sent a note to advertisers telling them it would start to manually review ads targeted to people based on politics, religion, ethnicity or social issues. The company is trying to figure out how to monitor use of its system without censoring ideas, after the Russian government used fake accounts to spread political discord in the U.S. ahead of the election.


The silver lining at least is that Stamos is aware of what a terrible idea the kind of censorship that Democratic politicians (and John McCain) are demanding... whether this means that, behind the smoke and mirrors of actively managing your news feed to provide you with your self-bias-perpetuating perspective, anything will change, is anyone"s guess.

Friday, September 29, 2017

The US Military Is Quietly Building SkyNet

Maybe Elon Musk had a point…


The US’s military leaders have agreed on a strategy to guarantee the US military retains its global dominance during the twenty-first century: Connect everything with everything, as DefenseOne describes it. The result? An unimaginably large cephapoloidal nervous system armed with the world’s most advanced weaponry, and in control of all military equipment belonging to the world’s most powerful army.


Sound familiar? It should...



A networked military – an extreme take on the “internet of things” - would connect everything from F-35 jets to the Navy’s destroyers to the armor of the tanks crawling over the land to the devices carried by soldiers – every weapon would be connected.  Every weapon, vehicle, and device connected, sharing data, constantly aware of the presence and state of every other node in a truly global network.


Of course, the development of these “smart” weapons should unnerve Tesla CEO Elon Musk, who has repeatedly warned that AI and machine learning poses a greater threat to the future of the US than North Korea. If not properly regulated, Elon suggested that machines could turn against their human masters.





“Until people see robots going down the street killing people, they don’t know how to react because it seems so ethereal,” he said.



“AI is a rare case where I think we need to be proactive in regulation instead of reactive. Because I think by the time we are reactive in AI regulation, it’s too late.”



The Joint Chiefs of Staff described their vision for a completely networked military in the newest iteration of their National Military Strategy, which lays out their plans for building the military"s weapon of the future. Ironically, Air Force Chief of Staff Gen. David Goldfein said he had based the plan on a certain money-losing electric-car manufacturer. Goldfein was particularly impressed by Tesla’s ability to remotely extend the battery life of vehicles as their owners fled Hurricane Irma earlier this month. 





In recent months, the Joint Chiefs of Staff put together the newest version of their National Military Strategy. Unlike previous ones, it is classified. But executing a strategy requiring buy-in and collaboration across the services. In recent months, at least two of the service chiefs talked openly about the strikingly similar direction that they are taking their forces. Standing before a sea of dark- blue uniforms at a September Air Force Association event in Maryland, Air Force Chief of Staff Gen. David Goldfein said he had “refined” his plans for the Air Force after discussions with the Joint Chiefs “as part of the creation of the classified military strategy.”



The future for the Air Force? The service needed to be more like a certain electric-car manufacturer.



“Every Tesla car is connected to every other Tesla car,” said Goldfein, referring to a presentation by Elon Musk about the ways his firm’s vehicles learn from their collective experience. “If a Tesla is headed down the road and hits a pothole, every Tesla that’s behind it that’s self-driving, it will avoid the pothole, immediately. If you’re driving the car, it automatically adjusts your shocks in case you hit it, too.”



Goldfein waxed enthusiastically about how Tesla was able to remotely increase the battery capacity of cars in the U.S. Southeast to facilitate evacuation before the recent hurricanes.



“What would the world look like if we connected what we have in that way? If we looked at the world through a lens of a network as opposed to individual platforms, electronic jamming shared immediately, avoided automatically? Every three minutes, a mobility aircraft takes off somewhere on the planet. Platforms are nodes in a network,” the Air Force chief said.



As DefenseOne explains, the idea of a networked military borrows from the  “network centric warfare” concept that first emerged more than a decade ago. However, the concept that military leaders proposed in their latest review is less a strategy for increasing efficiency than a plan to connect all military equipment on a single network. The result would be better coordinated, faster, and more lethal operations in air, land, sea, space, and cyberspace.



The Air Force has begun making broad investments in data sharing. And its experiments with next-generation light tactical attack aircraft are as much about hardware as networks, he said. “Not only what can I buy and what can they do, but more importantly, can they connect? Can they actually share? And can we tie it to a new network that’s based on sharable information that gets me beyond the challenges I have right now in terms of security?” Goldfein said.


The Air Force Science Board is studying how to control a network of military equipment including light attack aircraft, tanks and even unmanned drones. James Chow, the board’s new head, told DefenseOne the study would also consider how to connect to other services.


As DefenseOne explains, although most of the research into the networked military is being conducted by the Air Force, once implemented, any system would likely include weapons from across the military, like Navy destroyers, said Chow.


“Our scope would be in helping the Air Force to think about operations they would be conducting that would incorporate joint sensors and platforms, like destroyers, I think that has to be part of it. And that is within the charter of the study,” Chow  said, adding that the study has “the highest priority level for Air Force leadership.”


The Marines are also looking at tanks that are digitally connected through their armor, according to Lt. Gen. Robert Walsh, who leads Marine Corps Combat Development Command and serves as Deputy Commandant for Combat Development and Integration. Navy leaders have also authorized research into connecting every object on the sea, land, air, space and in cyberspace. This is no exaggeration. Adm. John Richardson, Chief of Naval Operations, said during a Navy expo earlier this year that he’d eventually like to “network everything,” explaining that creating such a system would be crucial to maintaining US military dominance.  


In an amusing aside, DefenseOne notes that, despite the obvious parallels, military leaders detest comparisons between their tech pet projects and anything from the plot of the Terminator franchise.


And while enabling instantaneous communication between military units would undoubtedly improve efficiency and tactical prowess, as Musk as pointed out, these projects should be undertaken cautiously.

Monday, September 11, 2017

Visualizing The Future Of Food

The urban population is exploding around the globe, and, as Visual Capitalist"s Jeff Desjardins explains below, yesterday’s food systems will soon be sub-optimal for many of the megacities swelling with tens of millions of people.


Further, issues like wasted food, poor working conditions, polluted ecosystems, mistreated animals, and greenhouse gases are just some of the concerns that people have about our current supply chains.


Today’s infographic from Futurism shows how food systems are evolving – and that the future of food depends on technologies that enable us to get more food out of fewer resources.




THE NEXT GEN OF FOOD SYSTEMS


Here are four technologies that may have a profound effect on how we eat in the future:


1. Automated Vertical Farms


It’s already clear that vertical farming is incredibly effective. By stacking farms on top of another and using automation, vertical farms can produce 100x more effectively per acre than conventional agricultural techniques.


They grow crops at twice the speed as usual, while using 40% less power, having 80% less food waste, and using 99% less water than outdoor fields. However, the problem for vertical farms is still cost – and it is not clear when they will be viable on a commercial basis.


2. Aquaponics


Another technology that has promise for the future of food is a unique combination of fish farming (aquaculture) with hydroponics.


In short, fish convert their food into nutrients that plants can absorb, while the plants clean the water for the fish. Compared to conventional farming, this technology uses about half of the water, while increasing the yield of the crops grown. As a bonus, it also can raise a significant amount of fish.


3. In Vitro Meats


Meat is costly and extremely resource intensive to produce. As just one example, to produce one pound of beef, it takes 1,847 gallons of water.


In vitro meats are one way to solve this. These self-replicating muscle tissue cultures are grown and fed nutrients in a broth, and bypass the need for having living animals altogether. Interestingly enough, market demand seems to be there: one recent study found that 70.6% of consumers are interested in trying lab grown beef.


4. Artificial Animal Products


One other route to get artificial meat is to use machine learning to grasp the complex chemistry and textures behind these products, and to find ways to replicate them. This has already been done for mayonnaise – and it’s in the works for eggs, milk, and cheese as well.


TASTING THE FUTURE OF FOOD


As these new technologies scale and hit markets, the future of food could change drastically. Many products will flop, but others will take a firm hold in our supply chains and become culturally acceptable and commercially viable. Certainly, food will be grown locally in massive skyscrapers, and there will be decent alternatives to be found for both meat or animal products in the market.


With the global population rising by more than a million people each week, finding and testing new solutions around food will be essential to make the most out of limited resources.

Friday, September 8, 2017

Quant Fund Run By Three 20-Somethings Trades $1 Billion A Day

Financial markets are increasingly being dominated by quantitative and passive traders (even as quant forms have underperformed this year).


We highlighted this dichotomy earlier this year in a post titled “Quants Dominate The Market; Unexpectedly They Are Also Badly Underperforming It:”






“Two days ago, JPM"s head quant made a striking observation: "Passive and Quantitative investors now account for ~60% of equity assets (vs. less than 30% a decade ago). We estimate that only ~10% of trading volumes originates from fundamental discretionary traders." In short, markets are now "a quant"s world", with carbon-based traders looking like a slow anachronism from a bygone era.



Bloomberg confirmed as much today, when looking at another divergence between quant funds and traditional, discretionary managers: "systematic strategies have barely budged from near-record participation in U.S. stocks. Meanwhile, fundamental equity long-short managers can’t afford to be anything but picky, considering the market’s narrow leadership. The result: the largest gap on record between humans’ and computers’ gross exposure to U.S. equities, data compiled by Credit Suisse Group AG show.”



This year is shaping up to be a dismal one for so-called quant funds. Still, even as quants have failed to capture record-setting equity gains, they"ve held on to their status of Wall Street darlings, attracting the lion"s share of inflows, not to mention flattering press coverage, like this profile of one quantitative fund published by Forbes.



Domeyard, a Boston-based hedge fund founded by three twentysomethings, uses strategies pioneered by HFT prop-trading shops, sometimes executing $1 billion in trades in a day.








"We are doing on average $1 billion of daily transactions... it"s a high frequency trading strategy that is signal based."




As funds scramble to lure new investor with more attractive fee schedules, Domeyard is declining to accept a set fee in lieu of pocketing 40% to 50% of profits. According to Forbes, Domeyard operates more like an HFT shop than a hedge fund in a few notable ways, including its practice of closing out positions at the end of every trading day.


Here’s Forbes:





“Brash and optimistic, Domeyard’s founders have structured their firm as a hedge fund that doesn’t charge its investors a management fee, but does take between 40% to 50% of the profits. Qi says the firm, which currently manages in the low tens of millions of dollars, runs a low capacity strategy that currently makes between 10,000 to 40,000 trades daily. Although run as a hedge fund, Domeyard closes out its trades like many proprietary trading firms do, ending each day with no market exposure.”



The firm has attracted money from big-name investors, including Howard Morgan, a co-founder of Renaissance Technologies:





“Domeyard has raised $10 million for its general partnership from the likes of Howard Morgan, a co-founder of Renaissance Technologies who later became a venture capitalist, and Gary Bergstrom, the founder of quantitative investment firm Acadian Asset Management. Domeyard’s 14 employees include former portfolio managers who led high frequency trading teams at Quantlab, Athena Capital Research and Sun Trading, as well as former senior engineers from PDT Partners and Lime Brokerage—some of the biggest names in quantitative and high frequency trading.”



To be sure, HFT-oriented startup funds like Domeyard are facing obstacles that seem increasingly insurmountable, as the Wall Street Journal pointed out earlier this year. More banks have opened their own HFT arms, arbing away some of the profitability of industry pioneers like Virtu Financial.


For their part, Domeyard’s founders hope to find an “edge” by relying on “sequential machine learning and making large scale computations of statistics.”





“The Domeyard crew is operating in a field dominated by big firms with years of operating history that have spent fortunes on infrastructure and armies of mathematicians and engineers. In addition, this low-volatility stock market era has cut deeply into some of the richest strategies of high frequency traders, causing a wave of consolidation in the industry.



But Domeyard’s young founders think that there are some advantages to being the new kids on the high-frequency block. The firm is working to unlock profitable trading strategies by using sequential machine learning and making large scale computations of statistics. “I feel like we can do better in a lot of areas and with some technological problems because we started from scratch,” says Wang.”



Hopefully the strategy works - for their investors" sake.

Monday, April 3, 2017

Mayhem At Your Fingertips

"Jeezuz! No, that"s scary!"


My wife was looking at an app on my phone with a stream of automated alerts.



Actually, it"s way more than an app. It’s the tip of the iceberg for a much broader safety and security iceberg. A multi-channel communication platform with push, SMS, voice calling, email, and real-time alerts - meaning time saved reacting to any emergency. Soon, it’s coming with a network of partners that will actually snag you during an emergency.


I explained all this to my wife.


"But why do you need this," stuff she wanted to know.


Fair point...


I"ll readily and, might I say, gladly admit that living in a small boutique beachside community in a country many don"t know exists this technology seems awfully like overkill. The fact is bugger all happens in the "terror" bracket down here.


Well, that"s not true actually. Just last week some naughty backpackers went and rented surfboards at the main beach and never returned them. It was all over the local news in hours and residents were on the lookout. I suspect some burly Kiwi farmer has probably found and dealt with the little snots by now and they"ll shortly be found naked tied to a tree with bailing twine and with goats chewing on their soft bits. In any event, this is big news here.


The truth is I don"t always need this stuff for my personal use but I"ve got this sexy swishbang real time data feed on global risk at my fingertips. Just because I"m removed from "hot spots" doesn"t mean I can"t benefit from knowing what"s happening. The SigActs engine (part of their platform) creates a place for aggregated open-source intelligence that provides an every-day benefit, not just during an emergency.


If, for example, I wanted to know about the risks of carjackings in an area my sister was looking at a job offering, I"ve got it at my fingertips. Prevention is better than cure.


The other reason is that I seeded the particular company and, as a result, have been eager to be kept up to speed on their progress. They are, after all, in a sector that I"ve said before will EXPLODE.


The real solutions to crime aren"t going to look like Vin Diesel, and the dunderheads at airports around the world aren"t helping anyone by ruining our laptops while having half a dozen labradors rummage through our shoes. That"s useful for keeping pedophiles and people with suspiciously long arms employed, but not much else.


The real bang for your buck will lie in artificial intelligence, machine learning, drones, and the integration of existing data sources.


Here"s a useful little set of stats for you.


  • 300% YoY increase in use of cellphone-based accountability.

  • 400% increase in fatalities from terrorist attacks, globally from 2005 to 2015 (Global Terrorism Database).

  • $31.9bn - projected size of  critical communications market in 2020, up from $15.6bn today (Frost and Sullivan, Market and Markets 2016).

I reached out to the CEO Greg Adams of Stabilitas (the company referenced above) to see if he"d be ok with sharing their recent update with you:





No working model exists



Crowdsourcing security data offers enormous promise: real-time, ground-truth intel for everyone in the network. But any crowdsourcing effort comes with significant challenges. With more than 7 billion potential intel sources, crowdsourced reporting needs some controls for reliability. Current models for security information are consumer-centric and do not have mechanisms to protect proprietary or sensitive company data. More importantly, these models leave organizations without the structure they need to safeguard large numbers of people effectively.



...so we’re building one.



Leveraging professionals, vested stakeholders, and Artificial Intelligence (AI) , we’re tackling each of these problems. The concept is simple, develop a broad, trusted network for intelligence-sharing and validation of open-source data to keep one another safe.



Here’s how it works. A user-generated report gets passed to the security manager (or similar role), who confirms the report and shares it to her organization and passes it up to Stabilitas. Our software does a final analysis, then anonymizes and shares the report across our ecosystem while still keeping your company’s data secure and partitioned. There’s trust-based human verification at each level, supported by pattern recognition, sentiment analysis, and other machine learning (more AI) processes the whole way through.



We believe this will provide unparalleled speed, accuracy, and granularity in risk information. Security leaders at Fortune 500 companies have told us how excited they are about this project, particularly when combined with our intelligence and communication platform.



We’re testing the service with a limited group. To be among the first members of the Security Crowd™, click here.



This sort of business will be the future of security and crime control - I"m sure of it.


If you want to know more about what they"re doing feel free to reach out directly to the gents here.


Disclosure: I am an investor in Stabilitas and this is NOT a solicitation to do anything. I"m not paid by them or anyone under this blue sky to say or do anything. I mention the company because, unsurprisingly, I know a little about what they"re up to, and I believe, rightly or wrongly, that this is the space to be in - obviously otherwise I wouldn"t have sent them some of my hard earned moolah. That may turn out to be a terrible idea... or not. I am banking on the latter.


- Chris


"Technology is anything that wasn’t around when you were born." — Alan Kay

Saturday, February 4, 2017

Meet The "Bionic Barrista" Whose Mission Is To Terminate Millions Of Minimum Wage Jobs

Tired of your barista giving you attitude, spitting in your coffee if you only mention Trump, or misspelling your name on your morning cup of joe? Surely a robot could do better. Well, we are about to find out, because on Monday, Cafe X opened its very first robotic cafe in San Francisco’s Metreon shopping center Digital Trends reports. Promising “precision crafted specialty coffee in seconds, the way the roaster intended,” Cafe X thinks that anything a human can do, its machines can do better. Or rather just one machine. 


Nicknamed Gordon, after a Cafe X employee, this robot mans, or robots, two standard professional coffee machines in order to serve up espressos and lattes. In the San Francisco location, customers can grab a cup of coffee with beans from AKA Coffee, Verve Coffee Roasters, or Peet’s. While the coffee itself may not make Cafe X stand out from the competition, the startup hopes that the robot’s efficiency and utility will.


And it surely will, because while its name may be Gordon, its title is the "bionic barrista" and its primary mission is to terminate millions of minimum wage jobs around the globe, boosting the bottom line for major coffee chains everywhere, whose growth has plateaued and who are desperate to cut on overhead costs. Already the average Cafe X coffee costs more than 10%, or 40 cents less than a similar drink at Starbucks. With greater scale the price will only drop.


While offering clear savings for the business, there will be some tradeoffs - introducing automation and robotics into food service will reduce costs and increase efficiency at the expense of customization and a "human touch." Some companies - and clients - may prefer a personal experience to an efficient one, or a customized product. The company behind Gordon, however, disagrees: “There’s a lot of work that goes into great coffee. The Cafe X system is designed for humans and robots to collaborate,” Cafe X explains on its websites. “Smart robotics and machine learning working autonomously allows our operations team to focus on sourcing and using fresh ingredients, maintaining extremely high hygiene standards, and ensuring a great customer experience with every single interaction.”  According to Cafe X, a great customer experience involves efficiency and replicability. “By being automated, we guarantee every cup of coffee you are served from a Cafe X machine is how the roaster intended you to enjoy their coffee,” Cafe X CEO Henry Hu told CNET.


For clients, the efficiency improvements and passed-through cost savings will likely more than offset any loss of a "human touch" - you can order your cup of coffee ahead of time with the Cafe X mobile app and even schedule a pickup time, if you want. Thanks to the robot’s artificial intelligence software, your pre-orders are taken into consideration alongside walk-in orders to ensure that no one is waiting for too long. And with a single robot capable of making 100 to 120 cups of coffee in an hour, you likely won’t be waiting long at all.


And since bionic barristas not only do not expect a weekly paycheck, but need no healthcare of benefits, the choice for Howard Schultz" replacement is clear. Oh, and to those 10,000 refugees who had hoped to get a job at Starbucks, our condolences.


Watch "Gordon" in action here:



... here:



... and here:


Tuesday, January 31, 2017

Online Grocer Debuts "Fruit-Picking Robot" In Latest Blow To Minimum Wage Proponents

In the latest sign that low-skill jobs are doomed to the inevitable, detrimental effects of technological advancements, particularly in era of politicians relentlessly fighting for higher minimum wages, an online grocer in Britain, Ocada, has debuted a prototype of a robotic arm that can pick fruit off an assembly line just like a human worker.  Per a report from BBC, the fruit and vegetable picker is part of a five-year, EU-funded collaboration between five European universities and Disney, called Soma (Soft Manipulation).


Currently, all of Ocado"s customer orders are bagged on an assembly line at a warehouse in Andover, Hampshire by 1,000s of human hands.  But that may be all about to change as Ocado"s technology looks to combine it"s robotic human hand with computer vision and the ability to actually pick fruit and vegetables according to ripeness.





"People have tried suction cups, robot hands with three fingers... What we are trying to do is to actually mimic the human hand."



"The gripper is based on air pressure, which controls the movement of the robotic fingers.



"What we are trying to do is combine computer vision - being able to recognise products by looking at them - with the control aspect which is the gripping aspect."



At the moment, only the gripper is being demonstrated but ultimately the robot will learn to distinguish fruit ripeness through machine learning.



It will also be able to pick other items which require different care - such as wine bottles and detergent.



"Fruit and vegetables are the hardest to pick," said Mr Voica.



And here is a look at the developing technology in action:




And another:




And while the robotic hand is still under development, Ocado told TechCrunch that it is already being tested in a replicated warehouse and will soon be rolled out for live use in it"s Andover facility.





To manipulate different items without damaging them, Ocado’s new robotic arm uses a gripper that is anthropomorphic, or takes the form of the human hand. Dubbed the RBO Hand 2, this element has flexible rubber “fingers,” and uses pressurized air to move them and enable safe, gentle handling of groceries. Researchers at the Technische Universität Berlin (TUB) developed the soft robotic hand, originally. Other types of robotic grippers out there use suction to pick apples, or a ball filled with sand-like material to physically grasp metal parts.



Ocado has already been testing the robot hands in a replicated production warehouse, to figure out if they’re ready for real world use. The answer is now yes. Clarke tells TechCrunch, “We will begin to gradually deploy this at our Andover warehouse, where in due course, [the gripper] will start picking a meaningful fraction of the range of 48,500 items we ship out to customers.” The company will begin the roll out slowly, recording the results of tests in the real world environment. It will still be some time before Ocado customers get a back packed up by SoMa Ocado RBO Hands.



Of course, it"s easy to imagine how such technology can be used to replace millions of low-skilled tasks across a variety of industries, once again highlighting the headwinds facing international labor markets for decades to come.


Do you see what happens, Bernie?  Do you see what happens, Bernie, when you artificially raise minimum wage and make capital projects way more attractive?  This is what happens, Bernie.